research on covid 19 impact on education

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The Effect of COVID-19 on Education

Jacob hoofman.

a Wayne State University School of Medicine, 540 East Canfield, Detroit, MI 48201, USA

Elizabeth Secord

b Department of Pediatrics, Wayne Pediatrics, School of Medicine, Pediatrics Wayne State University, 400 Mack Avenue, Detroit, MI 48201, USA

COVID-19 has changed education for learners of all ages. Preliminary data project educational losses at many levels and verify the increased anxiety and depression associated with the changes, but there are not yet data on long-term outcomes. Guidance from oversight organizations regarding the safety and efficacy of new delivery modalities for education have been quickly forged. It is no surprise that the socioeconomic gaps and gaps for special learners have widened. The medical profession and other professions that teach by incrementally graduated internships are also severely affected and have had to make drastic changes.

• • Virtual learning has become a norm during COVID-19.
• • Children requiring special learning services, those living in poverty, and those speaking English as a second language have lost more from the pandemic educational changes.
• • For children with attention deficit disorder and no comorbidities, virtual learning has sometimes been advantageous.
• • Math learning scores are more likely to be affected than language arts scores by pandemic changes.
• • School meals, access to friends, and organized activities have also been lost with the closing of in-person school.

The transition to an online education during the coronavirus disease 2019 (COVID-19) pandemic may bring about adverse educational changes and adverse health consequences for children and young adult learners in grade school, middle school, high school, college, and professional schools. The effects may differ by age, maturity, and socioeconomic class. At this time, we have few data on outcomes, but many oversight organizations have tried to establish guidelines, expressed concerns, and extrapolated from previous experiences.

General educational losses and disparities

Many researchers are examining how the new environment affects learners’ mental, physical, and social health to help compensate for any losses incurred by this pandemic and to better prepare for future pandemics. There is a paucity of data at this juncture, but some investigators have extrapolated from earlier school shutdowns owing to hurricanes and other natural disasters. 1

Inclement weather closures are estimated in some studies to lower middle school math grades by 0.013 to 0.039 standard deviations and natural disaster closures by up to 0.10 standard deviation decreases in overall achievement scores. 2 The data from inclement weather closures did show a more significant decrease for children dependent on school meals, but generally the data were not stratified by socioeconomic differences. 3 , 4 Math scores are impacted overall more negatively by school absences than English language scores for all school closures. 4 , 5

The Northwest Evaluation Association is a global nonprofit organization that provides research-based assessments and professional development for educators. A team of researchers at Stanford University evaluated Northwest Evaluation Association test scores for students in 17 states and the District of Columbia in the Fall of 2020 and estimated that the average student had lost one-third of a year to a full year's worth of learning in reading, and about three-quarters of a year to more than 1 year in math since schools closed in March 2020. 5

With school shifted from traditional attendance at a school building to attendance via the Internet, families have come under new stressors. It is increasingly clear that families depended on schools for much more than math and reading. Shelter, food, health care, and social well-being are all part of what children and adolescents, as well as their parents or guardians, depend on schools to provide. 5 , 6

Many families have been impacted negatively by the loss of wages, leading to food insecurity and housing insecurity; some of loss this is a consequence of the need for parents to be at home with young children who cannot attend in-person school. 6 There is evidence that this economic instability is leading to an increase in depression and anxiety. 7 In 1 survey, 34.71% of parents reported behavioral problems in their children that they attributed to the pandemic and virtual schooling. 8

Children have been infected with and affected by coronavirus. In the United States, 93,605 students tested positive for COVID-19, and it was reported that 42% were Hispanic/Latino, 32% were non-Hispanic White, and 17% were non-Hispanic Black, emphasizing a disproportionate effect for children of color. 9 COVID infection itself is not the only issue that affects children’s health during the pandemic. School-based health care and school-based meals are lost when school goes virtual and children of lower socioeconomic class are more severely affected by these losses. Although some districts were able to deliver school meals, school-based health care is a primary source of health care for many children and has left some chronic conditions unchecked during the pandemic. 10

Many families report that the stress of the pandemic has led to a poorer diet in children with an increase in the consumption of sweet and fried foods. 11 , 12 Shelter at home orders and online education have led to fewer exercise opportunities. Research carried out by Ammar and colleagues 12 found that daily sitting had increased from 5 to 8 hours a day and binge eating, snacking, and the number of meals were all significantly increased owing to lockdown conditions and stay-at-home initiatives. There is growing evidence in both animal and human models that diets high in sugar and fat can play a detrimental role in cognition and should be of increased concern in light of the pandemic. 13

The family stress elicited by the COVID-19 shutdown is a particular concern because of compiled evidence that adverse life experiences at an early age are associated with an increased likelihood of mental health issues as an adult. 14 There is early evidence that children ages 6 to 18 years of age experienced a significant increase in their expression of “clinginess, irritability, and fear” during the early pandemic school shutdowns. 15 These emotions associated with anxiety may have a negative impact on the family unit, which was already stressed owing to the pandemic.

Another major concern is the length of isolation many children have had to endure since the pandemic began and what effects it might have on their ability to socialize. The school, for many children, is the agent for forming their social connections as well as where early social development occurs. 16 Noting that academic performance is also declining the pandemic may be creating a snowball effect, setting back children without access to resources from which they may never recover, even into adulthood.

Predictions from data analysis of school absenteeism, summer breaks, and natural disaster occurrences are imperfect for the current situation, but all indications are that we should not expect all children and adolescents to be affected equally. 4 , 5 Although some children and adolescents will likely suffer no long-term consequences, COVID-19 is expected to widen the already existing educational gap from socioeconomic differences, and children with learning differences are expected to suffer more losses than neurotypical children. 4 , 5

Special education and the COVID-19 pandemic

Although COVID-19 has affected all levels of education reception and delivery, children with special needs have been more profoundly impacted. Children in the United States who have special needs have legal protection for appropriate education by the Individuals with Disabilities Education Act and Section 504 of the Rehabilitation Act of 1973. 17 , 18 Collectively, this legislation is meant to allow for appropriate accommodations, services, modifications, and specialized academic instruction to ensure that “every child receives a free appropriate public education . . . in the least restrictive environment.” 17

Children with autism usually have applied behavioral analysis (ABA) as part of their individualized educational plan. ABA therapists for autism use a technique of discrete trial training that shapes and rewards incremental changes toward new behaviors. 19 Discrete trial training involves breaking behaviors into small steps and repetition of rewards for small advances in the steps toward those behaviors. It is an intensive one-on-one therapy that puts a child and therapist in close contact for many hours at a time, often 20 to 40 hours a week. This therapy works best when initiated at a young age in children with autism and is often initiated in the home. 19

Because ABA workers were considered essential workers from the early days of the pandemic, organizations providing this service had the responsibility and the freedom to develop safety protocols for delivery of this necessary service and did so in conjunction with certifying boards. 20

Early in the pandemic, there were interruptions in ABA followed by virtual visits, and finally by in-home therapy with COVID-19 isolation precautions. 21 Although the efficacy of virtual visits for ABA therapy would empirically seem to be inferior, there are few outcomes data available. The balance of safety versus efficacy quite early turned to in-home services with interruptions owing to illness and decreased therapist availability owing to the pandemic. 21 An overarching concern for children with autism is the possible loss of a window of opportunity to intervene early. Families of children and adolescents with autism spectrum disorder report increased stress compared with families of children with other disabilities before the pandemic, and during the pandemic this burden has increased with the added responsibility of monitoring in-home schooling. 20

Early data on virtual schooling children with attention deficit disorder (ADD) and attention deficit with hyperactivity (ADHD) shows that adolescents with ADD/ADHD found the switch to virtual learning more anxiety producing and more challenging than their peers. 22 However, according to a study in Ireland, younger children with ADD/ADHD and no other neurologic or psychiatric diagnoses who were stable on medication tended to report less anxiety with at-home schooling and their parents and caregivers reported improved behavior during the pandemic. 23 An unexpected benefit of shelter in home versus shelter in place may be to identify these stressors in face-to-face school for children with ADD/ADHD. If children with ADD/ADHD had an additional diagnosis of autism or depression, they reported increased anxiety with the school shutdown. 23 , 24

Much of the available literature is anticipatory guidance for in-home schooling of children with disabilities rather than data about schooling during the pandemic. The American Academy of Pediatrics published guidance advising that, because 70% of students with ADHD have other conditions, such as learning differences, oppositional defiant disorder, or depression, they may have very different responses to in home schooling which are a result of the non-ADHD diagnosis, for example, refusal to attempt work for children with oppositional defiant disorder, severe anxiety for those with depression and or anxiety disorders, and anxiety and perseveration for children with autism. 25 Children and families already stressed with learning differences have had substantial challenges during the COVID-19 school closures.

High school, depression, and COVID-19

High schoolers have lost a great deal during this pandemic. What should have been a time of establishing more independence has been hampered by shelter-in-place recommendations. Graduations, proms, athletic events, college visits, and many other social and educational events have been altered or lost and cannot be recaptured.

Adolescents reported higher rates of depression and anxiety associated with the pandemic, and in 1 study 14.4% of teenagers report post-traumatic stress disorder, whereas 40.4% report having depression and anxiety. 26 In another survey adolescent boys reported a significant decrease in life satisfaction from 92% before COVID to 72% during lockdown conditions. For adolescent girls, the decrease in life satisfaction was from 81% before COVID to 62% during the pandemic, with the oldest teenage girls reporting the lowest life satisfaction values during COVID-19 restrictions. 27 During the school shutdown for COVID-19, 21% of boys and 27% of girls reported an increase in family arguments. 26 Combine all of these reports with decreasing access to mental health services owing to pandemic restrictions and it becomes a complicated matter for parents to address their children's mental health needs as well as their educational needs. 28

A study conducted in Norway measured aspects of socialization and mood changes in adolescents during the pandemic. The opportunity for prosocial action was rated on a scale of 1 (not at all) to 6 (very much) based on how well certain phrases applied to them, for example, “I comforted a friend yesterday,” “Yesterday I did my best to care for a friend,” and “Yesterday I sent a message to a friend.” They also ranked mood by rating items on a scale of 1 (not at all) to 5 (very well) as items reflected their mood. 29 They found that adolescents showed an overall decrease in empathic concern and opportunity for prosocial actions, as well as a decrease in mood ratings during the pandemic. 29

A survey of 24,155 residents of Michigan projected an escalation of suicide risk for lesbian, gay, bisexual, transgender youth as well as those youth questioning their sexual orientation (LGBTQ) associated with increased social isolation. There was also a 66% increase in domestic violence for LGBTQ youth during shelter in place. 30 LGBTQ youth are yet another example of those already at increased risk having disproportionate effects of the pandemic.

Increased social media use during COVID-19, along with traditional forms of education moving to digital platforms, has led to the majority of adolescents spending significantly more time in front of screens. Excessive screen time is well-known to be associated with poor sleep, sedentary habits, mental health problems, and physical health issues. 31 With decreased access to physical activity, especially in crowded inner-city areas, and increased dependence on screen time for schooling, it is more difficult to craft easy solutions to the screen time issue.

During these times, it is more important than ever for pediatricians to check in on the mental health of patients with queries about how school is going, how patients are keeping contact with peers, and how are they processing social issues related to violence. Queries to families about the need for assistance with food insecurity, housing insecurity, and access to mental health services are necessary during this time of public emergency.

Medical school and COVID-19

Although medical school is an adult schooling experience, it affects not only the medical profession and our junior colleagues, but, by extrapolation, all education that requires hands-on experience or interning, and has been included for those reasons.

In the new COVID-19 era, medical schools have been forced to make drastic and quick changes to multiple levels of their curriculum to ensure both student and patient safety during the pandemic. Students entering their clinical rotations have had the most drastic alteration to their experience.

COVID-19 has led to some of the same changes high schools and colleges have adopted, specifically, replacement of large in-person lectures with small group activities small group discussion and virtual lectures. 32 The transition to an online format for medical education has been rapid and impacted both students and faculty. 33 , 34 In a survey by Singh and colleagues, 33 of the 192 students reporting 43.9% found online lectures to be poorer than physical classrooms during the pandemic. In another report by Shahrvini and colleagues, 35 of 104 students surveyed, 74.5% students felt disconnected from their medical school and their peers and 43.3% felt that they were unprepared for their clerkships. Although there are no pre-COVID-19 data for comparison, it is expected that the COVID-19 changes will lead to increased insecurity and feelings of poor preparation for clinical work.

Gross anatomy is a well-established tradition within the medical school curriculum and one that is conducted almost entirely in person and in close quarters around a cadaver. Harmon and colleagues 36 surveyed 67 gross anatomy educators and found that 8% were still holding in-person sessions and 34 ± 43% transitioned to using cadaver images and dissecting videos that could be accessed through the Internet.

Many third- and fourth-year medical students have seen periods of cancellation for clinical rotations and supplementation with online learning, telemedicine, or virtual rounds owing to the COVID-19 pandemic. 37 A study from Shahrvini and colleagues 38 found that an unofficial document from Reddit (a widely used social network platform with a subgroup for medical students and residents) reported that 75% of medical schools had canceled clinical activities for third- and fourth-year students for some part of 2020. In another survey by Harries and colleagues, 39 of the 741 students who responded, 93.7% were not involved in clinical rotations with in-person patient contact. The reactions of students varied, with 75.8% admitting to agreeing with the decision, 34.7% feeling guilty, and 27.0% feeling relieved. 39 In the same survey, 74.7% of students felt that their medical education had been disrupted, 84.1% said they felt increased anxiety, and 83.4% would accept the risk of COVID-19 infection if they were able to return to the clinical setting. 39

Since the start of the pandemic, medical schools have had to find new and innovative ways to continue teaching and exposing students to clinical settings. The use of electronic conferencing services has been critical to continuing education. One approach has been to turn to online applications like Google Hangouts, which come at no cost and offer a wide variety of tools to form an integrative learning environment. 32 , 37 , 40 Schools have also adopted a hybrid model of teaching where lectures can be prerecorded then viewed by the student asynchronously on their own time followed by live virtual lectures where faculty can offer question-and-answer sessions related to the material. By offering this new format, students have been given more flexibility in terms of creating a schedule that suits their needs and may decrease stress. 37

Although these changes can be a hurdle to students and faculty, it might prove to be beneficial for the future of medical training in some ways. Telemedicine is a growing field, and the American Medical Association and other programs have endorsed its value. 41 Telemedicine visits can still be used to take a history, conduct a basic visual physical examination, and build rapport, as well as performing other aspects of the clinical examination during a pandemic, and will continue to be useful for patients unable to attend regular visits at remote locations. Learning effectively now how to communicate professionally and carry out telemedicine visits may better prepare students for a future where telemedicine is an expectation and allow students to learn the limitations as well as the advantages of this modality. 41

Pandemic changes have strongly impacted the process of college applications, medical school applications, and residency applications. 32 For US medical residencies, 72% of applicants will, if the pattern from 2016 to 2019 continues, move between states or countries. 42 This level of movement is increasingly dangerous given the spread of COVID-19 and the lack of currently accepted procedures to carry out such a mass migration safely. The same follows for medical schools and universities.

We need to accept and prepare for the fact that medial students as well as other learners who require in-person training may lack some skills when they enter their profession. These skills will have to be acquired during a later phase of training. We may have less skilled entry-level resident physicians and nurses in our hospitals and in other clinical professions as well.

The COVID-19 pandemic has affected and will continue to affect the delivery of knowledge and skills at all levels of education. Although many children and adult learners will likely compensate for this interruption of traditional educational services and adapt to new modalities, some will struggle. The widening of the gap for those whose families cannot absorb the teaching and supervision of education required for in-home education because they lack the time and skills necessary are not addressed currently. The gap for those already at a disadvantage because of socioeconomic class, language, and special needs are most severely affected by the COVID-19 pandemic school closures and will have the hardest time compensating. As pediatricians, it is critical that we continue to check in with our young patients about how they are coping and what assistance we can guide them toward in our communities.

Clinics care points

• • Learners and educators at all levels of education have been affected by COVID-19 restrictions with rapid adaptations to virtual learning platforms.
• • The impact of COVID-19 on learners is not evenly distributed and children of racial minorities, those who live in poverty, those requiring special education, and children who speak English as a second language are more negatively affected by the need for remote learning.
• • Math scores are more impacted than language arts scores by previous school closures and thus far by these shutdowns for COVID-19.
• • Anxiety and depression have increased in children and particularly in adolescents as a result of COVID-19 itself and as a consequence of school changes.
• • Pediatricians should regularly screen for unmet needs in their patients during the pandemic, such as food insecurity with the loss of school meals, an inability to adapt to remote learning and increased computer time, and heightened anxiety and depression as results of school changes.

The authors have nothing to disclose.

New Data Show How the Pandemic Affected Learning Across Whole Communities

• Posted May 11, 2023
• By News editor
• Disruption and Crises
• Education Policy
• Evidence-Based Intervention

Today, The Education Recovery Scorecard , a collaboration with researchers at the Center for Education Policy Research at Harvard University (CEPR) and Stanford University’s Educational Opportunity Project , released 12 new state reports and a research brief to provide the most comprehensive picture yet of how the pandemic affected student learning. Building on their previous work, their findings reveal how school closures and local conditions exacerbated inequality between communities — and the urgent need for school leaders to expand recovery efforts now.

The research team reviewed data from 8,000 communities in 40 states and Washington, D.C., including 2022 NAEP scores and Spring 2022 assessments, COVID death rates, voting rates, and trust in government, patterns of social activity, and survey data from Facebook/Meta on family activities and mental health during the pandemic.

>> Read an op-ed by researchers Tom Kane and Sean Reardon in the New York Times .

They found that where children lived during the pandemic mattered more to their academic progress than their family background, income, or internet speed.  Moreover, after studying instances where test scores rose or fell in the decade before the pandemic, the researchers found that the impacts lingered for years.  

“Children have resumed learning, but largely at the same pace as before the pandemic. There’s no hurrying up teaching fractions or the Pythagorean theorem,” said CEPR faculty director Thomas Kane . “The hardest hit communities — like Richmond, Virginia, St. Louis, Missouri, and New Haven, Connecticut, where students fell behind by more than 1.5 years in math — have to teach 150 percent of a typical year’s worth of material for three years in a row — just to catch up. That is simply not going to happen without a major increase in instructional time.  Any district that lost more than a year of learning should be required to revisit their recovery plans and add instructional time — summer school, extended school year, tutoring, etc. — so that students are made whole. ”

“It’s not readily visible to parents when their children have fallen behind earlier cohorts, but the data from 7,800 school districts show clearly that this is the case,” said Sean Reardon , professor of poverty and inequality, Stanford Graduate School of Education. “The educational impacts of the pandemic were not only historically large, but were disproportionately visited on communities with many low-income and minority students. Our research shows that schools were far from the only cause of decreased learning — the pandemic affected children through many ways — but they are the institution best suited to remedy the unequal impacts of the pandemic.”

The new research includes:

• A research brief that offers insights into why students in some communities fared worse than others. 
• An update to the Education Recovery Scorecard, including data from 12 additional states whose 2022 scores were not available in October. The project now includes a district-level view of the pandemic’s effects in 40 states (plus D.C.). 
• A new interactive map that highlights examples of inequity between neighboring school districts. 

Among the key findings:

• Within the typical school district, the declines in test scores were similar for all groups of students, rich and poor, white, Black, Hispanic. And the extent to which schools were closed appears to have had the same effect on all students in a community, regardless of income or race. 
• Test scores declined more in places where the COVID death rate was higher, in communities where adults reported feeling more depression and anxiety during the pandemic, and where daily routines of families were most significantly restricted. This is true even in places where schools closed only very briefly at the start of the pandemic. 
• Test score declines were smaller in communities with high voting rates and high Census response rates — indicators of what sociologists call “institutional trust.” Moreover, remote learning was less harmful in such places. Living in a community where more people trusted the government appears to have been an asset to children during the pandemic.
• The average U.S. public school student in grades 3-8 lost the equivalent of a half year of learning in math and a quarter of a year in reading.

The researchers also looked at data from the decade prior to the pandemic to see how students bounced back after significant learning loss due to disruption in their schooling. The evidence shows that schools do not naturally bounce back: Affected students recovered 20–30% of the lost ground in the first year, but then made no further recovery in the subsequent three to four years.   

“Schools were not the sole cause of achievement losses,” Kane said. “Nor will they be the sole solution. As enticing as it might be to get back to normal, doing so will just leave the devastating increase in inequality caused by the pandemic in place. We must create learning opportunities for students outside of the normal school calendar, by adding academic content to summer camps and after-school programs and adding an optional 13th year of schooling.”

The Education Recovery Scorecard is supported by funds from Citadel founder and CEO Kenneth C. Griffin, Carnegie Corporation of New York, and the Walton Family Foundation.

The latest research, perspectives, and highlights from the Harvard Graduate School of Education

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Subscribe to the brown center on education policy newsletter, megan kuhfeld , megan kuhfeld senior research scientist - nwea @megankuhfeld jim soland , jim soland assistant professor, school of education and human development - university of virginia, affiliated research fellow - nwea @jsoland karyn lewis , and karyn lewis director, center for school and student progress - nwea @karynlew emily morton emily morton research scientist - nwea @emily_r_morton.

March 3, 2022

As we reach the two-year mark of the initial wave of pandemic-induced school shutdowns, academic normalcy remains out of reach for many students, educators, and parents. In addition to surging COVID-19 cases at the end of 2021, schools have faced severe staff shortages , high rates of absenteeism and quarantines , and rolling school closures . Furthermore, students and educators continue to struggle with mental health challenges , higher rates of violence and misbehavior , and concerns about lost instructional time .

As we outline in our new research study released in January, the cumulative impact of the COVID-19 pandemic on students’ academic achievement has been large. We tracked changes in math and reading test scores across the first two years of the pandemic using data from 5.4 million U.S. students in grades 3-8. We focused on test scores from immediately before the pandemic (fall 2019), following the initial onset (fall 2020), and more than one year into pandemic disruptions (fall 2021).

Average fall 2021 math test scores in grades 3-8 were 0.20-0.27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores were 0.09-0.18 SDs lower. This is a sizable drop. For context, the math drops are significantly larger than estimated impacts from other large-scale school disruptions, such as after Hurricane Katrina—math scores dropped 0.17 SDs in one year for New Orleans evacuees .

Even more concerning, test-score gaps between students in low-poverty and high-poverty elementary schools grew by approximately 20% in math (corresponding to 0.20 SDs) and 15% in reading (0.13 SDs), primarily during the 2020-21 school year. Further, achievement tended to drop more between fall 2020 and 2021 than between fall 2019 and 2020 (both overall and differentially by school poverty), indicating that disruptions to learning have continued to negatively impact students well past the initial hits following the spring 2020 school closures.

These numbers are alarming and potentially demoralizing, especially given the heroic efforts of students to learn and educators to teach in incredibly trying times. From our perspective, these test-score drops in no way indicate that these students represent a “ lost generation ” or that we should give up hope. Most of us have never lived through a pandemic, and there is so much we don’t know about students’ capacity for resiliency in these circumstances and what a timeline for recovery will look like. Nor are we suggesting that teachers are somehow at fault given the achievement drops that occurred between 2020 and 2021; rather, educators had difficult jobs before the pandemic, and now are contending with huge new challenges, many outside their control.

Clearly, however, there’s work to do. School districts and states are currently making important decisions about which interventions and strategies to implement to mitigate the learning declines during the last two years. Elementary and Secondary School Emergency Relief (ESSER) investments from the American Rescue Plan provided nearly $200 billion to public schools to spend on COVID-19-related needs. Of that sum, $22 billion is dedicated specifically to addressing learning loss using “evidence-based interventions” focused on the “ disproportionate impact of COVID-19 on underrepresented student subgroups. ” Reviews of district and state spending plans (see Future Ed , EduRecoveryHub , and RAND’s American School District Panel for more details) indicate that districts are spending their ESSER dollars designated for academic recovery on a wide variety of strategies, with summer learning, tutoring, after-school programs, and extended school-day and school-year initiatives rising to the top.

Comparing the negative impacts from learning disruptions to the positive impacts from interventions

To help contextualize the magnitude of the impacts of COVID-19, we situate test-score drops during the pandemic relative to the test-score gains associated with common interventions being employed by districts as part of pandemic recovery efforts. If we assume that such interventions will continue to be as successful in a COVID-19 school environment, can we expect that these strategies will be effective enough to help students catch up? To answer this question, we draw from recent reviews of research on high-dosage tutoring , summer learning programs , reductions in class size , and extending the school day (specifically for literacy instruction) . We report effect sizes for each intervention specific to a grade span and subject wherever possible (e.g., tutoring has been found to have larger effects in elementary math than in reading).

Figure 1 shows the standardized drops in math test scores between students testing in fall 2019 and fall 2021 (separately by elementary and middle school grades) relative to the average effect size of various educational interventions. The average effect size for math tutoring matches or exceeds the average COVID-19 score drop in math. Research on tutoring indicates that it often works best in younger grades, and when provided by a teacher rather than, say, a parent. Further, some of the tutoring programs that produce the biggest effects can be quite intensive (and likely expensive), including having full-time tutors supporting all students (not just those needing remediation) in one-on-one settings during the school day. Meanwhile, the average effect of reducing class size is negative but not significant, with high variability in the impact across different studies. Summer programs in math have been found to be effective (average effect size of .10 SDs), though these programs in isolation likely would not eliminate the COVID-19 test-score drops.

Figure 1: Math COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) Table 2; summer program results are pulled from Lynch et al (2021) Table 2; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span; Figles et al. and Lynch et al. report an overall effect size across elementary and middle grades. We were unable to find a rigorous study that reported effect sizes for extending the school day/year on math performance. Nictow et al. and Kraft & Falken (2021) also note large variations in tutoring effects depending on the type of tutor, with larger effects for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

Figure 2 displays a similar comparison using effect sizes from reading interventions. The average effect of tutoring programs on reading achievement is larger than the effects found for the other interventions, though summer reading programs and class size reduction both produced average effect sizes in the ballpark of the COVID-19 reading score drops.

Figure 2: Reading COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; extended-school-day results are from Figlio et al. (2018) Table 2; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) ; summer program results are pulled from Kim & Quinn (2013) Table 3; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: While Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span, Figlio et al. and Kim & Quinn report an overall effect size across elementary and middle grades. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

There are some limitations of drawing on research conducted prior to the pandemic to understand our ability to address the COVID-19 test-score drops. First, these studies were conducted under conditions that are very different from what schools currently face, and it is an open question whether the effectiveness of these interventions during the pandemic will be as consistent as they were before the pandemic. Second, we have little evidence and guidance about the efficacy of these interventions at the unprecedented scale that they are now being considered. For example, many school districts are expanding summer learning programs, but school districts have struggled to find staff interested in teaching summer school to meet the increased demand. Finally, given the widening test-score gaps between low- and high-poverty schools, it’s uncertain whether these interventions can actually combat the range of new challenges educators are facing in order to narrow these gaps. That is, students could catch up overall, yet the pandemic might still have lasting, negative effects on educational equality in this country.

Given that the current initiatives are unlikely to be implemented consistently across (and sometimes within) districts, timely feedback on the effects of initiatives and any needed adjustments will be crucial to districts’ success. The Road to COVID Recovery project and the National Student Support Accelerator are two such large-scale evaluation studies that aim to produce this type of evidence while providing resources for districts to track and evaluate their own programming. Additionally, a growing number of resources have been produced with recommendations on how to best implement recovery programs, including scaling up tutoring , summer learning programs , and expanded learning time .

Ultimately, there is much work to be done, and the challenges for students, educators, and parents are considerable. But this may be a moment when decades of educational reform, intervention, and research pay off. Relying on what we have learned could show the way forward.

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Executive summary.

In our latest report on unfinished learning, we examine the impact of the COVID-19 pandemic on student learning and well-being, and identify potential considerations for school systems as they support students in recovery and beyond. Our key findings include the following:

• The length of school closures varied widely across the world. School buildings in middle-income Latin America and South Asia were fully or partially closed the longest—for 75 weeks or more. Those in high-income Europe and Central Asia were fully or partially closed for less time (30 weeks on average), as were those in low-income sub-Saharan Africa (34 weeks on average).

About the authors

This article is a collaborative effort by Jake Bryant , Felipe Child , Emma Dorn , Jose Espinosa, Stephen Hall , Topsy Kola-Oyeneyin , Cheryl Lim, Frédéric Panier, Jimmy Sarakatsannis , Dirk Schmautzer , Seckin Ungur , and Bart Woord, representing views from McKinsey’s Education Practice.

• Access to quality remote and hybrid learning also varied both across and within countries. In Tanzania, while school buildings were closed, children in just 6 percent of households listened to radio lessons, 5 percent accessed TV lessons, and fewer than 1 percent participated in online learning. 1 Jacobus Cilliers and Shardul Oza, “What did children do during school closures? Insights from a parent survey in Tanzania,” Research on Improving Systems of Education (RISE), May 19, 2021.
• Furthermore, pandemic-related learning delays stack up on top of historical learning inequities. The World Bank estimates that while students in high-income countries gained an average of 50 harmonized learning outcomes (HLO) points a year prepandemic, students in low-income countries were gaining just 20, leaving those students several years behind. 2 Noam Angrist et al., “Measuring human capital using global learning data,” Nature , March 2021, Volume 592.
• High-performing systems, with relatively high levels of pre-COVID-19 performance, where students may be about one to five months behind due to the pandemic (for example, North America and Europe, where students are, on average, four months behind).
• Low-income prepandemic-challenged systems, with very low levels of pre-COVID-19 learning, where students may be about three to eight months behind due to the pandemic (for example, sub-Saharan Africa, where students are on average six months behind).
• Pandemic-affected middle-income systems, with moderate levels of pre-COVID-19 learning, where students may be nine to 15 months behind (for example, Latin America and South Asia, where students are, on average, 12 months behind).
• The pandemic also increased inequalities within systems. For example, it widened gaps between majority Black and majority White schools in the United States and increased preexisting urban-rural divides in Ethiopia.
• Beyond learning, the pandemic has had broader social and emotional impacts on students globally—with rising mental-health concerns, reports of violence against children, rising obesity, increases in teenage pregnancy, and rising levels of chronic absenteeism and dropouts.
• Lower levels of learning translate into lower future earnings potential for students and lower economic productivity for nations. By 2040, the economic impact of pandemic-related learning delays could lead to annual losses of $1.6 trillion worldwide, or 0.9 percent of total global GDP.
• Resilience: Safely reopen schools for in-person learning while ensuring resilience for future disruptions.
• Reenrollment: Encourage students, families, and teachers to reengage with learning in effective learning environments.
• Recovery: Support students as they recover from the academic and social-emotional impacts of the pandemic, starting with an understanding of each student’s needs.
• Reimagining: Recommit to quality education for every child, doubling down on the fundamentals of educational excellence and innovating to adapt.

In some parts of the world, students, parents, and teachers may be experiencing a novel feeling: cautious optimism. After two years of disruptions from COVID-19, the overnight shift to online and hybrid learning, and efforts to safeguard teachers, administrators, and students, cities and countries are seeing the first signs of the next normal. Masks are coming off. Events are being held in person. Extracurricular activities are back in full swing.

These signs of hope are counterbalanced by the lingering, widespread impact of the pandemic. While it’s too early to catalog all of the ways students have been affected, we are starting to see initial indications of the toll COVID-19 has taken on learning around the world. Our analysis of available data found no country was untouched, but the impact varied across regions and within countries. Even in places with effective school systems and near-universal connectivity and device access, learning delays were significant, especially for historically vulnerable populations. 3 Emma Dorn, Bryan Hancock, Jimmy Sarakatsannis, and Ellen Viruleg, “ COVID-19 and education: An emerging K-shaped recovery ,” McKinsey, December 14, 2021. In many countries that had poor education outcomes before the pandemic, the setbacks were even greater. In those countries, an even more ambitious, coordinated effort will likely be required to address the disruption students have experienced.

Our analysis highlights the extent of the challenge and demonstrates how the impact of the pandemic on learning extends across students, families, and entire communities. Beyond the direct effect on students, learning delays have the potential to affect economic growth: by 2040, according to McKinsey analysis, COVID-19-related unfinished learning could translate into $1.6 trillion in annual losses to the global economy.

Acting decisively in the near term could help to address learning delays as well as the broader social, emotional, and mental-health impact on students. In mobilizing to respond to the pandemic’s effect on student learning and thriving, countries also may need to reassess their education systems—what has been working well and what may need to be reimagined in light of the past two years. Our hope is that this article’s analysis provides a potential starting point for dialogue as nations seek to reinvigorate their education systems.

Gauging the pandemic’s widespread impact on education

One of the challenges in assessing the global effect of the pandemic on learning is the lack of data. Comparative international assessments mostly cover middle- to high-income countries and have not been carried out since the beginning of the pandemic. The next Program for International Student Assessment (PISA), for example, was delayed until 2022. 4 “PISA,” OECD, accessed March 30, 2022. Similarly, many countries had to cancel or defer national assessments. As a result, few nations have a complete data set, and many have no assessment data to indicate relative learning before and since school closures. Accordingly, our methodology used available data augmented by informed assumptions to get a directional picture of the pandemic’s effects on the scholastic achievement and well-being of students.

The pandemic’s impact on student learning

We evaluated the potential effect of the pandemic on student learning by multiplying the amount of time school was disrupted in each country by the estimated effectiveness of the schooling students received during disruptions.

The duration of school closures ran the gamut. During the 102-week period we studied (from the onset of COVID-19 to January 2022), school buildings in Latin America, including the Caribbean, and South Asia were fully or partially closed for 75 weeks or more, while those in Europe and Central Asia were fully or partially closed for an average of 30 weeks (Exhibit 1). Schools in some regions began reopening a few months into the pandemic, but as of January 2022, more than a quarter of the world’s student population resided in school systems where schools were not yet fully open.

Remote and hybrid learning similarly varied widely across and within countries. Some students were supported by internet access, devices, learning management systems, adaptive learning software, live videoconferencing with teachers and peers, and home environments with parents or hired professionals to support remote learning. Others had access to radio or television programs, paper packages, and text messaging. Some students may not have had access to any learning options. 5 What’s next? Lessons on education recovery: Findings from a survey of ministries of education amid the COVID-19 pandemic , UNESCO, UNICEF, the World Bank, and OECD, June 2021. We used the World Bank’s estimates on “mitigation effectiveness” by country income level to account for different levels of access to learning tools and quality through the pandemic (see the forthcoming methodological appendix for more details).

Our model suggests that in the first 23 months since the start of the pandemic, students around the world may have lost about eight months of learning, on average, with meaningful disparities across and within regions and countries. For example, students in South Asia, Latin America, and the Caribbean may be more than a year behind where they would have been absent the pandemic. In North America and Europe, students might be an average of four months behind (Exhibit 2).

The regional numbers only begin to tell the full story. The greater the range of school system performance and resources across regions, the greater the variation in student experiences. Students in Japan and Australia may be less than two months behind, while students in the Philippines and Indonesia may be more than a year behind where they would have been (Exhibit 3).

Within countries, the impact of COVID-19 has also affected individual students differently. Wherever assessments have taken place since the onset of the pandemic, they suggest widening gaps in both opportunity and achievement. Historically vulnerable and marginalized students are at an increased risk of falling further behind.

In the United States, students in majority Black schools were half a year behind in mathematics and reading by fall 2021, while students in majority White schools were just two months behind. 6 “ COVID-19 and education: An emerging K-shaped recovery ,” December 14, 2021. In Ethiopia, students in rural areas achieved under one-third of the expected learning from March to October 2020, while those in urban areas learned less than half of the expected amount. 7 Research on Improving Systems of Education (RISE) , “Learning inequalities widen following COVID-19 school closures in Ethiopia,” blog entry by Janice Kim, Pauline Rose, Ricardo Sabates, Dawit Tibebu Tiruneh, and Tassew Woldehanna, May 4, 2021. Assessments in New South Wales, Australia, detected minimal impact on learning overall, but third-grade students in the most disadvantaged schools experienced two months less growth in mathematics. 8 Leanne Fray et al., “The impact of COVID-19 on student learning in New South Wales primary schools: An empirical study,” The Australian Educational Researcher , 2021, Volume 48.

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Covid-19-related losses on top of historical inequalities.

The learning crisis is not new. In the years before COVID-19, many school systems faced challenges in providing learning opportunities for many of their students. The World Bank estimates that before the pandemic, more than half of students in low- and middle-income countries were living in “learning poverty”—unable to read and understand a simple text by age ten. That number may rise as high as 70 percent due to pandemic-related school disruptions. 9 Joao Azevedo et al., “The state of the global education crisis: A path to recovery,” World Bank Group, December 3, 2021.

The World Bank’s harmonized learning outcomes (HLOs) compare learning achievement and growth across countries. This measure combines multiple global student assessments into one metric, with a range of 625 for advanced attainment and 300 for minimum attainment. According to the World Bank’s 2018 HLO database, students from some countries in the Middle East, North Africa, and South Asia were several years behind their counterparts in North America and Europe before the pandemic (Exhibit 4). 10 Data Blog , “Harmonized learning outcomes: transforming learning assessment data into national education policy reforms,” blog entry by Harry A. Patrinos and Noam Angrist, August 12, 2019.

Students in these countries were also progressing more slowly each year in school. While students in high-income countries may have been gaining 50 HLO points in a year, students in low-income countries were gaining just 20. In other words, not much learning was happening in some countries even before the pandemic.

Prepandemic learning levels and pandemic-related learning delays interacted in different ways in different countries and regions. Although each country is unique, three archetypes emerge based on the performance of education systems (Exhibit 5).

High-performing systems. Countries in this archetype generally had higher pre-COVID-19 learning levels. Systems had more capacity for remote learning, and school buildings remained closed for shorter time periods. 11 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. Data suggest that after the initial shock of the pandemic in 2020, learning delays increased only moderately with subsequent school closures in the 2021–22 school year. Some high-income countries seem to show little evidence of decreased learning overall. According to the Australian National Assessment Program–Literacy and Numeracy (NAPLAN), the COVID-19 pandemic did not have a statistically significant impact on average student literacy and numeracy levels, even in Victoria, where learning was remote for more than 120 days. 12 “Highlights from Victorian preliminary results in NAPLAN 2021,” Victoria state government, August 26, 2021; Adam Carey, Melissa Cunningham, and Anna Prytz, “‘Children have suffered enormously’: School closures leave experts divided,” The Age , Melbourne, July 25, 2021. However, in many high-income countries, the impact of the pandemic on learning remained significant. Assessments of student learning in the United States in fall 2021 suggested students had fallen four months behind in mathematics and three months behind in reading. 13 “ COVID-19 and education: An emerging K-shaped recovery ,” December 14, 2021. Inequalities in learning also increased within many of these countries, with historically marginalized students most affected.

Lower-income, prepandemic-challenged systems. This archetype consists of mostly low-income and lower-middle-income countries with very low levels of pre-COVID-19 learning. When the pandemic struck, school buildings closed for varying periods of time, 14 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. with limited options for remote learning. In Tanzania, for example, schools were closed for 15 weeks, and during this period, just 6 percent of households reported that their children listened to radio lessons, 5 percent watched TV lessons, and fewer than 1 percent accessed educational programs on the internet. 15 Jacobus Cilliers and Shardul Oza, “What did children do during school closures? Insights from a parent survey in Tanzania,” Research on Improving Systems of Education (RISE), May 19, 2021. Across the analyzed time period, schools in sub-Saharan Africa were fully open for more weeks, on average, than schools in any other region. As a result, the pandemic’s impact on learning was relatively muted, even though many of these systems faced challenges with effective remote learning. 16 A report of six countries in Africa, for example, found limited impact of the pandemic on already-low student outcomes. For more information, see “MILO: Monitoring impacts on learning outcomes,” UNESCO, accessed March 11, 2022.

These relatively smaller pandemic learning delays are likely due in part to the limited progress students were making in schools before COVID-19. 17 World Bank blogs , “Harmonized learning outcomes: Transforming learning assessment data into national education policy reforms,” blog entry by Harry A. Patrinos and Noam Angrist, August 12, 2019. If students weren’t progressing scholastically when schools were open, closures were likely to have less impact. In Tanzania before the pandemic, three-quarters of students in grade three could not read a basic sentence. 18 “What did children do during school closures?,” May 19, 2021.

Pandemic-affected middle-income systems. School systems in Latin American and South Asian countries had low to moderate performance before COVID-19. Many middle-income countries in this group did have some capacity to plan and roll out remote-learning options, especially in urban areas. 19 “Responses to Educational Disruption Survey (REDS),” UNESCO, accessed March 11, 2022. However, pandemic-related disruptions caused widespread school closures for extended periods of time—more than 50 weeks in some countries. 20 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. The resulting learning delays may represent a true crisis for major economies such as India, Indonesia, and Mexico, where students are more than a year behind, on average.

While some students may have just learned more slowly than they would have absent the pandemic, others in this archetype may have actually slipped backward. A study by the Azim Premji Foundation suggests that as early as January 2021, more than 90 percent of students assessed in India have lost at least one language ability (such as reading words or writing simple sentences), while more than 80 percent lost a math ability (for example, identifying single- and double-digit numbers or naming shapes). 21 Loss of learning during the pandemic , Azim Premji Foundation, February 2021. This pattern could be particularly challenging, since higher-order skills are increasingly important in middle-income countries with rising levels of workplace automation. McKinsey’s “ Jobs lost, jobs gained ” report 22 For more information, see “ Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages ,” McKinsey Global Institute, November 28, 2017. suggests India may need 34 million to 100 million more high school graduates by 2030 to fill workplace demands. The pandemic has put existing high school graduation rates at risk, let alone the vast expansion required to meet future demand for workers.

The pandemic’s effects beyond learning

Much of the dialogue around school systems focuses on educational achievement, but schools offer more than academic instruction. A school system’s contributions may include social interaction; an opportunity for students to build relationships with caring adults; a base for extracurricular activities, from the arts to athletics; an access point for physical- and mental-health services; and a guarantee of balanced meals on a regular basis. The school year may also enable students to track their progress and celebrate milestones. When schools had to close for extended periods of time or move to hybrid learning, students were deprived of many of these benefits.

The pandemic’s impact on the social-emotional and mental and physical health of students has been measured even less than its impact on academic achievement, but early indications are concerning. Save the Children reports that 83 percent of children and 89 percent of parents globally have reported an increase in negative feelings since the pandemic began. 23 The hidden impact of COVID-19 on child protection and wellbeing , Save the Children International, September 2020. In the United States, one in three parents said they were very or extremely worried about their child’s mental health in spring 2021, with rising reported levels of student anxiety, depression, social withdrawal, and lethargy. 24 Emma Dorn, Bryan Hancock, Jimmy Sarakatsannis, and Ellen Viruleg, “ COVID-19 and education: The lingering effects of unfinished learning ,” McKinsey, July 27, 2021. Parents of Black and Hispanic students, the segments most affected by academic unfinished learning, also reported higher rates of concern about their student’s mental health and engagement with school. A UK survey found 53 percent of girls and 44 percent of boys aged 13 to 18 had experienced symptoms or trauma related to COVID-19. 25 Report1: Impact of COVID-19 on young people aged 13-24 in the UK- preliminary findings , PsyArXiv, January 20, 2021. In Bangladesh, a cross-sectional study revealed that 19.3 percent of children suffered moderate mental-health impacts, while 7.2 percent suffered from extreme mental-health effects. 26 Rajon Banik et al., “Impact of COVID-19 pandemic on the mental health of children in Bangladesh: A cross-sectional study,” Children and Youth Services Review , October 2020, Volume 117. Reports of violence against children rose in many countries. 27 “Publications,” Young Lives, accessed March 22, 2022. The pandemic affected physical health as well. Studies from the United States 28 Roger Riddell, “CDC: Child obesity jumped during COVID-19 pandemic,” K-12 Dive , September 24, 2021. and the United Kingdom 29 The annual report of Her Majesty’s chief inspector of education, children’s services and skills 2020/21 , Ofsted, December 7, 2021. show rising rates of childhood obesity. In Latin America and the Caribbean, more than 80 million children stopped receiving hot meals. 30 “We can move to online learning, but not online eating,” United Nations World Food Program, March 26, 2020. In Uganda, a record number of monthly teenage pregnancies—more than 32,000—were recorded from March 2020 to September 2021. 31 “Uganda overwhelmed by 32,000 monthly teen pregnancies,” Yeni Şafak , December 12, 2021.

Some students may never return to formal schooling at all. Even in high-income systems, levels of chronic absenteeism are rising, and some students have not reengaged in school. In the United States, 1.7 million to 3.3 million eighth to 12th graders may drop out of school because of the pandemic. In low- and middle-income countries, the situation could be far worse. Up to one-third of Ugandan students may not return to the classroom. This pattern is in line with past historical crises involving school closures. After the Ebola pandemic, 13 percent of students in Sierra Leone and 25 percent of students in Liberia dropped out of school, with girls and low-income students most affected. 32 The socio-economic impacts of Ebola in Liberia , World Bank, April 15, 2015; The socio-economic impacts of Ebola in Sierra Leone , World Bank, June 15, 2015. Among the poorest primary-school students in Sierra Leone, dropout rates increased by more than 60 percent. 33 William C. Smith, “Consequences of school closure on access to education: Lessons from the 2013-2016 Ebola pandemic,” International Review of Education , April 2021, Volume 67. This may result in reduced employment opportunities and lifelong earnings potential for many of these students.

The potential of long-term economic damage

Education can affect not just an individual’s future earnings and well-being but also a country’s economic growth and vitality. Research suggests higher levels of education lead to increased labor productivity and enhance an economy’s capacity for innovation. Unless the pandemic’s impact on student learning can be mitigated and students can be supported to catch up on missed learning, the global economy could experience lower GDP growth over the lifetime of this generation.

We estimate by 2040, unfinished learning related to COVID-19 could translate to annual losses of $1.6 trillion to the global economy, or 0.9 percent of predicted total GDP (Exhibit 6).

Although the total dollar amount of forgone GDP is highest in the largest economies of the world (encompassing East Asia, Europe, and North America), the relative impact is highest in regions with the greatest learning delays. In Latin America and the Caribbean, pandemic-related school closures could result in losses of more than 2 percent of GDP annually by 2040 and in subsequent years.

Economic impact could be affected further if students don’t return to school and cease learning altogether.

Identifying potential solutions

The response to the learning crisis will likely vary from country to country, based upon preexisting educational performance, the depth and breadth of learning delays, and system resources and capacity to respond. That said, all school systems will likely need to plan across multiple horizons:

As 2022 began, more than 95 percent of school systems around the world were at least partially open for traditional in-person learning. 34 “Responses to Educational Disruption Survey (REDS),” UNESCO, 2022, accessed March 11, 2022. That progress is encouraging but tenuous. Many systems reopened only to close down again when another wave of COVID-19 caused additional disruptions. Even within partially open systems, not all students have access to in-person learning, and many are still attending partial days or weeks. Building resilience could mean ensuring protocols are in place for safe and supportive in-person learning, and ensuring plans are in place to provide remote options that support the whole child at the system, school, and student levels in response to future crises. School systems can also benefit by creating the flexibility to change policies and procedures as new data and circumstances arise.

COVID-19 and education: The lingering effects of unfinished learning

Reenrollment.

Opening buildings and embedding effective safety precautions have been challenging for many systems, but ensuring students and teachers actually turn up and reengage with learning is perhaps even more difficult. Even where in-person learning has resumed, many students have not returned or remain chronically absent. 35 Indira Dammu, Hailly T.N. Korman, and Bonnie O’Keefe, Missing in the margins 2021: Revisiting the COVID-19 attendance crisis , Bellwether Education Partners, October 21, 2021. Families may still have safety worries about in-person learning. Some students may have found jobs and now rely on that income. 36 Elias Biryabarema, “Student joy, dropout heartache as Uganda reopens schools after long COVID-19 shutdown,” Reuters, January 10, 2022. Others may have become pregnant or now act as caregivers at home. 37 Brookings Education Plus Development , “What do we know about the effects of COVID-19 on girls’ return to school?,” blog entry by Erin Ganju, Christina Kwauk, and Dana Schmidt, September 22, 2021. Still others may feel so far behind academically or so disconnected from the school environment at a social level that a return feels impossible. A multipronged approach could be helpful to understand the barriers students may face, how those could differ across student segments, and ways to support all students in continuing their educational journeys.

Systems could consider a tiered approach to support reengagement. Tier-one interventions could be rolled out for all students and include both improving school offerings for families and students and communicating about enhanced services. This might involve back-to-school awareness campaigns at the national and community levels featuring respected community members, clear communication of safety protocols, access to free food and other basic needs on campuses, and the promotion of a positive school climate with deep family engagement.

Tier-two interventions, which could be directed at students who are at heightened risk of not returning to school, may involve more targeted support. These efforts might include community events and canvassing to bring school buses or mobile libraries to historically marginalized neighborhoods, phone- or text-banking aimed at students who have not returned to school, or summer opportunities (including fun reorientation activities) to convince students to return to the school campus. At the student level, it could include providing some groups of students with deeper learning or social-emotional recovery services to help them reintegrate into school.

Tier-three interventions encompass more intensive and specialized support. These efforts may include visits to the homes of individual students or new educational environments tailored to student needs—for example, night schools for students who need to complete high school while working.

Once students are back in school, many may need support to recover from the academic and social-emotional effects of the pandemic. Indeed, while academic recovery seems daunting, supporting the mental-health and social-emotional needs of students may end up being the bigger challenge. 38 Protecting youth mental health: The U.S. surgeon general’s advisory , U.S. Department of Health and Human Services, 2021. This process starts with a recognition that each child is unique and that the pandemic has affected different students in different ways. Understanding each student’s situation, in terms of both learning and well-being, is important at the classroom level, with teachers and administrators trained to interpret cues from students and refer them to more intensive support when necessary. Assessments will likely also be needed at the school and system levels to plan the response.

With an understanding of both the depth and breadth of student needs, systems and schools could consider three levers of academic acceleration: more time, more dedicated attention, and more focused content. Implementation of these levers will likely vary by context, but the overall goals are the same: to overcome both historical gaps and new COVID-19-related losses, and to do so across academic and whole-child indicators.

In high-income countries, digital formative assessments could help determine in real time what students know, where they may have gaps, and what the next step could be for each child. More relational tactics can be incorporated alongside digital assessments, such as teachers taking the time to connect with each child around a simple reading assessment, which may rebuild relationships and connectivity while assessing student capabilities. Schools could also consider universal mental-health diagnostics and screeners, and train teachers and staff to recognize the signs of trauma in students.

Once schools have identified students who need academic support, proven, evidence-based solutions could support acceleration in high-income school systems. High-dosage tutoring, for example, could enable students to learn one to two additional years of mathematics in a single year. Delivered three to five times a week by trained college graduates during the school day on top of regular math instruction, this type of tutoring is labor and capital intensive but has a high return on investment. Acceleration academies, which provide 25 hours of targeted instruction in reading to small groups of eight to 12 students during vacations, have helped students gain three months of reading in just one week. Exposing students to grade-level content and providing them with targeted supports and scaffolds to access this content has improved course completion rates by two to four times over traditional “re-teaching” remediation approaches.

With an understanding of both the depth and breadth of student needs, systems and schools could consider three levers of academic acceleration: more time, more dedicated attention, and more focused content.

In low- and middle-income countries, where learning delays may have been much greater and where the financial and human-capital resources for education can be more limited, different implementation approaches may be required. Simple, fast, inexpensive, and low-stakes evaluations of student learning could be carried out at the classroom level using pen and paper, oral assessments, and mobile data collection, for example.

Solutions for supporting the acceleration of student learning in these contexts could start with ensuring foundational literacy and numeracy (FLN), prioritizing essential standards and content. Evidence-based teaching methods could speed up learning; for example, Pratham’s Teaching at the Right Level (TaRL) approach—which groups children by learning needs, rather than by age or grade, and dedicates time to basic skills with continual reassessment—has led to improvements of more than a year of learning in classrooms and summer camps. 39 Improvements of 0.2 to 0.7 standard deviations; assuming that one year of learning ranges from 0.2 of a standard deviation in low income countries and 0.5 of a standard deviation in high income countries, in accordance with World Bank assumptions:; João Pedro Azevedo et al., Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes , World Bank working paper 9284, June 2020; David K. Evans and Fei Yuan, Equivalent years of schooling , World Bank working paper 8752, February 2019. Even with the application of existing approaches, more time in class may be required—with options to extend the school year or school day to support students. Widespread tutoring may not be realistic in some countries, but peer-to-peer tutoring and cross-grade mentoring and coaching could supplement in-class efforts. 40 COVID-19 response–remediation: Helping students catch up on lost learning, with a focus on closing equity gaps , UNESCO, July 2020.

Reimagining

In addition to accelerating learning in the short term, systems can also use this moment to consider how to build better systems for the future. This may involve both recommitting to the core fundamentals of educational excellence and reimagining elements of instruction, teaching, and leadership for a post-COVID-19 world. 41 Jake Bryant, Emma Dorn, Stephen Hall, and Frédéric Panier, “ Reimagining a more equitable and resilient K-12 education system ,” McKinsey, September 8, 2020. A lot of ground could be covered by rolling out existing evidence-based interventions at scale—recommitting to core literacy and numeracy skills, high-quality instructional materials, job-embedded teacher coaching, and effective performance management. Recommitting to these basics, however, may not be enough. Systems can also innovate across multiple dimensions: providing whole-child supports, using technology to improve access and quality, moving toward competency-based learning, and rethinking teacher preparation and roles, school structures, and resource allocation.

For example, many systems are reemphasizing the importance of caring for the whole child. Integrating social-emotional learning for all students, providing trauma-informed training for teachers and staff, 42 “Welcome to the trauma-informed educator training series,” Mayerson Center for Safe and Healthy Children, accessed March 22, 2022. and providing counseling and more intensive support on and off campus for some students could provide supportive schooling environments beyond immediate crisis support. 43 “District student wellbeing services reflection tool,” Chiefs for Change, January 2022. A UNESCO survey suggests that 78 percent of countries offered psychosocial and emotional support to teachers as a response to the pandemic. 44 What’s next? Lessons on education recovery , June 2021. Looking forward, the State of California is launching a $3 billion multiyear transition to community schools, taking an integrated approach to students’ academic, health, and social-emotional needs in the context of the broader community in which those students live. 45 John Fensterwald, “California ready to launch $3 billion, multiyear transition to community schools,” EdSource, January 31, 2022.

The role of education technology in instruction is another much-debated element of reimagining. Proponents believe education technology holds promise to overcome human-capital challenges to improved access and quality, especially given the acceleration of digital adoption during the pandemic. Others point out that historical efforts to harness technology in education have not yielded results at scale. 46 Jake Bryant, Felipe Child, Emma Dorn, and Stephen Hall, “ New global data reveal education technology’s impact on learning ,” McKinsey, June 12, 2020.

Numerous experiments are under way in low- and middle-income countries where human capital  challenges are the greatest. Robust solar-powered tablets loaded with the evidence-based literacy and numeracy app one billion led to learning gains of more than four months 47 “Helping children achieve their full potential,” Imagine Worldwide, accessed March 22, 2022. in Malawi, with plans to roll out the program across the country’s 5,300 primary schools. 48 “Partners and projects,” onebillion.org, accessed March 22, 2022. NewGlobe’s digital teacher guides provide scripted lesson plans on devices designed for low-infrastructure environments. In Nigeria, students using these tools progressed twice as fast in numeracy and three times as fast in literacy as their peers. 49 “The EKOEXCEL effect,” NewGlobe Schools, accessed March 22, 2022. As new solutions are rolled out, it will likely be important to continually evaluate their impact compared with existing evidence-based approaches to retain what is working and discard that which is not.

Charting a potential path forward

There is no precedent for global learning delays at this scale, and the increasing automation of the workforce advances the urgency of supporting students to catch up to—and possibly exceed—prepandemic education levels to thrive in the global economy. Systems will likely need resources, knowledge, and organizational capacity to make progress across these priorities.

Even before COVID-19, UNESCO estimated that low- and middle-income countries faced a funding gap of $148 billion a year to reach universal preprimary, primary, and secondary education by 2030 as required by UN Sustainable Development Goal 4. As a result of the pandemic, that gap has widened to $180 billion to $195 billion a year. 50 Act now: Reduce the impact of COVID-19 on the cost of achieving SDG 4 , UNESCO, September 2020. Even if that funding gap were closed, the result would be increased enrollment, not improvements in learning. UNESCO estimates that just 3 percent of global stimulus funds related to COVID-19 have been directed to education , 97 percent of which is concentrated in high-income countries. 51 “Uneven global education stimulus risks widening learning disparities,” UNESCO, October 19, 2021.

In many countries, shortages of teachers and administrators are just as pressing as the lack of funding. Many teachers in Uganda weren’t paid during the pandemic and have found new careers. 52 Alon Mwesigwa, “’I’ll never go back’: Uganda’s schools at risk as teachers find new work during Covid,” Guardian , September 30, 2021. Even high-income countries are grappling with teacher shortages. In the United States, 40 percent of district leaders and principals describe their current staff shortages as “severe” or “very severe.” 53 Mark Lieberman, “How bad are school staffing shortages? What we learned by asking administrators,” EducationWeek , October 12, 2021. Fully addressing pandemic-related learning losses will require a full accounting of the cost and a long-term commitment, recognizing the critical importance of investments in education for future economic growth and stability.

Countries do not need to reinvent the wheel or go it alone. Many existing resources catalog evidence-based practices relevant to different contexts, both historical approaches and those specific to COVID-19 recovery. For high-income countries, the Education Endowment Foundation, Annenberg’s EdResearch for Recovery platform, and the Collaborative for Student Success resources for states and districts in the United States provide research-based guidance on solutions.

In many countries, shortages of teachers and administrators are just as pressing as the lack of funding.

For low- and middle-income countries, materials developed in partnership with UNESCO, UNICEF, and the World Bank include tools to support FLN, Continuous and Accelerated Learning, and teacher capacity (Teach and Coach). UNESCO’s COVID-19 Response Toolkit provides guidance across income levels. Collaboration across schools, regions, and countries could also promote knowledge sharing at a time of evolving needs and practices—from webinars to active communities of practice and shared-learning collaboratives.

Organizing for the response across these multiple levels is a challenge even for the most well-resourced and sophisticated systems. Our recent research found 80 percent of government efforts to transform performance don’t fully meet their objectives. 54 “ Delivering for citizens: How to triple the success rate of government transformations ,” McKinsey, May 31, 2018. Success will likely require a relentless focus on implementation and execution, with multiple feedback loops to achieve continuous learning and improvement.

The COVID-19 pandemic was indisputably a global health and economic crisis. Our research suggests it also caused an education crisis on a scale never seen before.

The pandemic also showed, however, that innovation and collaboration can arise out of hardship. The global education community has an opportunity to come together to respond, bringing evidence-based practices at scale to every classroom. Working together, donors and investors, school systems and districts, principals and teachers, and parents and families can ensure that the students who endured the pandemic are not a lost generation but are instead defined by their resilience.

Jacob Bryant is a partner in McKinsey’s Seattle office; Felipe Child is a partner in the Bogotá office, where Jose Espinosa is an associate partner; Emma Dorn is a senior expert in the Silicon Valley office; Stephen Hall is a partner in the Dubai office, where Dirk Schmautzer is a partner; Topsy Kola-Oyeneyin is a partner in the Lagos office; Cheryl Lim is a partner in the Singapore office; Frédéric Panier is a partner in the Brussels office; Jimmy Sarakatsannis is a senior partner in the Washington, DC, office; and Seckin Ungur is a partner in the Sydney office, where Bart Woord is an associate partner.

The authors wish to thank Annie Chen, Kunal Kamath, An Lanh Le, Sadie Pate, and Ellen Viruleg for their contributions to this article.

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Nearly 147 million children missed more than half of their in-person schooling between 2020 and 2022. Image:  Unsplash/Taylor Flowe

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• As well as its health impacts, COVID-19 had a huge effect on the education of children – but the full scale is only just starting to emerge.
• As pandemic lockdowns continue to shut schools, it’s clear the most vulnerable have suffered the most.
• Recovering the months of lost education must be a priority for all nations.

When the World Health Organization declared COVID-19 to be a pandemic on 11 March 2020, few could have foreseen the catastrophic effects the virus would have on the education of the world’s children.

During the first 12 months of the pandemic, lockdowns led to 1.5 billion students in 188 countries being unable to attend school in person, causing lasting effects on the education of an entire generation .

As an OECD report into the effects of school closures in 2021 put it: “Few groups are less vulnerable to the coronavirus than school children, but few groups have been more affected by the policy responses to contain the virus.”

Although many school closures were announced as temporary measures, these shutdowns persisted throughout 2020 – and even beyond in some cases.

As late as March 2022, UNICEF reported that 23 countries, home to around 405 million schoolchildren, had not yet fully reopened their schools . As China battled to contain new COVID-19 outbreaks, schools were closed in Shanghai and Xian in October 2022.

COVID has ended education for some

Nearly 147 million children missed more than half of their in-person schooling between 2020 and 2022, UNICEF says. And it warns that many, especially the most vulnerable, are at risk of dropping out of education altogether.

The danger is highlighted by UNICEF data showing that 43% of students did not return when schools in Liberia reopened in December 2020. The number of out-of-school children in South Africa tripled from 250,000 to 750,000 between March 2020 and July 2021, UNICEF adds.

When schools in Uganda reopened after being closed for two years, almost one in ten children were missing from classrooms. And in Malawi, the dropout rate among girls in secondary education increased by 48% between 2020 and 2021.

Out-of-school children are among the most vulnerable and marginalized children in society, says UNICEF. They are the least likely to be able to read, write or do basic maths, and when not in school they are at risk of exploitation and a lifetime of poverty and deprivation, it says.

Lost learning time

Even when children are in school, the amount of learning time they have lost to the pandemic is compounding what UNICEF describes as “a desperately poor level of learning” in 32 low-income countries it has studied.

“In the countries analyzed, the current pace of learning is so slow that it would take seven years for most schoolchildren to learn foundational reading skills that should have been grasped in two years, and 11 years to learn foundational numeracy skills,” the charity says.

Analysis of the crisis by UNESCO, published in November 2022, found that the most vulnerable learners have been hardest hit by the lack of schooling. It added that progress towards the United Nations Sustainable Development Goal for Education had been set back.

In Latin America and the Caribbean – a region that suffered one of the longest periods of school closures – average primary education scores in reading and maths could have slipped back to a level last seen 10 years ago , the World Bank says.

Four out of five sixth graders may not be able to adequately understand and interpret a text of moderate length, the bank says. As a result, these students are likely to earn 12% less over their lifetime than if their education had not been curtailed by the pandemic, it estimates.

Widening the achievement gap

In India, the pandemic has widened the gaps in learning outcomes among schoolchildren with those from disenfranchised and vulnerable families falling furthest behind, according to a 2022 report by the World Economic Forum.

Even where schools tried to keep teaching using remote learning, the socio-economic divide was perpetuated. In the United States, a study found children’s achievement in maths fell by 50% more in less well-off areas , compared to those in more affluent neighbourhoods.

One year on: we look back at how the Forum’s networks have navigated the global response to COVID-19.

Using a multistakeholder approach, the Forum and its partners through its COVID Action Platform have provided countless solutions to navigate the COVID-19 pandemic worldwide, protecting lives and livelihoods.

Throughout 2020, along with launching its COVID Action Platform , the Forum and its Partners launched more than 40 initiatives in response to the pandemic.

The work continues. As one example, the COVID Response Alliance for Social Entrepreneurs is supporting 90,000 social entrepreneurs, with an impact on 1.4 billion people, working to serve the needs of excluded, marginalized and vulnerable groups in more than 190 countries.

Read more about the COVID-19 Tools Accelerator, our support of GAVI, the Vaccine Alliance, the Coalition for Epidemics Preparedness and Innovations (CEPI), and the COVAX initiative and innovative approaches to solve the pandemic, like our Common Trust Network – aiming to help roll out a “digital passport” in our Impact Story .

Consultancy firm McKinsey says that US students were on average five months behind in mathematics and four months behind in reading by the end of the 2020-21 school year. Disadvantaged students were hit hardest, with Black students losing six months of learning on average.

Researchers in Japan found a similar pattern, with disadvantaged children and the youngest suffering most from school closures. They said the adverse effects of being forced to study at home lasted longest for those with poorest living conditions .

However, in Sweden, where schools stayed open during the pandemic, there was no decline in reading comprehension scores among children from all socio-economic groups, leading researchers to conclude that the shock of the pandemic alone did not affect students’ performance.

Getting learning back on track

So what can be done to help the pandemic generation to recover their lost learning ?

The World Bank outlines 10 actions countries can take, including getting schools to assess students’ learning loss and monitor their progress once they are back at school.

Catch-up education and measures to ensure that children don’t drop out of school will be essential, it says. These could include changing the school calendar, and amending the curriculum to focus on foundational skills.

There’s also a need to enhance learning opportunities at home, such as by distributing books and digital devices if possible. Supporting parents in this role is also critical, the bank says.

Teachers will also need extra help to avoid burnout, the bank notes. It highlights a “need to invest aggressively in teachers’ professional development and use technology to enhance their work”.

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Open Access

Peer-reviewed

Research Article

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

Contributed equally to this work with: Brennan Klein, Nicholas Generous

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected] (BK); [email protected] (AV)

¤ Current address: Network Science Institute, Northeastern University, 177 Huntington Ave. #213, Boston, Massachusetts, United States of America

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America

Roles Conceptualization, Data curation, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America, Biosecurity and Public Health Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America

Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

Roles Data curation, Writing – review & editing

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, College of Engineering, Northeastern University, Boston, Massachusetts, United States of America

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, College of Professional Studies, Northeastern University, Boston, Massachusetts, United States of America

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Network Science Institute, Northeastern University, Boston, United States of America

Roles Methodology, Writing – original draft, Writing – review & editing

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, Shorenstein Center on Media, Politics and Public Policy, Harvard University, Massachusetts, Boston, United States of America

Roles Conceptualization, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Roles Data curation, Project administration, Resources, Writing – original draft, Writing – review & editing

Affiliations Educational Studies Department, Davidson College, Davidson, North Carolina, United States of America, College Crisis Initiative, Davidson College, Davidson, North Carolina, United States of America

Roles Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliations Network Science Institute, Northeastern University, Boston, United States of America, Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America, Santa Fe Institute, Santa Fe, United States of America

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

• Brennan Klein, 
• Nicholas Generous, 
• Matteo Chinazzi, 
• Zarana Bhadricha, 
• Rishab Gunashekar, 
• Preeti Kori, 
• Bodian Li, 
• Stefan McCabe, 
• Jon Green, 

• Published: June 23, 2022
• https://doi.org/10.1371/journal.pdig.0000065
• Reader Comments

With a dataset of testing and case counts from over 1,400 institutions of higher education (IHEs) in the United States, we analyze the number of infections and deaths from SARS-CoV-2 in the counties surrounding these IHEs during the Fall 2020 semester (August to December, 2020). We find that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester; whereas before and after the semester, these two groups had almost identical COVID-19 incidence. Additionally, we see fewer cases and deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. To perform these two comparisons, we used a matching procedure designed to create well-balanced groups of counties that are aligned as much as possible along age, race, income, population, and urban/rural categories—demographic variables that have been shown to be correlated with COVID-19 outcomes. We conclude with a case study of IHEs in Massachusetts—a state with especially high detail in our dataset—which further highlights the importance of IHE-affiliated testing for the broader community. The results in this work suggest that campus testing can itself be thought of as a mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to mitigating the spread of COVID-19 in a pre-vaccine environment.

Author summary

The ongoing COVID-19 pandemic has upended personal, public, and institutional life and has forced many to make decisions with limited data on how to best protect themselves and their communities. In particular, institutes of higher education (IHEs) have had to make difficult choices regarding campus COVID-19 policy without extensive data to inform their decisions. To better understand the relationship between IHE policy and COVID-19 mitigation, we collected data on testing, cases, and campus policy from over 1,400 IHEs in the United States and analyzed the number of COVID-19 infections and deaths in the counties surrounding these IHEs. Our study found that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester—controlling for age, race, income, population, and urban/rural designation. Among counties with IHEs that did return in-person, we see fewer deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. Our study suggests that campus testing can be seen as another useful mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to controlling the spread of COVID-19 in the general population.

Citation: Klein B, Generous N, Chinazzi M, Bhadricha Z, Gunashekar R, Kori P, et al. (2022) Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy. PLOS Digit Health 1(6): e0000065. https://doi.org/10.1371/journal.pdig.0000065

Editor: Yuan Lai, Tsinghua University, CHINA

Received: December 5, 2021; Accepted: May 18, 2022; Published: June 23, 2022

Copyright: © 2022 Klein et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The dataset and Python code to reproduce the analyses and construction of the database is available at https://github.com/jkbren/campus-covid .

Funding: A.V. and M.C. acknowledge support from COVID Supplement CDC-HHS-6U01IP001137-01 and Cooperative Agreement no. NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE). A.V. acknowledges support from the Chleck Foundation. N.G. acknowledges LA-UR-21-25928. The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the funding agencies, the National Institutes of Health, or U.S. Department of Health and Human Services. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: S.V.S. holds unexercised options in Iliad Biotechnologies. This entity provided no financial support associated with this research, did not have a role in the design of this study, and did not have any role during its execution, analyses, interpretation of the data and/or decision to submit.

Introduction

Younger adults account for a large share of SARS-CoV-2 infections in the United States, but they are less likely to become hospitalized and/or die after becoming infected [ 1 – 5 ]. Mitigating transmission among this population could have a substantial impact on the trajectory of the COVID-19 pandemic [ 2 ]; younger adults typically have more daily contacts with others [ 6 – 8 ], are less likely to practice COVID-19 mitigation behaviors [ 9 , 10 ], are more likely to have have jobs in offices or settings with more contacts with colleagues [ 11 ], and travel at higher rates [ 12 – 14 ]. Additionally, in the United States, over 19.6 million people attend institutes of higher education (IHEs; i.e., colleges, universities, trade schools, etc.) [ 15 ], where students often live in highly clustered housing (e.g. dorms), attend in-person classes and events, and gather for parties, sporting events, and other high-attendance events.

Because of this, the COVID-19 pandemic presented a particular challenge for IHEs during the Fall 2020 semester [ 16 – 21 ]. On the one hand, bringing students back for on-campus and in-person education introduced the risk that an IHE would contribute to or exacerbate large regional outbreaks [ 22 – 30 ]; on the other hand, postponing students’ return to campus may bring economic or social hardship to the communities in which the IHEs are embedded [ 31 – 34 ], since IHEs are often large sources of employment for counties across the United States. As a result, IHEs instituted a variety of “reopening” strategies during the Fall 2020 semester [ 35 – 44 ]. Among IHEs that brought students and employees back to campus—either primarily in person or in a “hybrid” manner—we see different approaches to regularly conducting (and reporting) COVID-19 diagnostic testing for students, faculty, and staff throughout the semester.

Most of these policies were designed to minimize spread within the campus population as well as between the IHE and the broader community. These policies include testing of asymptomatic students and staff, isolating infectious students, quarantining those who were potentially exposed through contact tracing, extensive cleaning, ventilation, mask requirements, daily self-reported health assessments, temperature checks, and more [ 45 , 46 ]. As with much of the COVID-19 pandemic [ 47 ], these policies were often instituted in a heterogeneous manner, with varying levels of severity [ 37 ], which makes studying their effects both important and challenging. Studying the various differences between these policies is made even more difficult because of the lack of a centralized data source and standardized reporting style. On top of that, counties with IHEs represent a wide range of demographics (age, income, race, etc.) [ 48 ], which must be accounted for when comparing any policies, since these factors have known associations with an individual’s likelihood of hospitalization or death [ 49 , 50 ].

Many IHEs developed and maintained “COVID dashboards” [ 51 ] that update the campus community about the number of COVID-19 cases reported/detected on campus and, if applicable, the number of diagnostic tests conducted through the IHE. Here, we introduce a dataset of testing and case counts from over 1,400 IHEs in the United States ( Fig 1 ), and we use this dataset to isolate and quantify the impact that various IHE-level policies may have on the surrounding communities during the Fall 2020 semester (August to December, 2020). After a matched analysis of statistically similar counties, we show that counties with IHEs that reopened for primarily in-person education had a higher number of cases and deaths than counties with IHEs that did not. Among IHEs that did allow students back on campus, we see fewer cases and deaths on average if the county contains IHEs that conduct on-campus COVID testing. We further examine this result by focusing on data from IHEs in Massachusetts, where we find that cities with IHEs that test more also have fewer average cases per capita. This pattern holds in spite of the number of cases detected among members of the campus community. These results point to a benefit of large-scale, asymptomatic testing of the campus community (students, faculty, staff, etc.), which can be especially important in regions without (or with fewer) local mitigation policies in place.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

Map of the 1,448 institutes of higher education included in the Campus COVID Dataset. The dataset includes semester-long time series for 971 institutes of higher education (see S1 Text for several examples), in addition to 477 that have cumulative data only (i.e. one sum for the total testing and/or case counts for the Fall 2020 semester). County and state boundary maps downloaded from the United States Census TIGER/Line Shapefiles [ 52 ].

https://doi.org/10.1371/journal.pdig.0000065.g001

Throughout this section, we aim to make two broad comparisons. First, we look at different approaches for how IHEs reopened for the Fall 2020 semester (early August through early December, 2020). We compare COVID-19 outcomes between counties with IHEs where students returned to fully or primarily in-person education and counties with IHEs that remained fully or primarily online . IHE reopening status is based on data from [ 37 ]. We group the categories of “fully online” and “primarily online” into “primarily online” and do the same for fully/primarily in-person; schools listed as “hybrid” are not included in this comparison but present interesting avenues for future research. Second, we quantify the benefits of IHE-affiliated testing by comparing COVID-19 outcomes between counties with IHEs that reported any campus testing and counties with IHEs that reported no campus testing . Testing data are from the Campus COVID Dataset [ 53 ] (see Data & methods section) and were collected manually through the COVID dashboards of over 1,400 IHEs. To perform the two main comparisons above, we carefully match groups of counties in order to avoid potential confounding effects of the underlying demographics of the counties’ populations.

Comparing counties with similar demographics

Constructing groups of counties..

COVID-19 has had a disproportionate impact on older populations, and we see especially high death rates in regions with more congregate senior living and long-term care facilities [ 54 , 55 ]. On the other hand, in regions with more young people (i.e., “college towns”—or, here, college counties) experienced relatively fewer hospitalizations and deaths [ 55 ]. This means that care should be taken when comparing averages between groups of counties, and prior to creating the groups, we must attempt to match the underlying demographics of the groups as much as possible.

This becomes an optimization problem: there are over 1,238 different counties with IHEs in our dataset. We want to separate them into two groups of counties, A and B , that are roughly equivalent in size and that consist of counties with as similar distributions of demographics as possible. For example, here we create a group of counties with IHEs that returned primarily in-person ( n A = 393 total) and a group of counties with IHEs that remained primarily online ( n B = 449 total) during the Fall 2020 semester. In our case, a key variable we will optimize over, x , is the percent of county population enrolled at IHEs full-time. The reason for this is intuitive: we want to compare college counties , which we define based on the fraction of IHE students among the total population. However, it is not necessarily obvious what value this threshold x should take (e.g. is a college county one where x = 0.1% of the total population is a full-time IHE student? 1.0%? 10%? etc.), so we use an optimization technique in order to select the value for x .

Following this optimization procedure, we determined the threshold to be 3.68%. That is, in order for a county to be included in the “primarily in-person” group (or, analogously, the “primarily online” group), the total number of full-time students attending “primarily in person” IHEs must exceed 3.68% of the total population. The specific value for this threshold may appear ad hoc or arbitrary, but importantly, the two groups we are left with are highly similar along our key variables of interest. See S1 Text where we describe this procedure in depth and show how similar the distributions of demographic variables between the resulting groups are (Figs B and C in S1 Text ).

In summary, we create two groups of college counties—those with IHE students who returned to the Fall 2020 semester primarily in-person and those with IHE students who remained primarily online. To do this, we had to choose what constituted a “college county”—we determined that this should be based on the percent of IHE students in a county’s total population, x . At the same time, we wanted to ensure statistical and demographic similarity between the populations in each group. In the end, we selected x = 3.68%, the value that minimized the total JSD between the distributions of interest between the two groups.

Fall 2020 reopening status: In-person vs. online education.

With this grouping, we now compare the average new cases and new deaths per 100,000 between the two groups ( Fig 2 ). By minimizing the demographic variability between the “in-person” counties and the “online” counties, we get closer to addressing the questions surrounding the effects of IHE policy on the broader community. In Fig 2a , we see that during July and August the number of new cases per 100,000 was almost identical for the in-person and online counties. By the end of August (i.e., the start of the Fall 2020 semester), we begin to see these two curves diverge; college counties with primarily in-person enrollment report more new cases per 100,000 on average for the remainder of 2020, a gap that narrows shortly after the Fall 2020 semester ends.

Here, we compare the average (a) new cases and (b) new deaths per 100,000 in counties with IHEs that were categorized as “primarily in-person” vs. “primarily online” for the Fall 2020 semester. IHEs classified with “hybrid” reopening strategy were not included in this comparison as there is a great deal of heterogeneity in what constitutes a “hybrid” reopening. IHE reopening data is from [ 37 ]. (Ribbons: 95% confidence interval).

https://doi.org/10.1371/journal.pdig.0000065.g002

We see the same trend—but lagged by about four weeks—when comparing the average new deaths per 100,000 between the two groups of counties. These analyses, even after controlling for several potentially confounding demographic variables, highlight clear differences in COVID outcomes based on IHE reopening policy. In S1 Text , we also show how the matching procedure used here excludes other potentially confounding spatial variables as well. For example, counties that were hit early and hard by COVID-19 in March and April of 2020 (e.g. counties in New York City, greater Boston area, etc.) are already not included in these averages (see a visualization of the included counties in Fig C in S1 Text ).

Quantifying the benefits of IHE-affiliated testing.

The extent to which IHEs tested their students and employees for COVID-19 varied substantially: some schools focused their limited testing resources on only testing symptomatic individuals while others developed a strict and massive testing program that required frequent (e.g. weekly) asymptomatic testing. Because of this heterogeneity, we sought the simplest distinction for comparing groups of counties; we split the “primarily in person” counties from the Fall 2020 Reopening Status section into two groups of counties: those with IHEs that reported conducting any COVID-19 tests on campus and those that reported none . Of the n = 234 “primarily in person” counties from the previous section, the Campus COVID Dataset includes data from n = 144 counties. Often, when IHEs do not administer any on-campus tests, they have a form for students and staff to self-report results from external testing providers (e.g. pharmacies, health clinics, etc.). In order to classify an IHE as “non-testing” we sought out official documentation on the IHE’s websites, though a key limitation of this approach is that an IHE could have been conducting testing without posting updates to their websites.

Counties with IHEs that reported conducting a nonzero number of tests saw, on average, fewer reported cases and deaths ( Fig 3 ). Notably, we see an increase in the number of cases per 100,000 on average in early September 2020 among counties with IHEs that do report testing (i.e., the campus testing is working as designed—detecting cases in the campus population; Fig 3a ); this same increase in reported cases does not appear among counties with IHEs that do not report testing. This suggests that the return-to-campus surges that were being detected in IHEs that report testing may have occurred but remained undetected or under-reported in counties without IHE-affiliated testing. This suggestion is in part corroborated by the increase in deaths in the middle of October among counties without IHE testing, which does not appear to follow a commensurate increase in case counts ( Fig 3b ).

As in Fig 2 , we compare the average (a) new cases and (b) new deaths per 100,000 in counties with IHEs reported conducting any COVID-19 tests vs. counties with IHEs that reported no tests. Note: if there are multiple IHEs in a single county, we sum together the total number of tests between all IHEs. (Ribbons: 95% confidence interval).

https://doi.org/10.1371/journal.pdig.0000065.g003

Importantly, while the two groups of counties used in this comparison were relatively balanced with respect to demographic variables, they are not formed based on information about differences in county-level mitigation policies that may have been active in the counties during this time period; this is in part due to relatively sparse data around county-specific policies (though there are data sets that report some county-level policies; see [ 56 ]). Perhaps more importantly, however, we do not include these data here because of the difficulty in standardizing the implementation and enforcement of specific policies (e.g. see [ 47 ] to look at the impact of heterogeneous policies across regions). Despite that, it is conceivable that IHEs that report more campus testing are also embedded in counties with more stringent mitigation policies in place; as such, even though we observe on average fewer cases and deaths in counties with IHEs that report campus testing, it would be incomplete to assume that IHE testing is the only reason for these differences. To get at addressing these points, we conducted additional analyses in S1 Text where we used state-level policy data [ 57 ] to quantify the effect of IHE testing policy while controlling for a number of county-level demographic variables as well as the number of active mitigation policies in place. Here again, we see significantly fewer deaths per 100,000 in counties with IHEs that conduct campus testing ( Table 1 ).

Regression table under a Negative Binomial model. See Table C and Fig D in S1 Text for descriptions of variables. Standard errors were adjusted for clustering at the county level. Coefficients in bold are statistically significant at the 95% confidence level.

https://doi.org/10.1371/journal.pdig.0000065.t001

Lastly, the grouping selected here (no reported testing vs. any reported testing) does not provide insights into the ideal amount of IHE testing needed to manage campus outbreaks. However, we examine this question in the following section, where we group cities in Massachusetts based on the amount of IHE testing, as opposed to simply whether they have IHE testing or not. Future work will examine whether there are optimal trade-offs between testing volume, cost of testing, levels of local transmission, and community demographics.

Case study: Higher education in Massachusetts

According to the data collected in this work, IHEs in Massachusetts administered more COVID-19 tests to students and staff, on average, than most other states. As such, the Campus COVID Dataset includes time series data for 56 IHEs during both the Fall 2020 and Spring 2021 semesters. Additionally, the Massachusetts Department of Health releases weekly data about testing and case counts at the city level (total of n = 351 cities instead of n = 15 counties) [ 59 ]. In this section, we analyze Massachusetts as an informative case study about the role that IHE-affiliated testing may play in a community’s response to COVID-19.

In February, 2021—at the start of the Spring semester—the University of Massachusetts, Amherst (UMass Amherst) experienced a large COVID-19 outbreak among the campus community. Throughout the Fall 2020 semester, UMass Amherst followed a campus testing regimen that required frequent testing of on-campus students and staff; as a result, the city of Amherst’s average number of tests per 1,000 residents was far higher than that of other cities in Massachusetts ( Fig 4c ). After the Fall 2020 semester ended, the overall testing volume in Amherst sharply declined since the number of students on campus decreases during December and January; the timing of this decline coincided with large increases in COVID-19 cases both regionally and statewide ( Fig 4b & 4c ). However, as neighboring cities to Amherst began to report a surge in cases during this period ( Fig 4b ), the city of Amherst did not report a commensurate rise in cases. It is possible that there were simply not as many cases in Amherst during December and January, but because there was such a large decrease in the amount of tests conducted during that period, it is also possible that there were some infections that remained undetected.

Top: Highlighting testing and case counts in and around Amherst, Massachusetts. (a) Map of Massachusetts cities; in this map, the city of Amherst is red and the surrounding cities are colored blue. (b) Time series of weekly new cases per 1,000 in: Amherst, the surrounding cities, and the rest of Massachusetts. (c) Time series of weekly new tests per 1,000 in: Amherst, the surrounding cities, and the rest of Massachusetts. Bottom: Comparing outcomes of cities and IHEs with more/less IHE-affiliated testing. (d) City-level average weekly new cases per 1,000, grouped by cities with IHEs that test students on average fewer than once a month, between one and three times a month, and over three times a month (Note: we sought out city-level data for COVID-19 deaths, but the state does not report these). (e) IHE-level average weekly new cases, grouped by IHEs that test students on average fewer than once a month, between one and three times a month, and over three times a month. Municipality boundary map downloaded from MassGIS (Bureau of Geographic Information) [ 58 ].

https://doi.org/10.1371/journal.pdig.0000065.g004

Either way, when students returned to campus in January, they returned to a city with a testing rate that was lower than it had been in late November, 2020. During the first few weeks of the Spring 2021 semester, UMass Amherst reported almost 1,000 new infections among students and staff, one of the largest outbreaks in the country at that time [ 60 ]. It is difficult to know whether the UMass Amherst outbreaks were primarily the result of importation from different areas following students’ return to campus or whether the returning students instead became infected following interactions with Amherst residents (or both). Regardless the source of these cases in Amherst, what happened after the February surge highlights the role that IHEs can have in local mitigation; testing volume in Amherst increased dramatically during the Spring 2021 semester, students who tested positive were strictly isolated, and on-campus restrictions of activities were put in place [ 61 ]. There indeed was a large outbreak, but without a robust on-campus testing protocol, the scale of this citywide outbreak might have grown even larger.

The example of UMass Amherst is a useful case study for highlighting a broader trend among Massachusetts cities with IHEs—a trend that largely mirrors the results in the previous section on IHE testing. In Fig 4d we show the average new cases per 1,000 for cities with IHEs that test their students an average of a) less than once per month, b) between 1–3 times per month, and c) more than three times per month; on average, cities with IHEs that conduct more tests also have fewer new cases. This pattern does not hold when only looking at on-campus cases from IHEs (as opposed to citywide cases); instead, we see that IHEs that test less also report fewer cases ( Fig 4e ). This trend may emerge because low-testing IHEs are not conducting enough tests to detect the true number of cases on campus, though proving this definitively is almost impossible without detailed contact tracing and/or retrospective antibody testing.

In the end, the resolution and completeness of the data for IHEs in Massachusetts give us an even more detailed look at the relationship between campus testing and new infections in the communities surrounding IHEs. Moving forward, improving the collection and reporting of this data nationwide will be crucial for our continued response to the COVID-19 pandemic.

The COVID-19 pandemic required governments and organizations to implement a variety of non-pharmaceutical interventions (NPIs) often without a thorough understanding of their effectiveness. Policy makers had to make difficult decisions about which policies to prioritize. While a body of literature has emerged since the beginning of the pandemic about measuring the effectiveness of NPIs [ 62 – 65 ], to date there have been no studies that attempt to measure the effectiveness of campus testing systematically nation wide. This study sheds light on this topic by directly measuring the impact of campus testing on county level COVID-19 outcomes. We collected data from 1,448 colleges and universities across the United States, recording the number of tests and cases reported during the Fall 2020 semester; by combining this data with standardized information about each school’s reopening plan, we compared differences in counties’ COVID-19 cases and deaths, while controlling for a number of demographic variables.

We used an entropy minimization approach to create two groups of counties that were as similar to demographic variables of interest (e.g., age, income, ethnicity) as possible in order to minimize confounding. The resulting groups had a similar number of counties per group, were spatially heterogeneous, and did not ultimately include counties from regions that experienced early surges in March, 2020 (e.g., counties in New York City, etc; see S1 Text ), which could have confounding effects. When looking at county COVID-19 outcomes, our results shows that COVID-19 outcomes were worse in counties with IHEs that report no testing and in counties where IHEs returned to primarily in-person instruction during the Fall 2020 semester. These findings support the CDC recommendation to implement universal entry screening before the beginning of each semester and serial screening testing when capacity is sufficient [ 66 ] and are in line with smaller scale, preliminary results from other studies [ 67 , 68 ]. While this study does not look at optimal testing strategies, it offers evidence for the protective effect of campus testing in any form and reopening status on county COVID-19 outcomes.

The COVID-19 pandemic highlighted the importance of data standardization for understanding the impact of the virus but also in to inform response, resource allocation, and policy. While much attention has been given to this topic for data reported by healthcare and public health organizations, little attention has been given for COVID-19 case and testing data reported by IHEs. A significant portion of the effort undertaken by this study was spent compiling and standardizing the data across IHEs nationwide. In the cases where IHEs did report campus testing data, the ease of access varied widely and oftentimes different metrics for cases and testing were reported out. For example, some IHEs would report only active cases, cumulative cases, or number of isolated individuals. Similarly, sometimes there would be no distinction between types of test given or temporal information on when the test was given. In their campus testing guidance [ 66 ], the CDC should also include recommendations on data standards and reporting formats.

While COVID-19 cases in the United States are lower than the peak in January 2021 and 2022, concerns remain around lingering outbreaks caused by new variants emerging, ongoing transmission in the rest of the world, vaccine hesitancy, and the possibility of waning effectiveness of the current vaccines [ 69 , 70 ]. In regions like the Mountain West and South at the time of writing, vaccination rates remain disproportionately low among younger adults and the general population when compared to nation wide averages [ 71 ]. States in these same regions are also disproportionately represented among the states with the lowest IHE testing in our data set. Heterogeneity in vaccine uptake—and policy response broadly—makes it challenging to disentangle the effectiveness of any one specific policy response. On the one hand, further data collection on policy compliance (e.g. through online or traditional survey methods, digital trace data collection, etc.) may help to elucidate specific effects of different policies. On the other hand, because most of the current study focused on a period before widespread vaccine availability (and little impact of more transmissible SARS-CoV-2 variants), the Fall 2020 semester may in fact have been an ideal time to pose the questions in this work. In sum, given the number of younger adults enrolled in IHEs, the increased mobility and international nature of this population, and the fact that this population is less likely to practice COVID-19 mitigation behaviors, campus testing represents another effective control policy that IHEs and counties should consider to continue keeping COVID-19 incidence low.

Data & methods

Data collection and sources.

County-level case data are from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University [ 72 ]. County-level population and demographic data are from the 2018 American Community Survey (ACS) [ 73 ]. Weekly data for testing and case counts in Massachusetts cities are from the Massachusetts Department of Public Health [ 59 ]. Data about IHEs—including the number of full-time students and staff, campus location, institution type, etc.—come from the Integrated Postsecondary Education Data System (IPEDS) via the National Center for Education Statistics [ 74 ].

Data about individual IHEs’ plans for returning to campus (i.e., online only, in-person, hybrid, etc.) come from the College Crisis Initiative at Davidson College [ 37 ]. This dataset classifies IHEs based on the following categories, which we use to create three broader categories (in parentheses): “Fully in person” (primarily in-person), “Fully online, at least some students allowed on campus” (primarily online), “Fully online, no students on campus” (primarily online), “Hybrid or Hyflex teaching” (hybrid), “Primarily online, some courses in person” (primarily online), “Primarily in person, some courses online” (primarily in person), “Primarily online, with delayed transition to in-person instruction” (primarily online), “Professor’s choice” (hybrid), “Simultaneous teaching” (hybrid), “Some of a variety of methods, non-specific plan” (hybrid). We did not include “hybrid” IHEs in our analyses here, but they remain an interesting avenue for future research, which we strongly encourage using the Campus COVID Dataset.

The campus COVID dataset

The Campus COVID Dataset was collected through a combination of web scraping, manual data entry, or communication with administrators at IHEs. In sum, the process involved collecting thousands of URLs of the COVID-19 dashboards (or analogous website) of each of over 4,000 IHEs, which we then used for manual data collection, inputting time series of case counts and testing volume between August 1 and December 16, 2020. The data for each IHE is stored in its own Google Sheet (indexed by a unique identifier, its ipeds_id ), the URL of which is accessible through a separate Reference sheet. For full details on the data collection process, see S1 Text .

Statistical controls for mitigation policies

While the two groups of counties—the “primarily in-person” vs. “primarily online” counties—are broadly similar across demographic categories (Fig B in S1 Text ), there could still be underlying differences between the two groups that influence their different COVID-19 outcomes. For example, this could happen if the two groups differed in the extent to which they enacted mitigation policies (i.e., if there were a common variable influencing whether a given county introduced mitigation policies as well as whether IHEs in the county remained primarily online vs. in-person during the Fall 2020 semester). There are a number of possible sources of this variability, ranging from differences in population density [ 75 ], to differences in messaging from political leaders [ 76 ]. In the model below, we include the data about voting patterns in the 2020 presidential election in order to control for potential biases arising from differences in political behavior at the county level.

To control for potential biases arising from differences in local mitigation policies, we assigned each county to an “active mitigation policies” score based on policy tracking data from the Oxford COVID-19 Government Response Tracker [ 57 ]. These are daily time series data indicating whether or not a number of different policies were active on each day for a given state. Not only does this dataset list the presence or absence of a given policy, it also includes information about the severity (e.g. restrictions on gatherings of 10 people vs. restrictions on gatherings of 100 people, or closing all non-essential workplaces vs. closing specific industries, etc.). From these indicator variables, Hale et al. (2021) define a summary “stringency index” that characterizes the daily intensity of the mitigation policies that a given region is undergoing over time. We include this “stringency index” variable in an Generalized Linear Model regression to quantify the extent to which this time series of policy measures—along with data about IHE testing and enrollment policy, demographic data about the county itself, and average temperature—predicts COVID-19-related deaths ( Table 1 ). After controlling for the variables above, we continue to see a significant negative association between the amount of IHE testing conducted in a county and COVID-19-related deaths, with a 38-day lag. Model specification and further details about the construction and interpretation of the model can be found in S1 Text .

Citation diversity statement

Recent work has quantified bias in citation practices across various scientific fields; namely, women and other minority scientists are often cited at a rate that is not proportional to their contributions to the field [ 77 – 84 ]. In this work, we aim to be proactive about the research we reference in a way that corresponds to the diversity of scholarship in public health and computational social science. To evaluate gender bias in the references used here, we obtained the gender of the first/last authors of the papers cited here through either 1) the gender pronouns used to refer to them in articles or biographies or 2) if none were available, we used a database of common name-gender combinations across a variety of languages and ethnicities. By this measure (excluding citations to datasets/organizations, citations included in this section, and self-citations to the first/last authors of this manuscript), our references contain 12% woman(first)-woman(last), 21% woman-man, 22% man-woman, 38% man-man, 0% nonbinary, 4% man solo-author, 3% woman solo-author. This method is limited in that an author’s pronouns may not be consistent across time or environment, and no database of common name-gender pairings is complete or fully accurate.

Supporting information

S1 text. supporting information..

Table A: Current status of the Campus COVID Dataset . In total, the Campus COVID Dataset includes data about more than 1,400 IHEs. To collect these data, we searched among over 2,719 IHEs; approximately 40% of these are IHEs with data that we could not find (because the IHE does not collect self-reported positive tests and/or does not conduct campus testing, etc.) or with data that we believe exists but was not being shared publicly by the IHE. There are over 971 IHEs with time series of testing and/or case counts for the Fall 2020 semester. If an IHE reported only cumulative testing or case counts, we classify it as “cumulative only”. Table B: Example template for inputting data . Each IHEs in the Campus COVID Dataset has a unique URL that leads to a dataframe with this structure. For each date that the IHE reports a number of new cases (“positive_tests” above) or new tests administered (“total_tests” above), we input that value in its corresponding row. For IHEs that report testing and case counts weekly, we insert the data at the first collection date, which makes for more accurate smoothing when performing 7-day averages. If the IHE only reports cumulative cases or tests for the Fall 2020 semester, we leave the “total_tests” and “positive_tests” columns blank and report the “cumulative_tests” and “cumulative_cases” in the “notes” column, which we extract later in the analyses. Table C: Description of variables in Table 1 . Where appropriate, we use the “per 100k” designation—the variable’s value divided by county population, multiplied by 100,000. Here “log” refers to the natural log, which we apply to variables that follow heavy-tailed distributions (e.g. income and population density). Fig A: JSD between distributions of demographic variables . As we vary the threshold for inclusion into the two groups—counties with IHEs that returned primarily in-person for Fall 2020 and counties with IHEs that remained primarily online—the Jensen-Shannon Divergence also changes. We want to select the value for this threshold based on whatever minimizes the Jensen-Shannon divergence, on average. Fig B: Comparison of county-level demographics between groups . Here, we compare the two groups—counties with IHEs that returned primarily in-person for Fall 2020 and counties with IHEs that remained primarily online—based on distributions of (a) age, (b) race, (c) income, and (d) urban-rural designation. Error bars: 95% confidence intervals. Fig C: Map of counties included in matched analysis . With the exception of California, which includes many primarily online IHEs, there are very few regions where the counties are clustered based on campus reopening strategy. County and state boundary maps downloaded from the United States Census TIGER/Line Shapefiles [ 52 ]. Fig D: Distributions of the variables used in the regression in Table 1 . Fig E: Example data: Northeastern University . Fig F: Example data: North Carolina State University . Fig G: Example data: University of California-Los Angeles . Fig H: Example data: Purdue University . Fig I: Example data: University of Miami . Fig J: Example data: Georgia Institute of Technology . Fig K: Example data: Duke University . Fig L: Example data: Ohio State University .

https://doi.org/10.1371/journal.pdig.0000065.s001

Acknowledgments

The authors thank Kaitlin O’Leary, Representative Mindy Domb, Timothy LaRock, Daniel Larremore, Maciej Kos, Jane Adams, Rylie Martin, Addie McDonough, Anne Ridenhour, Benjy Renton, and Mike Reed for helpful discussions and additions to the dataset. N.G. acknowledges LA-UR-21-25928.

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Exploring how the COVID-19 pandemic impacted teacher expectations in schools

• Published: 22 May 2024

Cite this article

• Agnes M. Flanagan   ORCID: orcid.org/0000-0002-0494-6042 1 ,
• Damien C. Cormier 1 ,
• Lia M. Daniels 1 &
• Melissa Tremblay 1  

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Expectations are beliefs that someone should or will achieve something. Expectations influence performance—positive expectations improve outcomes, whereas negative expectations worsen them. This interaction is well known in the context of education and academic performance; however, we do not know how teacher expectations changed during the COVID-19 pandemic. This study used a descriptive qualitative approach to explore the impact of the COVID-19 public health measures on expectations in schools. Specifically, to what extent did teacher expectations for students and themselves change during this unprecedented period. In addition, to what extent did teachers’ perceptions of what administrators expectated from them change during this same period. Twelve teachers were purposefully sampled across Canada and interviewed in the spring of 2021. Interviews were transcribed and analysed using qualitative content analysis. The results generally indicated that expectations for students and for teachers (i.e., themselves) changed. Students were still expected to do their best and teachers still generally had high expectations for themselves, but their expectations were tempered depending on each group’s needs. For example, if students showed significant behavioural or emotional needs, academic expectations were reduced. Administrators made some efforts to be supportive and realistic during this time; however, many participants felt it was not enough and found their administrator’s expectations were unrealistically high. Furthermore, participants described greater difficulty developing relationships with students during the pandemic, which also impacted how much teachers could expect of them. The findings contribute to the literature by providing suggestions for future research and proposing an expanded version of a conceptual model for expectations in schools. More importantly, the findings can inform school leaders on how to best support teachers, and how teachers can support and advocate for themselves, during high-stress situations or extreme circumstances such as a pandemic.

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Flanagan, A.M., Cormier, D.C., Daniels, L.M. et al. Exploring how the COVID-19 pandemic impacted teacher expectations in schools. Soc Psychol Educ (2024). https://doi.org/10.1007/s11218-024-09924-0

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Most K-12 parents say first year of pandemic had a negative effect on their children’s education

Recent  findings from the National Assessment of Educational Progress  add to mounting evidence that the transition to remote learning in the early stages of the  coronavirus pandemic  created  gaps in learning  that had a lasting impact on K-12 students in the United States. These findings are echoed in the views of many K-12 parents: About six-in-ten (61%) say the first year of the pandemic had a negative effect on their children’s education. Just 7% say it had a positive effect, while 28% say it had neither a positive nor negative effect.

Among parents who say the pandemic had a negative effect on their children’s education, more than four-in-ten (44%) say this is still the case today, while 56% say the impact was only temporary, according to a new Pew Research Center survey of U.S. parents.

The early stages of the pandemic also presented emotional challenges for children and teens . About half of parents (48%) say that the first year of the pandemic had a negative effect on their children’s emotional well-being, while 7% say it had a positive effect and 39% say the impact was neither positive nor negative. Among parents who say there was a negative impact in the first year, most (74%) say their children’s emotional well-being has gotten better, while 8% say it’s gotten worse and 18% say things have stayed about the same.

Pew Research Center conducted this analysis to study how parents of K-12 students assess the impact the COVID-19 pandemic has had on their children’s education and emotional well-being. To do this, we surveyed 3,757 U.S. parents with at least one child younger than 18 (including 3,251 who have a child in a K-12 school) from Sept. 20 to Oct. 2, 2022. Because parents with multiple children in K-12 schools may have different answers to these questions depending on the child or the school they attend, these parents were randomly assigned to think about their youngest or oldest child who is in K-12 when answering these questions. The data was weighted to account for the probability of being assigned to a child in elementary, middle or high school and is representative of all parents of students at each of these stages.

Most parents who took part are members of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This survey also included an oversample of Black, Hispanic and Asian parents from Ipsos’ KnowledgePanel, another probability-based online survey web panel recruited primarily through national, random sampling of residential addresses.

Address-based sampling ensures that nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and its methodology .

Related: Parents Differ Sharply by Party Over What Their K-12 Children Should Learn in School

Parents’ views on the effect of the first year of the pandemic on their children’s education differ significantly by race and ethnicity. While studies show that learning loss was more severe for Black and Hispanic students, White parents (66%) are more likely than Black (50%), Hispanic (55%) and Asian parents (50%) to say that the first year of the pandemic had a negative impact on their children’s education.

Income is another factor: A greater share of upper-income parents (68%) say their children’s education was negatively affected, compared with middle- and lower-income parents (63% and 54%, respectively).

The patterns are similar when it comes to the impact of the pandemic on children’s emotional well-being. White parents (53%) are more likely than Black (39%), Hispanic (41%) and Asian parents (40%) to say the first year of the pandemic had a negative effect on their children’s emotional well-being. And a higher share of upper-income parents (57%) than middle- or lower-income parents say the same (49% and 43%, respectively).

Parents’ views on the emotional impact of the first year of the pandemic also differ by the age of their children. Parents of high school and middle school students (57% and 50%, respectively) are more likely than parents of elementary school students (43%) to say the emotional effect was negative.

When asked whether the effects of the first year of the pandemic are still a factor for their children today, the results are mixed. Among parents who say the first year of the pandemic had a negative impact on their children’s education, a majority (56%) say the negative effect was only temporary. Still, 44% say it is still having an effect today.

These assessments don’t differ substantially across key demographic groups, but there are differences by the type of school children attend. Parents who were answering about a child in a public school were more likely than those answering about a child in a private school to say there is still a negative effect on their child’s education today (45% vs. 36%).

When it comes to the emotional impact of the pandemic, most parents who say there was a negative effect in the first year say things are better now (74%). But these attitudes differ by race and ethnicity.

Among parents who say the first year of the pandemic had a negative effect, White (77%) and Hispanic parents (73%) are more likely than Black parents (61%) to say their children’s emotional well-being has gotten better. Roughly four-in-ten Black parents say the negative effects of the first year of the pandemic have persisted or gotten worse. This compares with about a quarter of White and Hispanic parents. (There are too few Asian parents to analyze separately on this question.)

Upper-income parents who say the first year of the pandemic had a negative effect on their children’s emotional well-being are more likely than middle- or lower-income parents to say their children are doing better now in this regard (81% vs. 73% and 70%, respectively).

Note: Here are the questions used for this analysis, along with responses, and its methodology .

• Coronavirus (COVID-19)
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Dana Braga is a research assistant focusing on social and demographic research at Pew Research Center .

Kim Parker is director of social trends research at Pew Research Center .

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Online religious services appeal to many americans, but going in person remains more popular, about a third of u.s. workers who can work from home now do so all the time, how the pandemic has affected attendance at u.s. religious services, mental health and the pandemic: what u.s. surveys have found, most popular.

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This publication is available at https://www.gov.uk/government/publications/learning-during-the-pandemic/learning-during-the-pandemic-review-of-research-from-england

Emma Howard, Aneesa Khan and Charlotte Lockyer, from Ofqual’s Strategy, Risk, and Research Directorate.

With thanks to colleagues from

• Department for Education 
• Education Endowment Foundation 
• Education Policy Institute 
• FFT Education Datalab 
• GL Assessment 
• Institute for Fiscal Studies 
• Juniper Education 
• National Foundation for Educational Research 
• No More Marking 
• Renaissance 
• Roger Murphy
• RS Assessment from Hodder Education 
• SchoolDash 
• University College London 
• University of Exeter 

Executive summary

This review is a report in our ‘Learning During the Pandemic’ series. It comprises a review of the literature exploring what is currently known about changes in students’ learning in England over the duration of the coronavirus (COVID-19) pandemic. This supports Ofqual’s effective policy making for assessments in 2021, and years to come.

Here, we focus on three elements relating to how the pandemic has impacted learning. First, we consider teaching and learning experiences across the course of the pandemic, from March 2020 to March 2021. We also explore the scale and nature of any learning losses. Finally, we highlight the differential experiences of learning and how this may be reflected in terms of any learning losses.

This review aimed to be comprehensive of the literature related to learning during the pandemic in England. We provide a summary of the key findings here.

The pandemic has been a challenging period for teachers, schools and colleges, students and parents

While adjusting to the new way of living during the pandemic, many teachers, parents and students took on additional responsibilities that went above and beyond their usual roles and duties, and they should be recognised for their efforts.

The quality and quantity of learning students undertook declined as a result of the pandemic

Spring and summer terms 2020.

During the spring and summer 2020 terms teaching and learning was largely remote. Despite their best efforts, many schools and colleges often did not provide as effective teaching as they would have done under normal circumstances. The amount of work provided to students was in many cases much less compared with normal, and pedagogy was often less effective. Studying was most commonly independent of teachers or peers, comprising of worksheets, assignments and watching educational videos. Online lessons, which most closely resembled the usual classroom learning, were less common. With most learning being completed online, having sufficient access to electronic devices, the internet and a quiet study space at home became a critical issue. Most students had access to these resources to some degree, however there were still many who were not able to access their learning in this way.

The autumn term 2020

By the autumn term, schools and colleges reopened so that learning could once again be face-to-face. However, although this term, in general, offered better learning provision than remote learning, they were far removed from a normal year. There were many notable challenges to teaching in the 2020 autumn term. COVID-safe restrictions and social distancing in schools and colleges meant that often, individual students or student ‘bubbles’ had to self-isolate, and continue their learning remotely. This meant that teachers were often faced with the challenge of teaching in class as well as providing online learning for students who were isolating, which generally resulted in a decline in the quality of learning provision, particularly for individual students participating online. Even when students remained in the classroom, COVID-safe practices meant that the usual teaching in some subjects suffered, particularly because teacher-student and peer interactivity, sharing of equipment and practical tasks were reduced or ceased completely. As such, the autumn term was not felt by many to have been a successful period of learning recovery.

The spring term 2021

At the start of the 2021 spring term, England went back into a national lockdown, and learning was predominantly remote again. At this stage, we know less about the students’ learning in the 2021 spring term, but this period of remote learning is thought to have been more successful than previous periods, as teachers were better equipped to deliver remote teaching and access to digital resources for students who did not have them during the first lockdown was also somewhat improved. By March 2021, most students could return to school. While COVID-safe and social distancing restrictions are still in place in schools and colleges, the quality of learning experienced by students is still thought to be far less than it was before the pandemic.

Most students are reported to have some learning losses, while some have severe learning losses and some have learning gains

For most students, their learning has suffered to at least some degree. Teacher estimations indicate that while a small proportion of students made learning gains, most students have learning losses, and sometimes this was severe. The literature indicates that the extended periods of remote learning are likely to account for most of the learning loss.

Learning losses appear to be most prevalent in maths and literacy

Ofsted reports from the autumn terms indicate that students were most behind in maths and literacy skills. Practical skills were also identified as being behind, which was most problematic for qualifications with large practical components, such as some apprenticeships, and trades and beauty qualifications.

Experiences of teaching and learning during the pandemic were diverse, but disadvantage and deprivation appear to be most associated with less effective learning and overall learning losses

In this review we note the differential experiences of learning by: age or stage of education, deprivation and disadvantage, attending state or independent schools and colleges, lower attaining students, students with special education needs or disabilities (SEND), gender, ethnicity, region, and students in other circumstances (students living in single-parent households or with multiple siblings, vulnerable children and children of keyworkers).

In general, disadvantage and deprivation appear to be most associated with less effective learning. Teaching and learning for primary-aged students also appear to have been negatively impacted. Teachers’ estimates of how much learning these students have lost reflect these findings, and further raise concerns about the impact of the pandemic on these students’ future learning and occupational opportunities.

Learning experiences were diverse: there were differential experiences both between and within groups

While learning was broadly researched across different groups of students or students from different backgrounds, it is important to keep sight of the fact that the research and data analyses often minimise the role of individual experience. In reality, experiences of teaching and learning during the pandemic were diverse. Here, we briefly note that there are complex interactions between macro- and micro-level influences that give rise to complex and unique variations in experience (and relative impacts) for individuals between and within groups. Examples of factors that contribute to the diversity in experience are presented in the schematic summarising the section on ‘The impact the pandemic has had on learning’ – see Figure 1.

There are important implications for learning recovery

Given the complexity and uniqueness of learning experiences and learning losses, a one-size solution for learning recovery is unlikely to be equally beneficial to all. This has important implications for learning recovery programmes within schools and colleges, and also for wider decision-making and policy implementation in the field of educational assessment.

There is much about learning during the pandemic that remains unknown and under researched

Overall, it is evident that this research field has produced a considerable amount of research in a short period of time to build a foundation of knowledge around the impact of the pandemic on learning in England. However, it remains that there is much that is still unknown. For instance, there is little information regarding the impact of the pandemic for specific subjects, qualifications (particularly for vocational and technical qualifications), and year groups for which the timing of the pandemic has been particularly disruptive to their high-stakes assessments (such as those in years 10 to 13). Further evaluation is required in these under-researched areas to build a more complete picture of learning experiences and any learning losses.

Introduction

This review is a report in our ‘Learning During the Pandemic’ series. In particular, it should be read alongside two specialist reports in this series: ‘Quantifying lost time (report 2)’, and ‘Quantifying lost learning (report 3)’. This series of reports aimed to, as fully as possible, understand the impact of the pandemic on learning in the run up to high-stakes assessments. This review in particular focuses on the literature around students’ learning, and learning losses in England over the course of the coronavirus (COVID-19) pandemic. Our work monitoring and evaluating the emerging research around learning during the pandemic supports Ofqual’s effective policy-making in the run up to assessments in 2021 and beyond.

The current review

In preparing this report, we reviewed over 200 sources that discuss teaching, learning and students’ experiences over the course of the pandemic: from school closures in March 2020 until March 2021. Although this report was not based on a ‘systematic review’ of the literature, it intends to be comprehensive, in that we reviewed all available literature that was relevant to the impact of the pandemic on learning. We provide an evaluation of the literature sources in the section titled ‘Discussion’.

This review focuses on teaching and learning of students undertaking the assessments and qualifications that Ofqual regulates. As such, the focus is primarily on teaching and learning in England, from primary-aged children to school or college leavers, typically aged 19. It should be noted, however, that there is more literature within some contexts than others. For instance, the literature is more heavily focused on primary and secondary students’ experiences. Specific subjects or qualifications tended not to be the focus of research, however, where this is apparent in the findings, we include these in the review. School closures on 20 March 2020 meant that much teaching and learning had to be undertaken remotely. There is widespread concern regarding the degree to which students’ learning has suffered since the start of the pandemic, and the amount of learning they have lost. Here we explore several issues related to learning loss, which we discuss across three main sections:

• the impact the pandemic has had on learning: within this section we look at the literature around school and college, and home provision for learning, as well as student engagement
• the scale and nature of learning loss: within this section we explore accounts about how much learning has been lost, what aspects of learning have suffered the most, and what the recovery of learning loss looks like thus far
• the differential experiences of learning loss: within this section we address how the experiences of learning were diverse, both between and within groups. We provide an overarching summary of the scale of learning loss, and possible contributors to this, across different contexts, such as age, disadvantage and ethnicity, to name a few

The impact the pandemic has had on learning

The start of the pandemic in March 2020 changed how teaching and learning were undertaken for most learners. Schools and colleges went through periods of being closed to most students and learning were often undertaken remotely – although vulnerable children and children of keyworkers could still attend school during these periods. When schools and colleges re-opened for in-school teaching, the learning environment was far removed from what it was before the pandemic. Consistent with changes to social-distancing measures, school and college closures, and the degree to which students were able to return to school or college, the nature of teaching and learning and the relative impacts between March 2020 and March 2021 were diverse. It is important to note that much of the literature exploring the impacts of the pandemic on learning focuses on the immediate impact, typically between March and July 2020. Currently, at the time of writing, there is limited insight as to the nature and impacts of teaching and learning beyond autumn 2020.

We present the findings of the literature chronologically, firstly addressing findings related to the initial school closures in March 2020 through to the end of the 2020 summer term in July, and secondly addressing teaching and learning during the 2020 autumn and 2021 spring terms.

Remote teaching and learning in the 2020 spring and summer terms

The literature outlines several key aspects of teaching and learning that acted as barriers to learning or were protective against the negative impact of the pandemic. Here we categorise them into factors related to:

• school and college provision
• home learning provision
• student intrinsic factors

These dimensions will be explored in turn. Where this is discussed in the literature, the differential impacts on different groups of students, or across different contexts, are introduced. Also see the discussion section for an overview of the differential experiences of learning loss during the pandemic.

School and college provision

School and college closures from 20 March 2020 until the end of the summer term meant that most [footnote 1] teaching and learning had to be undertaken remotely. There is a large amount of research focused on the initial phase of the pandemic, between March and July 2020. Here we separate the findings and present them under five key areas:

• The type and amount of remote learning provision.
• The quality of the remote learning provision.
• Teacher engagement.
• In-school provision for children of keyworkers and vulnerable students during the first lockdown.
• The return to school for some students in June 2020.

The type and amount of remote learning provision

Overall, students were spending much less time on learning during the 2020 spring and summer terms than they would have done pre-pandemic. This issue is explored comprehensively in Report 2 from our ‘Learning During the Pandemic’ series, but to summarise, before the pandemic, students would spend around five to six hours learning per day in school, as well as taking additional time for homework. This contrasts with accounts from parents, teachers and students about the time spent on remote learning during the spring and summer terms, which estimate that students were spending, on average, around 2.5 to 4.5 hours on learning per day (Andrew, Cattan, Costa-Dias, Farquharson, Kraftman, Krutikova… & Sevilla, 2020a; Cattan, Farquharson, Krutikova, Phimister, Salisbury, and Sevilla, 2020; Green, 2020; Pensiero, Kelly & Bokhove, 2020; Williams, Mayhew, Lagou, & Welsby, 2020). This section looks into the learning activities students were undertaking during this time.

The types of learning that took place while schools and colleges were closed can be categorised into ‘online’ and ‘offline’ learning. Online learning refers to the use of real-time internet-facilitated resources, whereby students engaged in a live ‘online class’. Online learning was typically delivered via online-conferencing software, and could involve text chats and verbal interactivity with teachers and peers. Offline learning refers to learning that is undertaken outside of an ‘online class’ and independent of a teacher. This typically involved completing worksheets, undertaking project work or assignments or watching educational videos.

Offline learning was much more prevalent than online learning throughout the period of remote learning, with around 90% of parents of both primary and secondary children reporting that their child received offline learning resources. Provision tended to be more limited for online learning in schools, although colleges appear to have made more use of online learning platforms (Association of Colleges, 2020). Parents indicated that schools were more likely to provide online learning to secondary students than primary students (59% compared with 44%, respectively; Cattan et al., 2020; Williams et al., 2020). The Association of Colleges reports that online learning was adopted for the majority of subjects in 70% of colleges surveyed, but were condensed with 35% receiving a significantly reduced timetable (Association of Colleges, 2020).

For those who did receive online lessons across the school week, this accounted for a small proportion of students’ remote learning time. Parent reports of their child’s time use between April and June 2020 indicates that primary and secondary students spent, on average, between 1 and 2 hours on online learning per day, with secondary students receiving slightly more online learning than primary students (2.14 hours, compared with 1.48 hours, respectively; Lucas, Nelson and Sims, 2020; also see: Andrew et al., 2020a; Bayrakdar & Guveli, 2020; Pensiero et al., 2020).

However, using averages to understand students’ remote learning provision can mask the experiences of many students. Looking further at the data, it is clear that some schools and colleges delivered far less provision for online learning than others. In April, shortly after schools and colleges closed and teaching and learning was remote, online provision was found to be delivered every day to around a third of students (Pensiero et al., 2020; Benzeval, Borkowska, Burton, Crossley, Fumagalli, Jäckle, … & Read, 2020a). At the same time, 60% of parents of primary students reported that their child did not have any online lessons. For secondary students this was just over 50%, and for post-secondary students this was 39% (Eivers, Worth & Ghosh, 2020; Pallan, Adab, Clarke, Duff, Frew … & Murphy, 2021).

In May 2020, online provision had increased, where the number of students not undertaking online classes had reduced to 30% of primary, and 28% of secondary students (Andrew et al., 2020a). In contrast to this, around 20% of secondary students reportedly spent more than 4 hours a day participating in online learning in May 2020. For primary students this was around 8% (Andrews et al., 2020a). Moreover, online learning provision was not available to all students every day, with only 7% of students receiving at least one online teaching lesson every day.

At the start of the lockdown in March 2020, while almost all students in years 10 and 12 were provided with school work, almost half of parents whose children who were in years 11 (42%) and 13 (49%) reported that their school did not provide them with any remote learning (Eivers et al., 2020). The cancellation of exams probably had a major role in this decision. By the time of the school closures, students had typically covered all of the course content, and would usually be in a period of revision in preparation for their exams. Without the exams to revise for, many schools and colleges likely prioritised learning for other year groups over the year 11 and 13s. It is not clear from the literature whether learning provision from the school or college picked up for year 11 and 13 students as remote learning continued through the summer term. This is unlikely to have happened, however, as these students would typically be on ‘revision leave’ from May onwards, to continue their learning independently.

Students spent more time undertaking offline work than online work during the first lockdown. On average, parents reported that primary and secondary students spent between 1 and 2 hours on offline learning per day. However, there was also large variation in time spent on offline work (Andrew et al., 2020a). Around 15% of primary students, and 25% of secondary students, reportedly did not undertake any offline learning (Green, 2020). Around 60% of primary, and 30% of secondary, students reportedly spent up to 2 hours on offline learning. At the other end of the range of experience, 25% of secondary students spent between 2 and 4 hours on offline learning and 17% spent more than 4 hours a day on offline learning.

The rapidity with which remote learning resources were implemented in light of the pandemic is striking. Schools and colleges, and individual teachers, constructed their own methods of remote teaching. This meant that there was diversity in the approaches teachers took and the resources that were available to facilitate this. Parental reports indicate differences in the provision of remote learning across different contexts (Andrews et al., 2020a; Andrews, Cattan, Costa-Dias, Farquharson, Kraftman, Krutikova, … & Sevilla, 2020b). The most deprived students and students in state schools and colleges were less likely to experience online learning and have interactions with teachers, students and peers than less deprived students and students in independent schools. Independent schools were also nearly twice as likely to provide full school days than state schools (Eyles & Elliot-Major, 2021; Cullinane & Montacute, 2020). In place of online learning, paper-based resources were more common in schools with the most deprived students. This was largely driven by differences in digital resources and devices, but has further implications for the quality of students’ learning, as will be discussed in the section, ‘Quality of the remote learning provision’.

There were also regional divides, whereby 12.5% of students in London received daily online teaching, compared with 5% of students in the East Midlands. Also, while the average proportion of students who received four or more pieces of offline work per day was 20%, in the south-east this was 28% and in the north-east this was only 9%.

While there is less research exploring the impact of the pandemic for learners outside of schools and colleges, there is some that highlights that there are also contexts for which learning provision has been more limited or removed entirely. This is particularly the case for college students on practical courses and apprentices, who have been severely impacted by the pandemic (Association of Colleges, 2020; Ofsted, 2020a). During April 2020, a survey of employers (Doherty & Cullinane, 2020) reported that 36% of apprentices were furloughed, 8% were made redundant, and 17% had their off-the-job learning suspended. Apprentices experienced further challenges during the first lockdown, with 37% of surveyed employers reporting that a lack of equipment at home, or unsuitability of the work, meant that some apprentices could not work from home. A further 14% of employers reported that some apprentices did not have access to a digital device or the internet to continue their apprenticeship from home.

Quality of the remote learning provision

There was no prior requirement for schools and colleges across England to engage in remote teaching and learning before the pandemic. As such, investment in remote education solutions was lacking at the time of the initial school closures in March 2020. The lack of infrastructure to support online teaching resulted in many teachers feeling initially unprepared to deliver teaching remotely (Educate, 2020; Ofsted, 2020a).

Interviews with teachers carried out by Educate explored the change to teaching and learning across the period of initial school closures in the 2020 spring and summer terms. In total, 46 interviews were carried out between July and September 2020, where teachers were asked to reflect back on their teaching practices since the initial lockdown in March 2020. Overall, it was evident that to cope with the severe changes to the way teaching was delivered, most schools and colleges adopted Remote Emergency Teaching practices. Senior leaders report that this largely comprised of using materials provided by external providers (92%) and using externally provided pre-recorded video lessons (90%). Where schools and colleges did provide their own resources, they were typically worksheets (80%; Lucas et al., 2020). As previously discussed, fewer senior leaders reported that their teachers delivered active teaching provision such as live remote lessons (14%) or online discussions (37%, Lucas et al., 2020).

Teachers also reported that the move to remote teaching was not undertaken with ease. Out of 46 interviews Educate (2020) undertook, only 3 schools (1 state school and 2 independent schools) reported that the transition to remote teaching was seamless. Most of the teachers who took part in the interviews further indicated dissatisfaction with the teaching that they had delivered in the spring term, reporting that their approaches to remote teaching needed to be reviewed. This was particularly driven by views around the lack of efficiency, interactivity and engagement between students and teachers.

Any type of learning provision is important to support students’ learning during school closures, but it is important to consider that some methods of teaching may be more effective than others. Moreover, the quality of the teaching within those methods also has implications for effective learning. As we have seen, offline resources were the most common learning provision during the first lockdown in March 2020 (Andrew et al., 2020a; Green, 2020). Offline resources can be beneficial as they enable students to make better use of their time spent on their education, where students can move through the work at their own pace (Müller & Goldenberg, 2021). However, offline resources are unlikely to sufficiently substitute for the high-quality professional teaching delivered by teachers because they are likely to lack crucial elements of effective pedagogy. Effective pedagogy includes clear explanations about learning content, scaffolding to support learning and adapt to learning needs, and appropriate feedback that promotes development (Andrew et al. 2020b, Education Endowment Foundation, 2020a; Müller & Goldenberg, 2021). Effective pedagogy is particularly important for supporting younger students’ learning, who are less likely to be able to effectively undertake independent learning in the way the older students can (Müller & Goldenberg, 2021).

Online lessons are the closest substitute to in-class learning that students will have experienced pre-pandemic. They are argued to be the most effective remote learning activity due to the presence of the teacher, which facilitates the aspects of effective pedagogy outlined above (Andrew et al. 2020b). The Education Endowment Foundation (2020a) further reported that pre-recorded material could be used by teachers, as what matters most is explanations building on pupils’ prior learning and how their understanding is later assessed. It is not clear from the research how much online teaching was delivered with good pedagogy during the 2020 spring and summer terms. However, given that students generally reported that they would have liked more feedback and engagement with teachers and peers (Child Poverty Action Group, 2020), it is likely that the online teaching was below the quality that students receive during normal periods of learning, pre-pandemic.

It is worth noting, that while the time students spent on learning did not change over the period of the initial lockdown (see Report 2 in our ‘Learning During the Pandemic’ series), the quality of remote learning resources improved. As the school closures were extended into the summer term, schools and colleges reduced their reliance on offline resources, and started to incorporate more pre-recorded and live online lessons into their teaching (Cattan et al., 2020; Edurio, 2020). This is shown in the increase of the proportion of parents reporting that their students were provided with online learning between April and June 2020, which rose from 44% to 51% for primary students, and 59% to 65% for secondary students.

In general, after the initial switch to remote learning, teachers reported feeling able to deliver remote learning well (Lucas et al., 2020), indicating they were happy with the way in which their school or college reacted and adapted to the new way of teaching. Those who felt this way were largely driven by feeling well-supported by their senior leaders. School leaders tended to adopt a flexible approach to deliver remote teaching, and considered relevant research and consultations with staff, students and parents. Some schools and colleges trained staff on how to refine their lesson delivery and teach effectively remotely (Ofsted, 2020b). With teaching mainly taking online forms, confidence in using digital resources also played a large part in teachers feeling able to deliver remote learning (Lucas et al., 2020). However, confidence in digital skills was not universally felt. There were further barriers when it came to less experienced teachers moving to a remote curriculum at speed, such as ensuring staff having digital skills to teach content remotely (Ofsted, 2020a). Teachers were often using online resources for delivering remote lessons, assessing students, providing feedback and organising collaboration spaces for students to work together (Edurio, 2020). Findings across two surveys (undertaken in May, and June to July) exploring teachers’ views about technological barriers to effective teaching indicate that, while 30% of teachers reported that they did not need any further training to support their teaching, a quarter said they would need training to use new online teaching tools effectively (Edurio, 2020; Menzies, 2020). The areas of training teachers reported would be most valuable to their new way of remote teaching was for using technology in general (18%), organising digital collaboration spaces for students (17%), and delivering online lessons (15%, Edurio, 2020).

The change to remote teaching had further impacts on the content that was delivered to students. Teachers adapted their teaching in a way that met the needs of their students, but sometimes this meant diverting away from covering the curriculum. Research shows that 80% of primary and secondary teachers (out of ~1,800 surveyed) reported that, up to May 2020, all or certain areas of the curriculum were receiving less attention than in a typical learning year (Lucas et al., 2020). Schools and colleges serving the most deprived communities were reported as struggling the most to cover the curriculum during lockdown (Lucas et al., 2020), and curriculum alignment was particularly difficult to achieve in primary schools. Around 83% of primary teachers reported struggling to cover the curriculum sufficiently, where 61% of secondary teachers reported that this was the case (Lucas et al., 2020).

There were two main contributors to reduced curriculum coverage: challenges related to student engagement, and challenges related to access to teaching provision. Primary teachers report prioritising learning activities that were engaging and motivating for students (Lucas, et al., 2020; Moss, Bradbury, Duncan, Harmey, and Levy, 2020a). The importance of parental engagement and support for primary students’ learning was also well understood by primary teachers, and teachers often adapted learning resources so they could be fun and accessible for the whole family (Moss et al. 2020a; Moss, Bradbury, Duncan, Harmey and Levy, 2020b). In addition, in primary schools, the focus in the spring and summer 2020 terms was on maintaining prior learning over learning new material (Lucas et al., 2020). Primary school leaders mentioned that the lack of activity-based teaching and learning often resulted in younger students not being able to develop the conceptual understanding for new materials that would be achieved in the classroom. Therefore, where new curriculum content was covered in their remote learning, younger children were struggling to embed it.

Teachers further adapted their teaching to ensure that primary students had the facilities to engage in learning activities. For many serving deprived communities, this meant prioritising ensuring that students without access to devices had learning opportunities even if they could not access online resources (63%; Moss et al., 2020a, Moss et al., 2020b). A quarter of primary teachers (responding to the survey) reported that they hand delivered hard copies of learning resources to students’ homes (Moss et al., 2020a).

Even though two-thirds of secondary teachers reported that all or certain areas of the curriculum were receiving less attention than in a normal year (Lucas, et al., 2020), curriculum coverage in secondary schools was less of a concern than in primary schools. Although there is less research that addresses this directly, secondary students are less likely to share the challenges to learning that younger students have. Older children tend to be better able to undertake independent learning than younger children and are more likely to have access to (and be able to use unsupervised) digital devices with which to undertake remote learning. Although there were fewer barriers in teaching, learning and covering the curriculum for secondary students, compared with primary students, secondary students’ learning of the curriculum was disrupted nonetheless, and many experienced, and continue to experience, learning loss.

We cover the scale and nature of learning loss experienced by students further in the section, ‘The scale and nature of learning loss’, but it is clear that student engagement with their learning and motivation also influence this (see the section, ‘Student intrinsic factors’). Teaching of some parts of the curriculum was also understandably hindered by lockdown restrictions. For instance, some secondary leaders reported that because students were unable to access equipment, learning in more practical subjects was disrupted, for instance in PE, music, science, and design and technology (Ofsted 2020b; Ofsted 2020c).

Teacher engagement

Teacher engagement is a fundamental aspect of effective teaching and learning. The circumstances of the lockdown in the 2020 spring and summer terms meant schools and colleges were using, or sometimes inventing, new remote ways in which to teach, engage, motivate and monitor the well-being of their students. With schools and colleges being closed, there was a shift away from teachers being in close daily contact with their students, where students could ask questions, work with peers and informally chat with teachers. Overall, teachers and students report that teachers not being able to wander around the classroom and directly engage with students was a barrier to effective educational communication (Ofsted, 2021). To overcome the reduced nature in which teachers and students could engage with each other, many schools and colleges delivered alternative means to keep in touch with students and continue effective communication about their learning. For instance, teachers report using chatroom discussions, 1-to-1 calls with parents and students, interactive questioning during live lessons, adaptive learning software, and digital exercise books with commenting, editing and feedback functionality (Ofsted, 2021). However, clarity, feedback and peer and teacher discussions were often reduced compared to when students were in school, or in some cases, were completely absent.

In May 2020, teachers reported that they were in regular contact with, on average, 60% of their pupils (Lucas et al., 2020). This comprised of teachers delivering online live lessons, setting work, checking in with students and providing feedback. In general, the majority of students (78%) reported they were happy with the way their school supported them in the period immediately following school closures (Yeeles, Baars, Mulcahy, Shield & Mountford-Zimdars, 2020). However, in a separate survey, students reported that they wished they had received more feedback from teachers on their work (Child Poverty Action Group, 2020).

Teacher feedback can be an important teaching tool that helps students adjust their skills and learning strategies. Students reported that during the initial school closures, teacher feedback helped them feel more motivated to continue with learning activities (Child Poverty Action Group, 2020). In May 2020, 60% of parents of primary school children and 40% of parents of secondary school children reported that their child did not receive personalised feedback from their teacher(s) during the lockdown (Educate, 2020). This may at least in part be due to secondary students having several teachers across their subjects, and therefore having more opportunities for contact and feedback. Of those students receiving homework and submitting it back to school, 65% report that at least half of the homework was checked by teachers. This proportion is higher among post-16 students, though (82%, Benzeval et al., 2020a). A few school leaders acknowledged the importance of immediacy of feedback to students about their work (Ofsted, 2021), however students separately reported that in general, they were often frustrated about the length of time they had to wait to receive comments from teachers on work they had submitted (Child Poverty Action Group, 2020). When considering the workload implications of rapid feedback, this is likely difficult to deliver. Nevertheless, research shows that in general, feedback for a large proportion of students’ schoolwork was not delivered at all (Child Poverty Action Group, 2020; Educate, 2020; Green, 2020).

Because of the resource requirements and workload implications of maintaining the teaching and learning dialogue between teachers and students, there are variations in the degree to which teacher engagement was experienced by different groups of students. Again, much of the variation seen around this is associated with measures of deprivation, with the most deprived students experiencing less teacher feedback and engagement.

Teachers in the most deprived schools report being in contact with around half of their students at the beginning of school closures, which is a significantly smaller proportion than teachers in the least deprived schools (67%) (Lucas et al., 2020). Moreover, children with limited or no access to electronic devices were less likely to be able to submit their work to have it checked by their teacher and receive feedback (Andrew et al., 2020b; Green, 2020). Students attending a state school (53%) and students eligible for free school meals (40%) were less likely to have work checked by a teacher, compared with students attending independent schools (76%), or those not eligible for free school meals (56%, Green, 2020). With regards to giving feedback, special education providers reported that they personalised learning resources for the majority of their pupils (66%) and gave personalised feedback to 73% of their pupils (Skipp, Hopwood & Webster, 2020).

The amount of feedback and contact time with students differed depending on the phase of education, with more primary school teachers (62%) reporting they were in contact with their students than secondary school teachers (50%). However, the type of contact with pupils was also different across these phases of education. Primary school teachers focused more on checking in with students and parents rather than teaching and learning than secondary school teachers. Secondary school teachers also typically teach more students than primary teachers do, across different classes and year groups. This inevitably reduces the amount of time that can be dedicated to any one student (Lucas et al., 2020).

In general, where learning was remote during the 2020 spring and summer terms, individual students experienced a reduction in teacher engagement compared with when they were at school, pre-pandemic. However, it is important to reflect that teachers were faced with new and never-seen-before challenges, and were navigating the new means of teaching as best as they could. Setting-up and adjusting to new ways of working, ensuring students had sufficient resources to learn and adapting teaching to ensure that students without sufficient resources were still able to undertake learning activities, went beyond teachers’ normal duties. Adapting to the new means of teaching resulted in increases in teachers’ workload, with teachers being pushed to the limit of what they could deliver (Ofsted, 2020b; Ofsted, 2020c).

In-school provision for children of keyworkers and vulnerable students during the first lockdown

Although schools and colleges were closed to most students during the lockdown, they remained open for the children of keyworkers, and vulnerable children, including: children of social workers, health professionals and teachers; looked-after children; and those with an education, health and care (EHC) plan. Individual schools and colleges were free to decide the nature of provision they offered to children of critical workers and vulnerable pupils during lockdown. Survey data suggests that while most schools were teaching the curriculum to the students in school, there was still a meaningful variation in educational experiences between schools. A survey carried out with almost 19,000 teachers in April 2020 asked teachers how many hours per day learners were being taught in school. While half stated they were offering 3 or more hours of teaching per day, almost one quarter answered ‘none – we’re offering childcare’ (Stewart, 2020, pg.1).

Similar variation was apparent the following month, where almost three-quarters of senior leaders indicated that the focus of in-school provision was providing a place where students were safe and cared for, rather than providing curriculum-based teaching. Nonetheless, most schools still taught the curriculum, particularly at secondary level, and the authors concluded that students undertaking in-school learning experienced the same, if not better, learning provision than those being taught remotely. This was because there were more opportunities for teacher support and supervision (Julius and Sims, 2020). Just under half of primary and secondary school leaders reported they were teaching students based in school the same curriculum content that was being sent to children who were learning remotely. A further 41% of secondary leaders reported that children were being provided time or resources to work on curriculum content with limited teaching input. This was 14% in primary schools. At primary level the picture is more mixed. While most leaders report covering aspects of the curriculum as their main approach, just under a third reported that the main approach of in-school provision was extra-curricular activities, such as arts and crafts. This suggests that a significant minority of vulnerable pupils and the children of keyworkers in primary schools may have covered less curriculum content than their peers who were based at home.

As with much of the literature on online provision, there is evidence that the nature of in-school provision may vary considerably depending on the deprivation of the school community. While 58% of senior leaders in schools serving the most affluent communities report their main approach is teaching the same curriculum content as is sent to other students, this falls to 35% of senior leaders in the most deprived communities. Similarly, leaders in the most deprived schools were twice as likely to report that their main approach was to provide extra-curricular activities than those in the least deprived schools. There were also significant differences across regions with leaders in the north-west twice as likely to report providing extra-curricular activities for pupils in-school compared to those in the south-west, the south-east and London (Julius and Sims, 2020).

Regarding provision in special schools, anecdotally, those children who had remained in education throughout were reported to have benefited from the experience and often flourished with smaller class sizes and more support. Some others enjoyed being at home and also made good progress (Skipp et al., 2020).

The return to school for some students in June 2020

In June and July of 2020, schools began to reopen for key year groups. Report 2 from our ‘Learning During the Pandemic’ series covers this in depth, but to summarise, from 1 June, primary schools were allowed to open for nursery children, as well as for reception, year 1 and year 6 students. From 15 June, secondary schools, sixth forms and further education colleges were allowed to open for years 10 and 12, to support students working towards their GCSEs and A levels the following year. However, guidance largely suggested that schools and colleges primarily educated these year groups remotely, and to keep in-school lessons to a minimum. Attendance in school was also not compulsory for students, and while 89% of primary and 74% of secondary schools did reopen, uptake of this provision was limited, with attendance at 27% for primary, and 5% for secondary school in July. As such, remote learning continued to be the predominant means of learning and 95% of secondary and 82% of primary teachers reported that they continued to provide remote learning (Sharp, Nelson, Lucas, Julius, McCrone & Sims, 2020).

For those students who did return to school, social distancing and other ‘COVID-safe’ practices appear to have negatively impacted the quality of in-school provision (Lucas et al., 2020). Despite being happy with the way in which their school adapted to remote learning early in the March lockdown, by July 2020, after a long period of teaching and learning under COVID-19 restrictions, the majority of teachers felt they were not able to teach to their usual standard (74%). The challenge of teaching under conditions of social distancing was the main reason for this (Sharp et al., 2020). Social distancing prevented teachers from moving around the classroom to support and interact with pupils. Practical and group work was also made more difficult to coordinate safely, and students were prevented from sharing equipment. In the same study, half of senior leaders reported using teaching assistants to lead classes to help manage the supervision of smaller ‘bubbles’, and almost half of teachers said they were mainly teaching pupils they did not usually teach (Sharp et al., 2020).

When returning year groups went back to school last summer, some schools focused on well-being and in-class teaching only for the 3 core subjects: maths, English and science (International Literacy Centre, 2020a, 2020b; Sharp et al., 2020). For instance, Teacher Tapp (2020a) found that 1 in 3 secondary schools delivered face-to-face teaching in just the 3 core subjects daily. This is not to say, however, that these schools did not continue remote learning for the wider diet of subjects. Independent and better-resourced primary schools were more likely to be teaching the breadth of the curriculum as normal, whereas state schools were most likely to deliver an adapted curriculum (Teacher Tapp, 2020a).

Although the quality of remote learning provision improved as remote learning continued, compared with that in the initial weeks of lockdown (Cattan et al., 2020; Edurio, 2020), evidence suggests that the quality of online provision for students continuing to learn remotely may have dipped as schools re-opened for some year groups. Teachers’ focus was increasingly split between those learning at home and those learning in school, leaving students based at home with less support and teacher engagement than they had been used to (Sharp et al., 2020; Teacher Tapp; June 2020). During this time, teachers report most commonly asking students to access content from external sources, complete a worksheet or read a book (Sharp et al., 2020), and therefore in general included fewer active and interactive learning opportunities.

Home learning provision

While schools and colleges were closed, the home environment had a more crucial role in facilitating students’ learning than before. This section looks at the impact of several important home provisions and their role in supporting students’ learning. In particular, we address parental support, other family factors, home learning resources and home learning environments. Although the literature supporting this section largely refers to findings from the initial period of school closures during the 2020 spring and summer terms, it is likely that many of these findings can be generalised to account for experiences beyond that period. For instance, during further school closures in the 2021 spring term and when individual students or student bubbles had to self-isolate and continue learning from home. This is helpful as, as we discuss in the section, ‘Teaching and learning in the 2020 autumn and 2021 spring terms ‘, there is little research that tells us about home learning provision in the autumn 2020 and spring 2021 terms.

Parental support

With the closure of schools and colleges, parents took on more responsibility to support their children’s learning at home. Just over half of teachers report that parents were engaged with their children’s home learning (Lucas et al., 2020; Villasden, Conti & Fitzsimons, 2020). In total, 58% of parents reported that they were home-schooling their children during the initial lockdown. Parents typically took part in more home-schooling for primary compared with secondary-aged children (Andrew et al., 2020a; Lucas et al., 2020; Pensiero et al., 2020; Villasden et al., 2020). They spent just under 1 hour supporting secondary children with their learning per day, compared with 2 hours supporting primary-aged children (Pensiero et al., 2020). Teachers further reported that 48% of parents of secondary-aged children were engaged with their child’s learning, compared to 56% of parents with primary-aged children.

These differences in parental engagement and support likely reflect the type of assistance that is required by children across these ages, with the need to supervise children in their learning becoming less as they grow older. The learning content of secondary-aged children also becomes more difficult, and those in key stage 4 were most likely to report that they were unable to get sufficient support with their work from their parents: a quarter of students at this education level reported that their parents could not help them (Impact Ed 2020).

Around half of parents reported that they found it either ‘quite’ or ‘very’ difficult to help their children with their learning (Andrew et al., 2020a, 2020c), and only half felt confident in their abilities to home-school (Williams et al., 2020). Home-schooling was clearly a challenging task for both parents and students. Responses to a parent survey indicate that 63% of households said either the parent, the child, or both, had ended up in tears over remote learning (Education Endowment Foundation, 2020b). Parents reported that balancing homeworking with home-schooling was challenging and that limited time for parental support was a driving factor for why parents reported their children were struggling. This was particularly the case for parents of younger children (Child Poverty Action Group, 2020; Williams et al., 2020). Parents also felt they needed better support from schools and colleges to undertake the home-schooling task, reporting that they needed clearer instructions on how to use the resources provided to them as well as specific support around how to teach certain topics (Child Poverty Action Group, 2020).

Over the course of the 2020 spring and summer terms, engagement of parents of both primary and secondary-aged children reduced, from 55% in May to 44% in July. By July, in many occupations, employees were allowed to return to work. This is likely to have further reduced parents’ capacity to support their children’s learning at home. This effect is more greatly observed for parents of primary children, which again, is likely a reflection of how the supervision required to maintain home-schooling for younger children was critical, yet unsustainable for many parents (Lucas et al., 2020).

Different contexts gave rise to parents’ differential experiences of home-schooling. Parents with graduate degrees reported feeling more confident to home-school their children compared with non-graduate parents (70% and 60%, respectively). Graduate parents were also likely to help their children more frequently, with 80% of graduate parents home-schooling their children 4 days a week, compared to 60% of non-graduate parents (Anders, Macmillan, Sturgis & Wyness, 2020). However, further research reports that parental education was unrelated to the overall amount of time spent helping with their child’s schoolwork (Eivers et al., 2020).

Parents in the top fifth of earnings were also more likely to report feeling confident in their ability to make up for lost learning as a result of school closures, than parents in the bottom fifth of earnings (86% and 29%, respectively, Eyles & Elliot-Major, 2021). In general, more deprived families found it difficult to support their children as they felt they had more limited resources to do so (Andrew et al., 2020a; Child Poverty Action Group, 2020). Parents in middle income households in particular were in a uniquely difficult position to support their children’s learning. This is because resources were more limited. They were more likely to continue working at home through lockdown than the poorest households, while having fewer resources to support home learning than the wealthiest households (Andrew et al., 2020a; Green, 2020; Eivers et al. 2020).

Children receiving free school meals were more likely to receive help from their parents. This is largely driven by their parents being less likely to be working during the lockdown (Green, 2020). However, parents of children who were eligible for free school meals faced further challenges in that they were the least likely to feel confident about home-schooling, and least likely to understand their child’s learning tasks (Education Endowment Foundation, 2020b). There were also regional differences in parental support provided to home-schooling during the 2020 spring and summer terms that may be related to regional deprivation. Teachers in schools serving the most deprived communities reported less parental engagement than the least deprived schools (Lucas et al., 2020). The northern regions of England (Yorkshire and the Humber: 50%) saw slightly lower levels of parental engagement than the south and east of England (excluding London: 59%).

Parents report that home-schooling was particularly difficult for children with SEND. In June and July 2020, Parentkind asked parents of children with SEND about their home-schooling experiences. Overall, these parents were struggling with home-schooling, with 34% of parents reporting they were not coping well with the arrangements for learning since school closures began. Almost half further reported that they were unsatisfied with the home learning support that was provided by the school (Parentkind, 2020a).

Other family factors

A number of other family factors also impacted home-learning for many students. In particular, the literature explores the impact of parental working patterns, single-parent households, and the presence of siblings on remote learning.

The presence of a parent in the home was associated with a greater volume of remote learning. For instance, students participated in more remote learning when both parents worked from home during lockdown, compared with parents with other working patterns (Pensiero et al., 2020). Students with unemployed parents were also more likely to engage with more offline learning than students with working parents. The latter findings are likely to be a result of unemployed parents having more time to support their children, however, we should consider that these parents may also have been more aware of the activities their students were partaking in, and remote learning was likely more visible to them.

Employment status and working patterns during the lockdown are also closely linked to socioeconomic status, where the parents in the wealthiest families were more likely to continue working from home, compared with mid- and low-income families, where parents were more likely to continue working in their place of employment or be furloughed (ONS, 2021). It is therefore difficult to determine which factors were the most influential on students’ remote learning, as parents who worked from home during lockdown were also more able to support their child’s learning effectively, and provide home resources that facilitated this (Andrew et al., 2020a; Child Poverty Action Group, 2020; Eyles & Elliot-Major, 2021). But it is also true that the mere presence of a parent likely motivated and engaged students to undertake remote learning.

While there are small negative numerical differences in the home learning provision of children with lone parents compared with children who have more than one parent, these differences are not found to be statistically significant (Pensiero et al., 2020). There are similarities in the proportions of parents reporting that their child was home-schooled in May 2020: with 85% of single-parent households reporting their children were home-schooled, compared to 87% of households with more than one parent (Williams et al., 2020). There were also only marginal differences in the hours of schoolwork, hours of adult support and number of online lessons students took part in across single- and multiple-parent households (Pensiero et al., 2020). Overall, these findings indicate similarities in key aspects of remote learning across single and multiple-parent households, which contrast with earlier research that finds living in a single-parent household could hinder outcomes for the children that live in them (Hampden-Thompson & Galindo, 2015; Song et al., 2012). However, it should not be ignored that single-parent households are more likely to be supported by one income, and are therefore more likely to experience challenges in providing home-based resources (Benzeval et al., 2020). We discuss this further in the section, ‘Home learning resources’.

Where parents continued to work at their place of employment, students with siblings were more likely to have had caring responsibilities. Living arrangements such as this likely resulted in challenges to remaining focused on their school work (Impact Ed, 2020). Indeed, parents of older children who had a young sibling aged 0 to 4 were significantly more likely to say that their older child was struggling with remote learning because of caring responsibilities for their younger siblings (39% compared with 7% who had siblings in older age brackets, Williams et al., 2020). These parents were also most likely to report that their older child did not have a quiet place to study (41% compared with 13%).

Having siblings who were much older was beneficial to younger, primary-aged students as the older sibling often supported their younger siblings with school work. However, while this was beneficial for the younger siblings, for the older siblings this could distract away from their own learning (Pensiero et al., 2020). In contrast, for secondary school students with an older sibling, the younger sibling could be disadvantaged. This was because they often had to compete for resources, such as parental support and home-learning resources, such as computers and spaces to study (Pensiero et al., 2020). In general, having siblings undertaking remote learning in the same household was likely to reduce the degree to which students’ remote learning was successful. This is particularly likely where home resources, such as amount and quality of parental support, digital resources and places to effectively study, are limited. It is therefore expected that students with siblings in the least wealthy households had less effective home-learning experiences than those in the wealthiest households.

Home learning resources

Given that learning was taking place in the home for most students during the first lockdown, resources in the home were a larger influence on students’ learning. The main resources that parents, teachers and students reported were digital devices, access to the internet, access to study spaces and tutoring.

The move to remote learning with important aspects of it predominantly being online meant that digital devices and internet access within the home was more important than ever for students’ learning. Around 85% of secondary and 90% of primary students were reported as having access to a computer, laptop or tablet for their remote learning during the first lockdown (Andrew et al., 2020a), but there were many students who did not have suitable devices and internet access when schools and colleges closed in March 2020. Data from Ofcom’s Technology Tracker (2020) estimated that at the start of 2020, between 1.14 million and 1.78 million children in the UK under the age of 18 had no access to a laptop, desktop or tablet. They also estimated that between 227,000 and 559,000 students lived in households without internet access.

For those with access to digital resources, estimates indicate that around three quarters of secondary and post-16 students had access to their own device: either a computer or laptop (around 60-70%), or a tablet (around 10-20%; Andrew et al., 2020a; Pallan et al, 2021). For primary school students, expectedly, there was much less availability of personal computers and laptops. Around a third of primary students had access to their own device (Benzeval et al., 2020a), but many more had access to some form of digital device.

While around 25% of primary students used a computer or laptop as their main device when required, the predominant means of digital access for primary-aged students was via a tablet (40%). When considering the type of work that students were expected to take part in for their home learning, Andrew et al. (2020a) acknowledged laptops and computers seem to be the most useful devices for facilitating this. This is particularly the case for older students, considering that the work they would have completed typically involves more written text and complex structures, and therefore requires a device that can facilitate this type of work. The higher proportion of primary students using a tablet as their main device for their work also supports this idea, as primary-aged children received more paper-based worksheets, and online learning was largely used to catch up with their teacher or watch videos (Cattan et al., 2020; Lucas et al., 2020; Williams et al., 2020).

Although most students had access to devices for their remote learning, many are reported to have had to share them with family members (Child Poverty Action Group, 2020; Yeeles et al., 2020). Benzeval et al. (2020a) reports that more than half of students had to share their device with a family member (51%). This may be more of an issue for primary school students, as Andrew et al. (2020a) found that these students were more likely to share a computer and less likely to have access to their own device compared to secondary school students. Secondary students could be more likely to have their own devices and share with younger siblings, whereas younger siblings are more likely to have access only to someone else’s device. There were mixed impacts resulting from having to share remote learning devices (Pensiero et al., 2020). For primary school children, using a shared computer reportedly had no negative impacts on their learning. However, for secondary school children, sharing a device is reported to have been disruptive, with those sharing being less likely to take part in online lessons. However, for secondary students who did share devices they were more likely to receive more adult support (Pensiero et al., 2020).

Despite many students having access to suitable digital devices to undertake their remote learning, there was still a substantial number of students who did not. In May and July 2020, senior leaders and teachers reported that limited internet access was a significant challenge for around a quarter of students (Lucas, et al., 2020; Sharp et al., 2020), and around 4% of students overall were estimated to have had no access to a digital device at all during the first lockdown (Benzeval et al., 2020a). Using this and other sources, we can estimate that around 3-10% of students were accessing their remote learning using a mobile phone [footnote 2] (Andrew et al., 2020a; Pallan et al., 2021). Where students were using mobile phones to access their online learning, senior leaders raised concerns about how effective these would be (Andrew et al., 2020a). Although those students using mobile phones were able to access the learning content, this method was likely to be less conducive to learning than using a laptop, on account that the screen size and typing functionality of phones is greatly reduced (Andrew et al., 2020; Ofsted, 2021). This was likely problematic for being able to see the content of live lessons and videos, as well as for completing assignments, particularly those with large word counts or with more complex structures. Using mobile phones to access online learning is therefore likely to have been more disruptive to older students’ learning.

For students who did not have suitable digital devices at home, some schools were able to provide them. This provision was greatest in independent schools, where, as reported in May 2020, 38% of independent primary and 20% of independent secondary schools provided their students with devices, compared with 1% of state primary, and 7% of state secondary schools (Menzies, 2020). Access to digital resources was a key concern for schools and colleges at the start of the pandemic, and continued to be through to the autumn 2020 and spring 2021 terms. The government aimed to supply devices to children in the first lockdown to help with access to remote learning (Department for Education, 2020a), however there were delays and difficulties in achieving this (Education Policy Institute, 2020). By mid-June only 115,000 of the 200,000 devices that were ordered were delivered to local authorities or academy trusts (Department for Education, 2020a). The government further introduced the Get Help with Technology programme in January 2021 (Department for Education 2020b). However, access to digital devices with which to undertake remote learning was a concern that persisted throughout the 2020 spring, summer and autumn terms (we discuss this further in the section, ‘Teaching and learning in the 2020 autumn and 2021 spring terms’).

For some students, finding a suitable quiet space to work at home was also often challenging (Lucas et al., 2020). This was particularly the case for younger students. Around 20% of primary school students reportedly did not have a designated space to study at home, whereas this was the case for around 10% of secondary students (Andrew et al., 2020a; Andrew et al. 2020b). Those students without a suitable space to study found remote learning more difficult, and this had further negative implications for their motivation to study (Yeeles et al., 2020).

In addition to the remote learning provided by the school or college, some students received additional tuition. During the first lockdown, it seems that the majority of children were not receiving paid tuition. Andrew et al. (2020a) found that only 4% of primary students and 5% of secondary students spent any time with a paid tutor weekly. However, on average these students spent an hour and a half per day in tutoring. The uptake of additional tuition during the pandemic was most common from the autumn term, when there was more of a focus on identifying and recovering from lost learning. We discuss this further in the section, ‘The return to school in September 2020’.

Evidence indicates that there was variability in the degree to which home resources were able to effectively support remote learning. As is the general theme seen throughout this report, students who were most deprived tended to have home environments that were less conducive for remote learning. Disadvantaged pupils seem to have access to the fewest resources when learning at home. Child Poverty Action Group (2020) found that low-income families were twice as likely to report a lack of resources when supporting home learning, with 40% missing at least one essential resource. Students in the most deprived schools are less likely to have suitable IT access to engage in online learning remotely, in comparison with peers in the least deprived schools (Cullinane & Montacute, 2020; Sharp et al., 2020; Teach First, 2020). For instance, Lucas et al. (2020) found that the proportion of students with little or no IT access in the least deprived schools (19%) is half that of students in the most deprived schools (39%). Moreover, the most deprived students were around three times more likely to have used a phone or had no device to access schoolwork, compared to the least deprived students (Andrew et al., 2020c; Pallan et al., 2021).

Green (2020) found 20% of students eligible for Free School Meals (FSM) had no access to a computer at home in comparison to 7% of non-FSM students. This had further implications for teacher-student interactions, where students eligible for FSM were less likely to have their work checked by a teacher because they were unable to submit it.

Access to a quiet space to study at home also seemed to be a more prominent issue for disadvantaged students. Andrew et al. (2020a) found children from wealthier families are more likely to have access to a study space. Secondary school students in the poorest households were twice as likely not to have access to a study space (12%) compared with their counterparts in the wealthiest households (6%). For younger children, almost 60% of primary students in the least wealthy households did not have access to their own study space, compared with 35% of students in the wealthiest households (Andrew et al., 2020c). Similarly, in March to April 2020, it was found that around 29% of Pupil Premium students did not have a quiet area to study, compared with 16% of non-Pupil Premium students. Access to a quiet study space did not improve over the spring and summer terms (Cattan et al., 2021; Yeeles et al., 2020). Disadvantaged students were also more likely to have to share their quiet study space with others, and Pupil Premium students were more likely to report that the quiet study space in their home was not readily available for their use (Yeeles et al., 2020).

As well as being less likely to lack key resources, students in the least deprived families were most likely to benefit from learning resources above what they would usually experience. For instance, Eyles and Elliot-Major (2021) found parents in the highest fifth of incomes were over 4 times more likely (15.7%) to pay for private tuition compared to parents in the lowest fifth of incomes (3.8%). Where students from the least wealthy families did receive tutoring, they still received much less tutoring time (between 1-4 hours) than the wealthiest families (5 hours). Students from wealthier families are also reported to spend more time on remote learning because they are more likely to have better home learning conditions and resources to support this (Andrew et al., 2020c).

Schools and colleges offered various ways of supporting students over the first lockdown period. However, nationally available resources were not suited to students with special learning needs (Skipp et al., 2021). In addition, families of children with SEND often required specialist equipment to support their child in their home learning. Lack of suitable equipment was also an issue for apprentices. Doherty and Cullinane (2020) found that 37% of employers reported that some apprentices were unable to work from home because they did not have access to the equipment needed to continue working. Employers further report that 14% of apprentices could not learn from home due to a lack of internet or devices.

Of the households who were struggling to provide devices for their children, there was a disproportionate number of single-parent households (21%) compared with two-parent households (7%; Williams et al, 2020). However, struggling to access a device was not a universally held experience of students in single-parent households. A separate survey finds that a higher proportion of students with single parents have their own computer (59%) compared with students living in a household with more than one parent (44%; Benzeval, Booker & Kumari, 2020b). It therefore appears that there is a large range of experience in these contexts.

Student intrinsic factors

The previous sections discuss how school or college and home provision enabled, or disabled, students to continue their learning at home while schools and colleges were closed in the 2020 spring and summer terms. Another important element to learning centres on students’ internal responses. In particular, here we discuss findings from the literature regarding students’ engagement with learning during lockdown, and the roles of well-being and motivation to learn in this.

Many children and young people found the transition to life in lockdown difficult, particularly from a mental health and well-being perspective (Pallan, et al., 2021; The Children’s Society, 2020a, 2020b). There were many factors about living under lockdown restrictions, online learning and being unable to socialise with friends, that were reported as detrimental to students’ mental health, well-being and desire for learning.

Many students reported that increased screen time associated with online learning led to headaches, burnout and stress (Müller & Goldenberg 2020a, 2020b, 2021; Open Data Institute, 2020). Although many reported enjoying the flexibility of offline learning (Muller & Goldenberg), the lack of structure and routine could be difficult to navigate. For instance, some students reported being unmotivated or having no discipline to study, while others, particularly girls, lacked the discipline to restrict learning to normal school hours and often worked longer than they would usually, compared with boys (Impact Ed, 2020; NSPCC, 2020; Müller & Goldenberg, 2020b; Open Data Institute, 2020; Young Minds, 2020a).

Many young people also reported feeling stressed and anxious about different aspects of their life. This included worries about school work, family and homelife and the pandemic, and some were also experiencing bereavements (Child Poverty Action Group, 2020; Impact Ed, 2020; Mountford-Zimdars & Moore, 2020; Open Data Institute, 2020; The Children’s Society, 2020a; Young Minds 2020b). Overall, the evidence indicates that school closures had direct and large negative impacts on students’ mental health and well-being. This had important implications for their remote learning.

Analysis of survey data shows that there was a positive correlation between students’ well-being and learning during the pandemic (Impact Ed, 2020). This means that those reporting better well-being were also engaging more with their learning, and vice versa. In separate studies, more than half (53%) of students reported they were struggling to continue with their education during lockdown, and more than three quarters of students (77%) reported that learning from home was much more difficult than learning at school (Williams et al, 2020; Yeeles et al.,2020). The most common reason given for why students were struggling was lack of motivation (Williams et al, 2020), and when asked to describe their day-to-day life in three words, around a third of students (31%) expressed boredom and around a fifth (18%) described life as repetitive (Yeeles et al., 2020).

The largest source of evidence relating to students’ engagement with learning during the first few months of lockdown is a survey of over 3,000 teachers and senior leaders conducted in May 2020 (Lucas et al., 2020). When asked about the degree to which students were completing work set by the school or college, teachers reported that on average, they are in regular contact with around 60% of students, but that less than half of students had returned their last piece of set work (42%). Student’s own reports of their learning indicate widespread disruption (Pallan et al., 2021). Almost all surveyed – 96% – reported they were not learning at their normal level. They, on average, rated their learning at 61% or what it usually was.

Senior college leaders reported that engagement was lower for certain students. Adult learners found it more difficult to continue their learning because of competing homelife priorities, and students studying practical subjects were restricted in continuing the hands-on aspects of the course (Association of Colleges, 2020).

The degree to which students engage with their learning is only partly impacted by their well-being and motivation to learn. Their ability to access learning, the amount of parental support, and provision given by the school or college must also be considered. The overwhelming evidence indicates that the most deprived students are less likely to have internet access, digital resources, parental support and quality learning resources from the school (as previously discussed in the section, ‘Home learning provision’). Indeed, differences in the degree to which students from different backgrounds were engaged with their learning are reported.

Secondary teachers reported that 89% of students with limited digital resources and learning environments were less engaged than their peers (Lucas et al., 2020). NFER further notes that secondary students are particularly at risk of disengagement compared with primary students, because older children are less likely to have parental supervision. For secondary students with younger siblings, the older children are also likely to be supporting their younger siblings with their learning, which often detracted from their own learning (Pensiero et al., 2020; Williams et al., 2020). Students in years 11 and 13 also showed reduced engagement and motivation to learn during the 2020 spring and summer terms, although this may be related to the cancellation of national examinations such as GCSEs and A levels, and less provision for their learning, at least during the initial stages of school closures (Eivers et al., 2020).

Teachers serving the most deprived communities further reported that on average, only 30% of students returned work during the first lockdown, compared to 49% of pupils in the least deprived schools (Lucas et al., 2020). The lack of this type of engagement is, at least partially, driven by the most deprived students being less likely to have access to devices with which to submit their work. The schools with the higher proportion of students eligible for FSM are also less likely to report that students were engaging with learning. Moreover, teachers thought that 62% of vulnerable students were less engaged with learning than their peers. This was 58% for SEND students, 52% for Pupil Premium students, and 48% for young carers.

Teaching and learning in the 2020 autumn and 2021 spring terms

This section discusses provision for learning between September 2020 through to March 2021. This period saw students returning to school for the September term, school closures resulting in remote learning in January 2021, and returning to school in March 2021. However, there were exceptions to this, whereby many students were undertaking remote learning when many students were in school in the autumn term and from March 2021, and where many students were attending school during the periods of lockdown, when schools and colleges were closed to most, but not all students, between January and March 2021. Learning provision and experiences over these periods were diverse, and to understand them fully we address each period of learning separately, first addressing the return to school in September 2020, then the school closures from January 2021, and finally the re-opening of school from March 2021. Within these sections we look at how the school environment was different to in a normal year, and the barriers to teaching and learning students experienced. As mentioned previously, there is much less literature that looks at the impact of the pandemic on teaching and learning across this period, and this is particularly the case for the 2021 spring term. However, it is likely that the evidence previously explored that related to the 2020 spring and summer terms can be generalised to similar contexts on learning in the 2020 autumn and 2021 spring terms. We identify where we make these extrapolations.

Although students’ school or college attendance is clearly linked to learning provision over these periods, we leave this issue to be addressed more fully in Report 2 from our ‘Learning During the Pandemic’ series. In summary, attendance rates for students in school were largely dependent on how the pandemic affected their local area. For instance, attendance was lower for students in urban areas, and was lower for students in more deprived areas (Sibieta & Robinson, 2020). Attendance in regions that had the highest rates of COVID-19 cases also tended to be lower.

The return to school in September 2020

From September 2020, schools and colleges were expected to fully re-open to all students for the duration of the term. In order to control the spread of COVID-19, schools and colleges were required to ensure high standards of hygiene and promote social distancing as far as possible. Common approaches to this included separating classes or year groups into ‘bubbles’, reducing students’ movement around the school, arranging desks in forward-facing rows, and asking staff to socially distance from students and one-another (Sharp et al., 2020).

This ‘new normal’ in schools and colleges posed obvious challenges for teachers and school leaders as they were tasked with managing the conflict between maintaining social distancing, achieving full curriculum coverage and ensuring high-quality teaching and learning. Over the term, these challenges became, if anything, more significant. School leaders felt they were increasingly ‘firefighting’ as cases of COVID-19 increased nationally (Ofsted, 2020d). Keeping educational settings ‘COVID-secure’ took considerable planning, time and resources (Open Data Institute, 2020). This is likely to have impacted on the quality of pupils’ education and may have slowed the pace of learning, or catch up on learning, among pupils in the autumn term.

We have little data about the progress of any catch-up over the 2020 autumn term. However, in the fourth Parentkind Coronavirus Surveys carried out in November, 70% of parents surveyed felt their child was getting some or all of the support they needed to catch up on missed learning. Another 9% felt their child did not need support, but 10% of parents believed their child was not receiving the support they needed (Parentkind, 2020b).

For many schools and colleges, on the return to school in the autumn term catching up on lost learning was not the immediate focus. An NFER survey of school leaders in July found their top priorities for September were: providing support for pupil’s emotional and mental health and well-being, re-engaging pupils with learning, and settling them into school (Sharp et al., 2020). In primary schools, children’s well-being was an even greater focus, with over 83% of primary teachers and 72% of secondary teachers identifying this as their top priority in September (Sharp et al., 2020; see also International Literacy Centre, 2020a).

When schools and colleges reopened in September, most students had not been in a school for 6 months. In the intervening time, they had experienced stress, anxiety and even bereavement as a result of the pandemic (Child Poverty Action Group, 2020; Impact Ed, 2020; Mountford-Zimdars & Moore, 2020; Open Data Institute, 2020; The Children’s Society, 2020a; Young Minds, 2020b). Many schools and colleges therefore focused initially on students’ mental and emotional well-being, particularly for younger students, before the process of re-engaging them with learning could begin in earnest (International Literacy Centre 2020a, 2020b; Ofsted 2020b; Sharp et al,, 2020). For many schools and colleges, the autumn term was not a ‘quick fix’ period for lost learning (Ofsted 2020a; Ofsted 2020b; Ofsted 2020c; Ofsted 2020d; Sharp et al,, 2020), although students on exam courses may have been an obvious exception to this.

As the autumn term progressed, schools and colleges grappled with how to build a detailed picture of learning loss (Ofsted 2020a; Ofsted 2020b; Ofsted 2020c; Ofsted 2020d). In October, 61% of teachers reported that identifying the gaps in their students’ learning and determining how to help those who needed the extra support was a key challenge of their daily lives (Open Data Institute, 2020). We discuss the scale and nature of learning loss more fully in the section, ‘The scale and nature of learning loss’. As and when teaching and learning gaps were identified they adapted their curriculum accordingly.

By October, in primary education there was an increased focus on English and maths teaching (Teacher Tapp, 2020b), with curriculum adaptations being made in consideration of what had been missed (Ofsted 2020b). Schools and colleges used different strategies to support this focus. Some reduced teaching time for foundation subjects, but even when they continued to teach the full breadth of subjects, most made at least some adaptations to the order and content of the curriculum in response to gaps in learning and to COVID-19 restrictions. Practical aspects of subjects such as PE and music were sometimes not being taught (Ofsted 2020b; Ofsted 2020e), and there was a reduction in practical science being taught in primary schools (Teacher Tapp, 2020c). During this term, learning losses in certain subjects and content areas may therefore have persisted.

In secondary education, most secondary schools reported that their students came back to studying the full range of subjects when they returned (Ofsted, 2020e). Most schools visited by Ofsted had re-ordered their curriculums to prioritise key concepts and knowledge (Ofsted, 2020e). Many also reported restrictions on practical work, for example, suspending elements of music or PE. Some schools also had limited access to practical activities in Key Stage 3 for subjects such as science, design and technology, and computing. This was often because specialist teaching areas were not accessible to all student ‘bubbles’ and leaders tended to prioritise pupils in Key Stages 4 and 5 for these spaces.

‘COVID-secure’ practices continued to impact on pedagogy through the autumn term. A survey by Teacher Tapp in September found that primary schools were doing more mixed-ability teaching than in previous years, with almost three quarters of teachers teaching maths and reading in mixed-ability groups, an increase of around 15% compared with in 2019 (Teacher Tapp, 2020d). In some secondary schools, there was also an increase in mixed-ability maths teaching, although this was not widely practised (Teacher Tapp, 2020c). Work that facilitated engagement and collaboration between students was also reduced, with teachers reporting a reduction in group and paired work in the classroom (Sharp et al., 2020; Teacher Tapp, 2020c).

Adaptions to the curriculum, subject content and teaching practices were not the only changes students faced, however. The autumn term was characterised by further disruption of teaching and learning as a result of often frequent bouts of COVID-19-related illness and self-isolation for students and their teachers (Ofsted, 2020c). The impact of this was felt unevenly across the country, an issue which we explore in-depth in Report 2 from our ‘Learning During the Pandemic’ series, but it is also worth noting here in relation to the impact this had on the quality of teaching and learning.

Like in the summer term when schools reopened for some year groups, in the autumn term, schools and colleges regularly had to provide a mixed diet of face-to-face and online teaching, as individual students or ‘bubbles’ had to self-isolate. This way of teaching was challenging for teachers, but crucially it had an impact on the quality of provision for those having to studying at home (Open Data Institute, 2020; Sharp et al., 2020). In their autumn visits, Ofsted found that the remote learning experience was “patchy and, in many cases, was not aligned effectively with the classroom curriculum” (Ofsted 2020d). In particular, children isolating as part of a bubble appeared to receive better provision than those isolating individually. When bubbles isolated at home, many teachers used live or recorded video lessons. In contrast, when individual students isolated, there was often no live or recorded video teaching (Ofsted, 2020b; Ofsted, 2020c), and work set tended to consolidate previous lessons, rather than provide new material (Parentkind, 2020b; Murphy & Isaacs, in prep). Ofsted concluded that the experience of learning loss these children experienced in the summer was being repeated (Ofsted, 2020f).

COVID-19-related sickness and self-isolation also took its toll on staffing, resulting in students missing lessons with their usual teachers, and sometimes relying on supply teachers or non-subject specialists (Murphy & Isaacs, in prep). One in five teachers surveyed reported they had covered a class for an ill colleague that week, with 30% taking on other additional duties to cover absences (Teacher Tapp, 2020e).

All of this resulted in a teaching and learning experience that was far removed from what many teachers and students would have been used to. During the autumn term, there was recognition of the efforts of many schools to provide additional pastoral care (Ofsted 2020b; Ofsted, 2020c; Ofsted 2021) and support students in catching up (Parentkind, 2020b). Students seemed to have settled back into learning well (Parentkind, 2020b; Ofsted, 2020e; Ofsted, 2020b). Nonetheless, the various forms of disruption to teaching and learning caused by COVID-19 mean that the autumn term may have been associated with further learning losses for some students, rather than the productive period of catch-up that many had envisaged.

Many students continued to undertake periods of remote learning during the autumn term. Although access to devices was an initial barrier to learning in the first lockdown, by the autumn term most schools had overcome this (Ofsted, 2021). Many schools used parent questionnaires to identify students who needed digital provision, and sourced devices (such as laptops) for them from the local community. Some worked with external stakeholders (for example, charities, businesses) to acquire laptops. Only a few leaders stated access to digital provision remained difficult and, in such instances, leaders provided non-digital learning resources for these students.

Responses from a parent survey in November and December 2020 indicate that 1 in 10 parents were concerned about their child’s ability to access a suitable device and having poor internet (Ofsted, 2021). Many more parents were concerned about the content their child was studying (40%). These findings suggest that access to appropriate technology seems to have become less problematic in autumn term compared with the first lockdown, however there were clearly some students who were continuing to struggle with their home learning. This is particularly problematic considering the 2021 spring term started with another prolonged period of national remote learning.

The impact of the disruption to teaching and learning that students experienced over the autumn term would have varied significantly across individuals and schools and colleges. We have come across little data to suggest how the experience varied between different groups of students. However, it is clear that face-to-face teaching was most interrupted in schools and colleges in regions with the highest COVID-19 cases. This was initially problematic for the northern regions of England, however as the autumn term continued, COVID-19 cases also began to rise in London, the south and south-east (for more details see Report 2 from our ‘Learning During the Pandemic’ series).

From attendance data, it is clear that urban schools and colleges and those serving the most deprived communities had the most interrupted in-school learning time (Education Policy Institute, 2020), and it is also expected that schools and colleges with the most limited resources would have faced the most challenges in delivering concurrent in-school and online teaching. Similarly, the challenges to home resources students faced in the 2020 spring and summer terms for their remote learning are likely to have persisted, particularly with regards to lacking a quiet space to study and parental support. Moreover, although access to digital devices and the internet may have improved in the autumn term for many who needed them, some students were still unable to access their remote learning.

School closures in January 2021

Continued concerns about the rise in COVID-19 cases resulted in schools and colleges being closed from January until March 2021, which meant teaching and learning entered the second phase of national remote learning. In light of ongoing concerns about access to digital devices, at the start of the 2021 spring term, the government increased the help available for accessing laptops and tablets with the Get Help with Technology programme (Department for Education 2020b). This enabled wider accessibility of digital devices for students to undertake their learning where they did not have them. Challenges to accessing digital devices persisted, with almost half (47%) of senior leaders reporting that half or less than half of their students who needed a laptop had been supplied with one (Montacute & Cullinane, 2021). During this time, students in the most deprived schools were still more likely to have poor access to digital devices at home than those in the least deprived schools (25% compared with 15%, respectively; Nelson, Andrade & Donkin, 2021).

The quality of remote teaching provision appears to have improved during this period compared with the first lockdown in 2020, with live online lessons being much more prevalent across primary (49%) and secondary schools (78%) during this period (Nelson et al., 2021). In January 2021, 68% of teachers reported that every student they taught could take part in at least one online live lesson, compared with 17% in May 2020 (Teacher Tapp, 2021a). Student engagement also appears to be improved in January 2021 compared to in May and June 2020, with twice as many teachers being more likely to report that at least three quarters of their students were engaged with their work in January 2021, compared with in May and June 2020 (77% versus 39%, respectively, Teacher Tapp, 2021b). Higher proportions of students were returning work during this period too, with teachers reporting a rise from 42% in March 2020 to 55% in January-February 2021 (Nelson et al., 2021).

There were small, but statistically significant, increases in curriculum coverage during January and February 2021, compared with in March 2020 (66% to 70% respectively; Nelson et al., 2021). However, despite these increases, there were still large parts that remained uncovered. This is likely because the remote and COVID-safe nature of teaching meant some learning tasks were undeliverable.

Again, there seems to have been a disadvantage divide in the type of learning resources received across contexts, with 10% of the most deprived secondary schools not providing live online teaching in January 2021. For the most deprived primary schools, this was 48%. This contrasts with 4% of most affluent secondary state schools, and 37% of the most affluent primary state schools, who were not providing live online teaching during the same period (Teacher Tapp, 2021c). Provision for delivering online live lessons appears to have increased for schools serving disadvantaged communities as the spring term continued, with teacher reports about the resources offered to students in March 2021 showing no significant differences across the most and least deprived schools. Despite increases in the quality of learning resources, students in the most deprived schools were still less likely than students in the least deprived schools to attend the online lessons (59% and 78%, respectively), and return set work (47% and 67%, respectively, Nelson et al., 2021). This is likely a result of students in the most deprived schools continuing to have poorer home learning environments and digital access.

Despite schools and colleges being closed to most students during this time, they remained open for vulnerable children and children of keyworkers. Attendance data shows that the uptake of this provision was dramatically increased compared with the first lockdown (see Report 2 from our ‘Learning During the Pandemic’ series). This meant that many more schools and colleges would have been responsible for delivering more concurrent online and in-school teaching during this period of school closures, compared with in the first lockdown in 2020. Although there is no evidence to describe how this impacted teaching and learning provision, it is likely that the challenges reported in the autumn term for teaching via dual methods persisted into the spring 2021 term. No doubt, the challenges were likely felt more strongly in schools where resources were more limited.

The re-opening of schools and colleges in March 2021

After a second period of lockdown during the 2021 spring term, schools and colleges re-opened once again on 8 March 2021. We have little data on this new phase of teaching and learning. A March poll from Teacher Tapp confirms a strong focus on well-being and socialisation and re-establishing behaviour rules, particularly in primary schools. In secondary schools, these were also the priorities for students returning to school, but there was more of a focus to return to the curriculum as usual for secondary schools. Independent schools, in particular, planned to return to normal as quickly as possible, including reintroducing extra-curricular activities where they could (Teacher Tapp, 2021d). Overall, students seemed to be motivated and engaged with learning on the return to school in March, with teachers reporting that students had returned to school displaying behaviour which is similar or even better than it would be in normal times (Teacher Tapp, 2021e).

Schematic overview of the impact of the pandemic on learning

Figure 1 shows a summary of features that have influenced teaching and learning during the pandemic. This schematic shows the features associated with school and home provision, and student intrinsic factors, as well as the role of a range of contexts on learning. It is reproduced as text in Appendix A .

Figure 1. A summary of the features that have influenced learning during the pandemic.

The scale and nature of learning loss

As we have seen, the COVID-19 pandemic has had far-reaching effects on the learning experience of students in England, in terms of learning resources, quality and time (see Report 2 from our ‘Learning During the Pandemic’ series). There is widespread concern that students have fallen behind with their learning compared with where they would have otherwise been, and that many will need substantial support to ‘catch up’ (see Edurio, 2020; Sharp et al., 2020). Media articles also highlight dramatic learning loss (Lough, 2020). However, we have relatively little data about the scale of any learning loss caused by COVID-19, and no historical precedent of disruption on this scale from which we can draw estimates. There are broadly two means by which research explores the scale of lost learning. The first is research that aims to quantify the amount of learning students have lost during the pandemic, for instance through looking at student performance data. Report 3 from our ‘Learning During the Pandemic’ series looks at this in detail. The second is research that looks into teacher observations and estimates, which we focus on in this report. Note that we further discuss the differential experiences of learning loss across different contexts and backgrounds in the section, ‘The differential experiences of learning loss’.

Teacher estimates of lost learning

Various studies use teacher perceptions to quantify the impact of the pandemic on students’ learning. These all highlight some degree of learning loss, at least for the ‘average’ student (Murphy & Isaacs, in prep; Sharp et al., 2020). Here we look at teachers’ reports of learning loss and the degree of catch-up needed over the course of the pandemic, how learning loss was differential across different groups of students, and the nature of learning losses.

Estimates of the scale of lost learning

At the end of the 2019-20 school year, it was widely suggested that most students would need some form of additional support to ‘catch-up’, but that just under half (44%) of their pupils needed intensive catch-up support (Edurio, 2020; Sharp et al., 2020). Nearly all teachers (98% surveyed) reported that their students were behind where they would expect them to be in their curriculum learning [footnote 3] (Sharp et al., 2020). At that stage, on average, teachers estimated students to be 3 months behind. There are significant differences between teacher estimates, however, suggesting ‘average’ figures mask great variation between individual students and schools and colleges. At one extreme, 2% of teachers reported their pupils were not behind in their learning at all, whereas at the other, 4% felt students were 6 months or more behind. Interestingly, the extent to which students had apparently fallen behind was strongly associated with perceptions that parents were less engaged with their child’s learning, poorer teacher training provision, and teachers’ perceptions that they were unable to teach at their usual standard during national lockdown.

These estimates of lost learning are slightly higher than suggested by the assessment data (see Report 3 from our ‘Learning During the Pandemic’ series). It is difficult to know what to make of this difference. It could, for example, reflect the fact that teachers were asked to make an estimation of learning loss overall, rather than for specific subjects. These views may therefore reflect more learning loss in non-core subjects for which we don’t have supporting evidence from the assessment data. Alternatively, this could reflect limitations with using teacher estimates in this context. While in usual times, we would expect teachers to have a good understanding of students’ progress, at the end of the 2020 summer term most would not have seen their students for many months and may have struggled to judge their progress. Indeed in May 2020, around 15% of teachers reported that they did not know which of their students were having a successful learning experience ( Teacher Tapp , 2021f). Moreover, it is also likely to be difficult for teachers to accurately judge the average learning loss across all students they teach given the significant variation in student experiences of learning in the pandemic. Teachers’ judgements may also be skewed by some of the extreme cases of learning loss they have encountered. Some judgements may also reflect the volume of curriculum content taught by the teacher, while others may reflect the volume of knowledge that individual students have acquired. For that reason, it is advisable to interpret these estimates with caution.

During the 2020 autumn terms, teachers’ concerns regarding learning loss remained. In October 2020, in collaboration with Teacher Tapp, the Open Data Institute asked over 6,000 teachers in England what proportion of the pupils they teach were currently behind in their learning. Over two thirds stated that one fifth of their class or more was behind, and 44% said that one third of their class or more was behind. Again, there were extremes within this, with 5% of teachers saying that just one in 30 students was behind, compared with 8% who felt almost all of their pupils were behind (Open Data Institute, 2020).

Over the autumn 2020 term, Ofsted carried out hundreds of ‘interim’ visits to schools, colleges and other providers. In their findings they note that most students had slipped backwards in their learning to some degree, although there was little consensus on the scale of this. They note that “lost learning is unarguable, but it is hard to assess” (Ofsted, 2020d). In the early visits in particular, schools were grappling with the problem of how best to identify how much learning had been lost (Ofsted 2020b; Ofsted, 2020e). As the term progressed – and teachers had been better able to assess students’ progress – senior leaders increasingly talked about students having many gaps in their learning, or even having regressed. By the November visits, Ofsted reported a widespread view among primary school leaders that pupils were at the same level as they were before March, learning little during the first national lockdown or even falling back further. Other primary leaders quantified this in terms of being 6 months behind (Ofsted, 2020c). The picture was less clear in secondary schools, as teachers reported greater variability in gaps in learning between students.

At the start of the 2021 spring term during the second wave of national school closures, a former director at Ofsted is reported in a TES article acknowledging that although there is not currently data to highlight this, he suspects that learning loss in the 2021 spring term would be reduced compared with that in the initial March 2020 lockdown. This was accountable to schools and colleges becoming more proficient at remote education (Muijs, 2021) and wider access to digital devices with which to undertake remote learning in line with the Get Help with Technology programme. Surveys of teachers and college leaders in spring 2021 indicate, however, that their concerns over lost learning had not diminished. A quarter of secondary state school teachers indicated that all or the majority of students were behind in their learning due to missed learning over the course of the pandemic, with a similar picture for college students and adult learners (Association of Colleges, 2021; Teacher Tapp, 2021g).

One theme that emerged strongly in the Ofsted reports is the difficulty in quantifying learning loss given the varied learning experience that students had during the first national lockdown, particularly given their differing home environments. They place students into 3 broad groups (Ofsted, 2020d):

• Coping well: some students have been, and continue to be, coping well with their learning in the face of restrictions. These students are in line or ahead of where teachers would expect them to be in a normal year.
• Slipped back: the majority of students appear to be behind in their learning compared with where teachers would expect them to be in a normal year.
• Hardest hit: some students’ learning has been more greatly impacted by the pandemic. These students have the most learning loss and are severely behind where teachers would expect them to be in a normal year. This is predominantly a result of the interplay between their individual circumstances and the impact of the pandemic on them.

The literature does not, at least yet, report teachers’ views on the degree to which their students were behind in their learning in the 2021 spring term.

The nature of learning loss

Although we have some emerging data on the amount of learning students may have ‘lost’, there is little evidence exploring which specific aspects of learning have been lost. Much of what we know is taken from the findings of Ofsted visits in the autumn term. This is by no means a systematic assessment of the nature of learning loss, however, it does identify a number of subjects or content areas that school leaders identified as particularly concerning. We summarise the aspects of learning that are reported as having the most learning losses in Figure 2. This is reproduced as text in Appendix B .

Figure 2. Aspects of learning with the most notable losses.

Inevitably, the nature of learning loss varies depending on the phase of education. As reported earlier, primary leaders were most likely to report significant learning loss, with the youngest pupils apparently most negatively affected by the pandemic. In early primary education, school leaders noted issues with basic fine and gross motor skills. Some pupils were unable to hold a pencil or eat with a knife and fork, when they had been doing so before. Reading and phonic knowledge were of most concern to leaders. There was also loss of early progress in maths, with pupils falling behind in mathematical vocabulary, place value and recall, for example. Some leaders found writing was also an issue for pupils. Many had lost stamina when writing at length and struggled with spelling, grammar, presentation, punctuation and handwriting (Ofsted, 2020b).

At the start of the autumn term, some primary leaders also felt Reception children were not as ready for school as they usually are. A YouGov study found a similar issue with school readiness, suggesting that Reception children were less prepared for school than usual due to them having spent less time in nurseries during the pandemic (Kindred2, 2020).

Like primary leaders, secondary school leaders often said that students had fallen behind in maths and literacy. Leaders found ‘basic mathematical skills’ had been affected, as well as specific knowledge and skills including fractions, trigonometry and mathematical problem solving. ‘Basic literacy’ was leaders’ greatest concern with regard to English – again, spelling, grammar, punctuation and spoken English were all emerging issues. Some secondary leaders had also found that a lack of access to equipment in the first national lockdown had affected pupils’ learning in more practical subjects, such as in science, PE, design and technology, and music. They also mentioned that pupils had particularly fallen behind with their proficiency in modern foreign languages (Ofsted, 2020b; Ofsted, 2020c).

Some aspects of learning are most at risk of learning loss. These include content that the student will not be assessed on, enrichment activities and life skills. Indeed, in January 2021, primary teachers reported that they were not scheduling work for design and technology (53% of teachers), computing (44%), modern foreign languages (43%) and music (42%) (Teacher Tapp, 2021h). It is not clear from the literature if this is the case in secondary schools.

We know little about the nature of learning losses across vocational and technical qualifications, however, remote learning will have particularly hindered the learning of practical skills in these qualifications. This, in particular, has implications for many apprenticeships, and trades and beauty qualifications (see Association for Colleges, 2021). Many of these courses were not running fully by October 2020 and are linked to sectors hardest hit by the pandemic (Ofsted 2020a).

In special schools, the areas of learning affected most depended largely on students’ different needs, but also on their experience during the first national lockdown. The loss of physiotherapy, speech and language therapy and occupational therapy had caused issues, especially for children with more complex needs. Where the therapists are still not back in school working with the pupils, the impact continues. For example, the impacts are observed through regression in communication skills, physical development and independence. Leaders of special schools are further concerned about children being able to eat. Many leaders felt there was a need for further social and emotional support when students return to school. This especially applied to some pupils with autism spectrum disorder who had adapted to the isolation while learning at home (Ofsted, 2020b).

The differential experiences of learning loss

As previous sections highlight, there is diversity across different groups of students with regards to the experiences of teaching and learning during the pandemic. These experiences differ in terms of the type, amount and quality of learning provision; home resources to facilitate remote learning; and students’ levels of engagement. It is clear that all of these aspects of teaching and learning would impact the degree to which different groups of students have been able to maintain the pace of learning that would be expected in a normal year. It is therefore important to consider the differential impacts of these differences in experience, firstly in terms of what this means for learning loss, and secondly what this means for the already existing attainment gap between advantaged and disadvantaged students.

Learning loss across different groups of students

This section considers what the literature tells us about the scale of learning loss across different contexts. We also summarise findings relating to the different experiences of learning, as already discussed in the section, ‘The impact the pandemic has had on learning’, as a way of understanding how differential learning loss may have arisen.

This section summarises what the literature tells us about learning during the pandemic across the following contexts:

• age or stage of education
• deprivation and disadvantage
• attending state or independent schools
• students in other circumstances
• lower attaining students
• students with SEND

Age or stage of education

Most of the studies published so far suggest there have been some differences in the level of lost learning depending on student age or phase of education. Teacher estimates suggest more profound learning loss in primary education. NFER’s July study (Sharp et al., 2020) found primary teachers estimated students were slightly further behind normal expectations (by 3 months on average), compared to secondary school teachers’ estimates of their students (2.5 months behind). Approximately a third of primary teachers reported that their pupils were 4 or more months behind where they normally would be, compared to a fifth in secondary schools. By October, over half of primary teachers (52%) felt that at least one-third of their class was behind in their learning, whereas a third of secondary teachers felt the same (Open Data Institute, 2020).

In line with the above findings, Ofsted’s interim visits over the autumn term also point towards greater learning loss among primary students, particularly at key stage 1. The picture at secondary level appeared more variable, with most students generally ‘keeping up’, but others with significant learning gaps. However, Ofsted report that many secondary leaders expressed concerns about year 7 students as they missed out on a ‘normal transition’, and some leaders were concerned about year 11 students preparing for national examinations (Ofsted, 2020c).

There are a number of reasons why younger children may have experienced larger learning losses, which we have touched on previously. Compared to secondary students, for primary students, there was a greater focus on pastoral care than on curriculum coverage (Julius & Sims, 2020). Secondary students were also more likely to have better access to digital devices and online learning activities such as live lessons (Lucas et al., 2020). Numerous sources also suggest that parental engagement is particularly critical to the progress of primary pupils learning online (Child Poverty Action Group, 2020; Lucas et al., 2020; Sharp et al., 2020; Williams et al., 2020). Where parents have not been engaged, or able to engage, in their children’s remote learning during school closures, younger children are likely to have had their learning more severely disrupted because their ability to work independently is far reduced compared to older students. Indeed, students whose parents could help them during national lockdowns appear to have been more resilient to learning losses (Ofsted, 2020f).

As discussed previously, the learning experience also differed across secondary year groups, especially for year 11 and year 13 students in summer 2020. These students were less likely to receive remote learning resources from their school during the first national lockdown (Benzeval et al., 2020a; Eivers et al., 2020). Exam cancellations will have played a major part in the relative absence of school work for students in the second year of their qualifications. Regardless of the absence of the need to prepare for exams, some of these students whose learning was not provided for towards the end of their course may have missed opportunities to learn some content and consolidate their knowledge through revision. Some students will have disengaged entirely from their education for up to 6 months before starting a new course. While there is currently no research to indicate as such, it is likely that they will have found the return to education (either for key stage 5 or university courses) more challenging than students in a normal year.

Deprivation and disadvantage

Throughout the published literature, there is a strong focus on the interplay between economic disadvantage and experiences of learning in the pandemic. Some reports published early in the pandemic warned that COVID-19 is likely to increase educational inequalities between children from better-off and the poorest households due to its disproportionate impact on the most deprived (Children’s Commissioner, 2020; Edge, 2020; Education Endowment Foundation, 2020c; Montacute, 2020; Montacute & Cullinane, 2021). It was estimated that school closures may ultimately widen the existing attainment gap between disadvantaged children and their peers among primary school children by 36% [footnote 4] by September 2020 (Education Endowment Foundation, 2020c). The emerging data suggests these fears are likely to have been borne out to at least some degree.

Teacher estimates of lost learning suggest that students in schools serving more deprived communities have fallen further behind their peers. This was increasingly felt across the duration of the pandemic (Edurio, 2020; Montacute & Cullinane, 2021; Open Data Institute, 2020; Teacher Tapp, 2020b). For instance, in July 2020, NFER (Sharp et al.) found that more than half (53%) of teachers in the most deprived schools reported pupils were 4 months or more behind on average, compared to 15% in the least deprived schools. The need for intensive catch-up support was also 25% higher in the most deprived schools, compared to the least deprived schools (Sharp et al., 2020). By January 2021, 84% of teachers felt the pandemic would cause the attainment gap between the most and least disadvantaged to widen in their school (whereas it was 76% in November), with a third believing this gap would be “substantial” (33%, up from 28% in November). Teachers serving the most disadvantaged schools were most concerned about the attainment gap (Teacher Tapp, 2020b).

Overall, there is overwhelming research indicating a large disparity in the remote learning experiences of the most and least disadvantaged students. Deprivation and disadvantage seem to be most associated with poorer learning experiences and learning losses during the pandemic, with students in the poorest families, whose parents have lower levels of education, those who are eligible for FSM, and pupil premium students, being worse affected compared with their counterparts. The paragraphs that follow gather together the research findings discussed in the section, ‘The impact the pandemic has had on learning’ to form a fuller picture of why this is the case.

Schools serving the most deprived communities were less likely to provide online live lessons. Teachers were less likely to be in contact with deprived students, and were less likely to give feedback on their work, which can in part be accountable to the digital divide that was observed, particularly at the beginning of the pandemic. Many students in low-income families were missing essential resources to support their learning, such as digital devices and internet access. FSM eligible students were particularly at risk of this (Green, 2020). This meant that deprived students were less likely to engage with teachers and peers, submit work and receive feedback (Green, 2020). Teachers’ time was also more likely to be strained when they were teaching more deprived students, as there was a greater need to cater for a range of students’ circumstances. Teachers were often divided between creating and delivering online learning for those with digital access, as well as creating and delivering paper-based learning resources to those without digital access.

The home environment was also less effective in facilitating students’ remote learning for deprived and disadvantaged students. Although parental education was unrelated to the overall amount of time spent helping their child with school work (Eivers et al. 2020; Villasden et al. 2020), research indicates that less-educated parents were less likely to support their children with home-schooling, and were less confident doing so (Anders et al., 2020). This, in particular, reflects the experiences of students eligible for FSM (Education Endowment Foundation, 2020b). Lower-earning parents also felt less confident in their ability to make up for lost learning and were less likely to be able to provide resources to facilitate home schooling, such as digital devices and private tuition (Eyles & Elliot-Major, 2021). Many deprived students were also hindered by not having a quiet space to study at home. This was particularly problematic for Pupil Premium students (Yeeles et al. 2020).

Attending state or independent schools

In line with differential learning experiences for the most and least deprived students, there are also large differences between perceptions of learning loss between state maintained and independent schools. While 16% of independent school teachers surveyed in October 2020 reported that 1 in 5 students in their class are behind in their learning, this rose to 26% of state school teachers (Open Data Institute, 2020). By March 2021, once students had returned to school, around 8% of independent secondary school teachers reported all or a majority of students were behind in their learning, compared to 40% of teachers in the most deprived schools (Teacher Tapp, 2021g).

Overall, it is clear that students attending independent schools were more likely to have received better learning provision from their school, and to have had a home environment that better supported their remote learning. This is somewhat expected, given that school fees were still being paid and students’ and parents’ expectations of quality of teaching and learning remained high (Green, 2020). Independent school students seemed to be receiving more remote online lessons than state school students, and they were more likely to receive a full school day’s worth of remote learning (Elliot-Major, Eyles & Machin, 2020). In addition to online lessons, students attending independent schools were likely to receive more offline work than students attending state schools, and unsurprisingly, given the extent of teaching and learning provision, were likely to spend more time on their school work. The challenges in accessing digital resources that some students attending state schools experienced were not typically shared among students attending independent schools (Menzies, 2020), with almost all independent school children having computer access at home with which to undertake their remote learning (Green, 2020).

Students in other circumstances

During lockdown there was a breadth of circumstances that negatively impacted students’ experiences of learning, which go beyond the usual contexts that we tend to recognise as being disadvantageous. This includes students living in single-parent households or with multiple siblings, vulnerable children and children of keyworkers. Again, the literature does not provide teacher estimates of learning loss for students across these circumstances. However, we can infer from the wider research that some circumstances are more likely to be associated with greater learning losses than others.

There is mixed evidence relating to the impact of living in a single-parent household. Research indicates that the duration a child was home-schooled by their parent(s) did not differ if the students had a single or more than one parent, and had no impact on their learning outcomes (Pensiero et al. 2020; Villasden et al. 2020; Williams et al., 2020). This contrasts with earlier evidence finding that a single-parent household could hinder student outcomes (Hampden-Thompson & Galindo, 2015; Song et al., 2012). There was also contrasting evidence regarding access to suitable devices to undertake remote learning. Benzeval et al. (2020a) found that students in single-parent households were more likely to have their own computer than students with more than one parent. In contrast, Williams et al. (2020) found that single parents disproportionally overreported a lack of suitable devices for their children. The mixed evidence base exploring the impact of single-parent households may suggest that there is a wide range of experiences for students with a single parent. Research further indicates that having siblings in the same household could negatively impact remote learning success, particularly for older students where they take on caring and home-schooling responsibilities for their younger siblings (Impact Ed, 2020; Williams et al., 2020).

In the first lockdown, schools and colleges closed to most students, although not to those considered vulnerable. Julius and Sims (2020) found that vulnerable children were lacking engagement and parental support, with many vulnerable students not engaging in remote learning during this time. In addition, their in-school attendance was low, especially for secondary-aged students. In contrast, almost a fifth of teachers reported vulnerable children were more engaged than their classmates. This is likely most applicable to the students who continued to attend school during periods of national school closures. Many vulnerable students and keyworker children had similar and, in many cases, better supported learning than children learning remotely. However, a small share of vulnerable students and keyworker children did not receive a main focus on the curriculum during in-school provision. These students were disproportionately more likely to be younger (primary-aged) children in the most deprived schools. Students with keyworker parents appeared to not be disadvantaged with regards to the amount of home-schooling support they received, with this being similar to that received by students whose parents were not keyworkers (Villasden et al., 2020).

One reason for disadvantaged students’ low participation and engagement is found to be due to ‘new’ personal or family challenges they were facing during the lockdown (Hodgen, Taylor, Jacques, Tereshchenko, Kwok & Cockerill, 2020). For example, there was a worsening of pre-existing mental health problems for young people during lockdown (Young Minds, 2020a). In addition, Impact Ed (2021) raised concerns around children that struggled the most but were not previously identified as vulnerable – also referred to as ‘lost’ children. Teacher Tapp polling for IPPR also found that half of teachers were not confident in knowing which children had faced issues such as bereavement, abuse, parent mental health issues and new caring responsibilities during lockdown (IPPR, 2020).

Lower attaining students

There are few studies which consider the differential impact of the pandemic on students according to their prior attainment. Where these do exist, they suggest that lower attaining students (or schools serving these students) may have experienced, on average, more lost learning. In their survey of teachers, NFER found that teachers in ‘lower attaining’ schools were significantly more likely to report that their pupils were further behind compared to where they would normally expect them to be at this time of year (Sharp et al., 2020). A similar pattern emerged from a survey of teachers carried out in June and July 2020. When asked to assess changes in pupil attainment, 80% of teachers said that the attainment gap between the most and least able pupils was increasing, with 4 in 10 saying that it was “increasing a lot” (Edurio, 2020).

• Students with SEND

Qualitative data from Ofsted’s interim visits to schools in autumn present a mixed picture about the degree of learning loss for students with SEND, whether in mainstream or special education (Ofsted, 2020b). While some school leaders in mainstream education felt that SEND students have fallen further behind with their learning than their peers, others are reported to have benefitted from learning remotely at their own pace (Ofsted 2020g). Other school leaders noted that being in school throughout the first lockdown was protective against learning loss for some students with SEND, and some students were further ahead with their learning because they had had more individual attention and support. In special education, however, many school leaders found that some pupils’ communication and physical skills had regressed, particularly those with more complex needs who rely on multi-agency support which was not available during lockdown, and may not have restarted during the autumn term due to COVID-19 restrictions. Nationally available resources were also not tailored to students with special needs, and many struggled to engage with home learning as their learning environment was not designed to cater to their learning needs (Skipp et al., 2021).

Generally, there does not seem to be a clear message in the research in terms of differential learning loss between boys and girls. Most teachers surveyed by NFER (Sharp et al. 2020) reported no difference between genders in learning loss (78%), although those who did report a difference (21%) reported that boys had fallen further behind than girls. This was more marked among secondary teachers. Indeed, some studies found that girls completed more schoolwork than boys (Green, 2020; Pensiero et al. 2020). However, this difference is also observed for learning before the pandemic. These differences may also reflect reporting bias. Much of the data on students’ home learning comes from parental reports, which can more easily recognise learning activities undertaken by girls rather than boys because of differences in study behaviours (Green, 2020).

We have little data as to the degree of learning loss for students according to their ethnic group. In one study, teachers from schools serving the highest proportion of pupils from Black, Asian and Minority Ethnic (BAME) backgrounds were significantly more likely to estimate that their pupils needed intensive catch-up support, these views persisted even after controlling for the effects of deprivation. However, in the same study, there was no link between how far behind in their learning pupils were perceived to be and the proportion of BAME students within the school (Sharp et al., 2020).

Although primary language is not inherently related to ethnicity, it is also worth noting that Ofsted anecdotally report that some school leaders felt that pupils who speak English as an additional language were struggling more than others with some aspects of reading, writing and oral fluency (Ofsted, 2020b).

The Equality and Human Rights Commission (2020) noted that differences in remote learning support during the pandemic could widen inequalities for those that already perform less well than their peers, such as Black pupils and some Gypsy, Roma and Traveller students. According to the Department for Education (2020c) data, a smaller proportion of students of these ethnic groups receive grades 9-4 in English and mathematics.

There is evidence that students from some ethnic backgrounds were more likely to have disadvantageous learning experiences during the pandemic (Bayrakdar & Guveli, 2020). Mixed ethnicity students received less support in terms of computer access, other home resources and having their work checked by a teacher (Green, 2020). When looking at differences in actual learning during lockdown however, it is found that Asian students received more offline and marginally more online schoolwork than others (Green, 2020). But, these were small and statistically non-significant differences, not translating into large differences in time spent on homework. Another study found that Pakistani or Bangladeshi children spent significantly less time on schoolwork at home during school closures than others (Bayrakdar & Guveli, 2020). In contrast, Black children spent the most time on school work across all ethnic groups.

Differences in remote teaching and learning experiences can largely be accounted for by differences in school policies and the learning provision provided by the school or college, with BAME students more likely to attend schools that had poorer remote teaching provision (Green, 2020). It should also be considered that BAME students are more likely to be from more deprived communities, and as noted earlier in this section, these students are less likely to have experienced the better volume and quality of teaching and learning support compared to students from the least deprived communities, which likely contributes to these students falling further behind in their studies compared with their peers (Montacute, 2020; Montacute & Cullinane, 2021).

It is worth noting that COVID-19 has had a disproportionate health impact on people from certain ethnic groups (Mamluk & Jones, 2020). There is no data directly investigating how this has affected learning loss for these students. However, it is likely that in the least, these students will have had, in general, more negative experiences as a result of how the pandemic has impacted their lives, with regards to health anxiety, family members having the virus, and family bereavements. Students from BAME backgrounds were less likely to return to school when they reopened, which may have been a direct result of parents’ safety concerns in light of the increased risk of COVID-19 for these populations (Sharp et al., 2020).

The literature does not provide details regarding teacher estimates of lost learning by region. However, from the wider research there are some patterns and probable impacts of the pandemic on regional learning loss. The evidence points towards there being regional differences in students’ learning experiences as a result of the pandemic.

There were some differences in remote learning and educational engagement during the pandemic by region, which is noted to be largely a result of difference in schools’ policies between regions as well as regional differences in managing cases of COVID-19 (Green, 2020). Teachers reported lower student engagement in the West Midlands than in London. Some students in the northern regions were particularly disadvantaged compared to the south and south-east. In the northern regions there were lower levels of parental engagement and home resources, such as access to digital resources. Students also received fewer offline learning resources, and were less likely to be engaging in online conversations with teachers and other students in the north. Students in London and south-east England reportedly spent the most time on schoolwork, and students in these areas received the most offline learning provision. Schools and colleges in London also provided the most online teaching (Green, 2020; Lucas et al., 2020).

Regardless of region, more urban areas were typically more at risk than rural areas of disrupted learning, with student bubbles having to self-isolate or whole schools closing, meaning that those students not in school had to continue to learn remotely. All of these factors are likely to contribute to interrupted learning, and may manifest as increased loss of learning within regional clusters.

Widening attainment gaps

We have seen how the pandemic has impacted different groups of students differently, in terms of their experiences of learning during the pandemic and also what this means for their learning trajectories. It is clear from the research that remote teaching and learning pulled more heavily on home resources and parental support, and also relied on schools and colleges to be able to react quickly and effectively in their delivery of remote teaching. Because of the changing source of resource and support in learning during the pandemic, there are concerns about the disproportionately negative impact of the pandemic for disadvantaged students and the degree to which the pandemic has further exacerbated the attainment gap between disadvantaged and advantaged students (Children’s Commissioner, 2020; Education Endowment Foundation, 2020c; Montacute, 2020).

For those students experiencing the most lost learning, it is suggested that additional support is required from across the community above what would normally be available to enable students to recover their lost learning (Elliot-Major & Machin, 2020). These interventions may be critical for ensuring that inequalities in teaching and learning experiences do not damage future educational and occupational opportunities (Elliot-Major & Machin, 2020).

Overall, it is likely that the circumstances of the pandemic will contribute to the disadvantage gap widening. However, at this point the size and significance of this contribution is still unclear (see Report 1 from our ‘Learning During the Pandemic’ series).

Individual experiences of learning loss

The nature of much of the research into understanding learning during the pandemic is that it tends to present individual experiences using collective measures, either by students as a whole, or by different groups of students and students from different backgrounds. This is also how we have presented the findings in this report. Representing experience in this way is helpful for many reasons, not least because it facilitates wider understanding of the issues at stake, and helps to highlight inequality of experience across broad groups. However, this can also fail to represent many whose experiences do not align with the norm. Throughout the report we indicate that average measures tend to mask the experience of many students. Taking the example of time spent on remote learning tasks, for instance: on average, students reportedly took part in 1 to 2 hours of online learning provided by the school during the first national lockdown. However, there were many students who did not receive any online learning provision, and many students who were provided with a full day’s online learning.

The complexity of influential factors

Sometimes, differences in learning experiences were due to more macro-level influences. For instance, local variations in responses to COVID-19 during periods of regional increases in cases resulted in some areas seeing school closures and not others. The resources a school or college has access to also seems to impact the quality of provision delivered to students. Sometimes, differences in learning experiences were due to more micro-level influences, for instance, whether a student has sufficient access to a device at home for their remote learning, or the degree to which they are motivated to engage with school work. There is a complex interplay between these macro- and micro-level influences, which contribute towards unique experiences of learning, and learning loss, during the pandemic.

To explain the interplay between macro- and micro-level influences, we present three main features that explain how differences in students’ learning experiences during the pandemic may have arisen.

They are that disadvantageous experiences are:

• often accumulative
• are compounded
• that this gives rise to variation in experience between groups and within groups

Let’s consider these ideas more closely.

Disadvantageous experiences are often accumulative. By this we mean that disadvantage in one aspect is more often associated with disadvantage in another aspect, and vice versa. For instance, students who were provided fewer and lower quality provision from their school or college were more likely to have fewer, and lower quality, home resources too. In contrast, students who were provided with the largest and best quality school provision were more likely to have more and better-quality home resources. However, we emphasise that this is not the case for everyone. There will have been many students who lacked home-based resources, but were provided with high quality remote learning resources from the school, and vice versa. The issue is therefore much more complex than being that of privilege versus deprivation (see Ofsted, 2020f).

This leads us to the next feature, that disadvantageous experiences are compounded. By this we mean that there are many contributing factors with complex interactions that give rise to learning loss; which, collectively, contributes to the third feature: importantly, that these complex interactions may, or may not, play out as disadvantageous for individual students .

The negative impact of the pandemic on learning is not based on the number of disadvantageous experiences a student has. But, there are clearly elements that have more weight , and therefore more impact than others. We explain this across a series of hypothetical scenarios – note that these scenarios are intended to be illustrative rather than exhaustive.

Scenario one

A school provides the best online learning provision, but a student does not have access to an electronic device with internet access and this is a barrier to their learning.

Scenario two

A school provides the best online learning provision, and a student has the best home resources. But, the student lacks the internal motivation and discipline to engage with their learning. In this case, the student’s lack of intrinsic drive to undertake learning is a barrier.

Scenario three

A student does not receive good quality learning provision from the school, but has excellent home resources (for example, good parental support, access to additional learning resources and private tutoring). Although the poorer school provision is a barrier to learning, good home resources may make up for this. This student is therefore likely to have fared better than their classmates who did not have access to resources and private tutoring.

It is important to consider the unique experiences of learning during the pandemic, particularly when evaluating how to recover lost learning and implement assessment policy decisions. It is clear that students’ experiences of learning during the pandemic, and therefore the degree to which they experience learning losses, is varied, not only across regions and schools, but also across students in the same school or class. It is therefore unlikely that decisions to address these issues would benefit all students, let alone to the same degree.

What do we know about learning experiences during the pandemic?

We’ve seen how there are many factors that have contributed towards effective, or ineffective, teaching and learning since the pandemic caused schools and colleges to initially close in March 2020. In general, the quantity and quality of teaching and learning during the pandemic was reduced compared with normal times.

The literature identifies several barriers to teaching and learning. From March 2020, teachers had to adjust quickly to new means to teaching remotely. Some reported that their limited confidence and skills in using IT and creating online resources made delivering online learning difficult. For many, particularly those serving deprived communities, they found they spent much of their time creating learning resources that could be accessed by all. Some teachers even reported hand-delivering paper-based resources.

Many students reported dips in motivation, on top of difficulties with their mental health and well-being. This, coinciding with fewer opportunities to engage with peers and teachers, meant that they found it difficult to stay on track with their learning. For some students, the home environment was also not conducive to effective learning. This was particularly problematic where they had limited access to the internet and devices with which to undertake their schoolwork. Some students also took on responsibilities to support their siblings with home-schooling, and for many, their parents were not able to give enough learning support.

Although in-school teaching is seemingly more conducive to effective pedagogy than remote learning, teaching and learning was somewhat deprioritised in many schools on the initial return to school in September 2020. This was particularly the case for primary, and less so for secondary, schools. For many students, the impacts of the pandemic took considerable toll on their social, emotional and mental health. For many schools and colleges, at least initially on students’ return, they therefore felt a more pressing need to support their students’ well-being over covering the curriculum.

The most notable challenge to teaching in the autumn 2020 term was the learning environment. COVID-19 restrictions and social distancing in schools and colleges reduced teacher-student engagement, and for many students, large proportions of the term were still not spent in the classroom with the teacher. Overall, although the quality and amount of learning in the autumn term was better than when it was remote, it was still far removed from the quality of teaching delivered before the pandemic. Teachers reported feeling as though they were ‘firefighting’: their efforts to support mental health and well-being, recovery of lost learning and covering the curriculum, keeping students and school staff safe.

In January 2021, further school closures meant that learning was undertaken remotely again. It is likely though that this phase of remote teaching was more successful than the initial phase when schools and colleges were closed from March 2020. This is because teachers were more attuned to delivering remote teaching, and there was better access to digital devices for students to engage in their remote learning. However, a larger proportion of students continued to attend school in January than during the first lockdown. Where teachers had to deliver remote teaching at the same time as in-school teaching, this was likely met with challenges and had implications for the quality of learning experienced.

What do we know about learning losses during the pandemic?

Most students appear to have experienced learning losses to some degree, and some have experienced severe learning losses. Reports often indicate that maths and literacy skills are most notably behind. Practical skills are also reported to have suffered, which is particularly problematic for courses that are largely practical in nature, such as some apprenticeships and trades and beauty qualifications.

Much of the learning losses are due to periods of remote learning. However, even when students were back in school, a need to focus on well-being, as well as changes to the learning environment as a result of COVID-safe restrictions, meant that learning could still not continue as normal. A small proportion of students seem to have thrived in their new learning environments and actually experienced learning gains above what would be expected in a normal year. This group includes students who had the best remote and in-school learning resources, such as those in the least deprived state schools and independent schools. Some students with special educational needs are also reported to have made better progress with their learning during the pandemic, particularly when learning remotely. Others, however, were unable to make progress with their learning remotely as they were lacking vital equipment that was otherwise available in school.

While teachers gave estimates of the scale of learning loss, these accounts were often subjective and could be based on the level of content a teacher had been able to teach, rather than an objective measure of content the student understands. We discuss more objective measures of learning loss in Report 3 from our ‘Learning During the Pandemic’ series. Nevertheless, it is likely that the extent and nature of learning losses will not be known until much later. We may gather some insight into learning loss as a result of the pandemic by measuring students’ preparedness to study new courses in September 2021, as well as from the National Reference Tests this year, and from end of course assessments for years to come.

What do we know about differential impacts of the pandemic on learning, and why are these important to consider?

A running theme throughout this report is that experiences of teaching and learning during the pandemic were diverse. The clearest driving factor of this is disadvantage and deprivation. The most deprived schools and households were, in general, less able to support students’ learning compared with the least deprived. This was the case during periods of both remote learning, as well as when students returned to school. Teachers also reported that gaps in learning were more pronounced for the more deprived students. This leads to concerns around the already existing attainment gap between the most and least advantaged students, and how the uneven impact of the pandemic is likely to have widened the attainment gap further.

Despite this broad picture, Ofsted’s visits remind us that the picture is not a simple one. While, on average, deprived students and schools serving more deprived areas may have suffered disproportionally from learning loss, the reality is that each child has had their own very unique experience of the pandemic and has faced different challenges. When discussing the groups who have been most affected by the pandemic, Ofsted note “This shouldn’t be confused for a simple message about privilege versus deprivation” (Ofsted, 2020f, p2).

There were further concerns about younger children. Teaching and learning during the pandemic were particularly negatively impacted for primary students. The level of support that younger students needed for their remote working was less readily available and learning tasks for this age were less amenable to a remote context. Teachers reported the most learning losses among primary students and raised concerns about how this may negatively impact their learning trajectories for years to come.

The literature identifies differential learning experiences and learning loss across groups of students and identifies groups of students that are otherwise not typically associated with being disadvantaged. This includes vulnerable students, students whose parents are keyworkers, and to some extent, students who had caring and home-schooling responsibilities for younger siblings. While it can be helpful to explore issues with relation to overarching groups of students, the unique individual experiences students had should not be ignored.

We have explored how there is a complex interaction between macro- and micro-level influences that contribute to the differential learning experiences between and within groups. In particular, it appears that factors that impact effective learning were typically accumulative, but compounded, giving rise to complex and often unique variations in experience. This means that there will have been students who appear to have had an arsenal of high-quality learning resources, who have nevertheless found their learning during the pandemic incredibly disrupted.

This consideration of the complexity and uniqueness of learning experience and any related learning losses is an important one. Schools, colleges and policy makers should be mindful of this when deciding the best course of action for education to recover from the pandemic, particularly as a one-size solution is unlikely to be equally beneficial.

This report focuses on the impact of the pandemic on students’ learning, and associated learning losses, but we should also acknowledge that the changes to teaching in the last year also had a large impact on teachers and school staff. Teachers took on many responsibilities that went beyond their usual work and should be recognised for their efforts. While also managing impacts of the pandemic in their own lives, many were also undertaking training in digital teaching, hand-delivering work for students who had barriers to accessing digital resources, putting an extra focus on pastoral care, making changes to lesson plans, changing how some course content was taught, as well as taking on extra work to cover staff illness.

Areas for further research

The existing literature offers a lot of useful insight into learning during the pandemic, and the research community has produced a large amount of research in a relatively short time. However, there are still some specific learning contexts for which we are largely unaware of the impact of the pandemic and would be a useful focus for future research. We have already discussed the value in exploring individual’s experiences in more depth and grappling with the extent and nature of learning losses. We identify some additional contexts for further research.

Overall, the literature is relatively lacking in research and analysis focused specifically on students who were in years 11 and 13 at the start of the pandemic in March 2020. The research mostly groups students into primary or secondary phases of education, although ‘post-secondary’ is also mentioned in some literature and presents findings in these groups. This is a relatively simplistic breakdown given the differences between students, and that provision is likely to have been different across year groups within these phases. Consider, for instance, that students in year 7 would be in the same ‘secondary’ group as the students in years 10 to 13; and year 1 students would be in the same ‘primary’ group as students in year 6. As we have mentioned above, when the pandemic initially resulted in school closures, students in years 11 and 13 who were preparing for their exams in summer 2020 are reported to have received less learning provision on account of their exams being cancelled. It is not clear if learning (or revision) provision picked up again as the pandemic continued or not. This has important implications for the degree to which students in these year groups were prepared for their next educational or occupational endeavours. Similarly, there is little to no information about the experiences of learners who continued to be assessed in summer 2020. Students who were in years 10 and 12 in March 2020, and other students who were preparing for assessments in 2021, are also likely to have had a very different experience of learning over the past year compared to students who are not on assessed courses. Again this is also something we currently know little about.

There is also large variation in maturation of students across the primary and secondary year groups. It is therefore not unreasonable to assume that the most suitable provision for students across these phases would differ based on this too. For instance, the degree of scaffolding and parental or teacher support needed to maintain student engagement in remote learning would be different depending on if the child was in year 1 compared with in year 6, and similarly different for year 7 students compared with year 11s.

From the literature, it seems that some aspects of learning were more difficult to deliver in a COVID-safe way. In some cases, the impact of this could be relatively small. For instance, where teachers report not being able to share equipment to undertake science practical work, this is likely to impact a smaller proportion of learning. Learning in some qualifications is also likely to have been more disrupted. Most schools and colleges offer GCSEs, A levels and a suite of vocational and technical qualifications. Those qualifications for which learning (or aspects of) could not continue remotely are likely to be the hardest hit. The literature is yet to explore this fully, but we have seen how students on more practical courses and apprenticeships have suffered.

It also appears that some schools deprioritised learning that was not linked to assessments, such as enrichment activities and complementary subject content. The impact of this is currently unknown, but may have negative implications for future learning, life skills and well-being.

An evaluation of the literature sources

We note in the introduction that we reviewed a considerable volume of research that contributed to this report. Although this report did not take a methodological ‘systematic review’ approach, it intended to be comprehensive. As well as reviewing all of the literature we had access to that was relevant to the impact of the pandemic on learning, we were also in contact with research groups contributing much of the research within this report to ensure our interpretations of the research are reflective of the original findings.

There are a few things to be mindful of when interpreting the findings from the research literature. Firstly, although student accounts are also taken into consideration, a lot of the literature uses teacher and parent reports to understand students’ experiences. Because of this, the accounts may not wholly or accurately reflect students’ experiences. For instance, a teacher may report that they provided several opportunities for teaching and learning, however the student may not have engaged with them. Similarly, when estimating the degree of learning losses, teachers may confound comparisons with content that has been taught with the knowledge, skills and abilities the students actually acquired. Parents are also likely to only report on the educational engagement that they observe or believe their children to be undertaking. Findings may therefore under- or over-inflate students’ actual learning experiences.

Secondly, as previously discussed and therefore not dwelled upon here, the full diversity of learning experiences during the pandemic is unlikely to be captured by the existing literature. This is because much of the research focuses on large-scale data sets and survey responses, from which findings are averaged and opportunities to explore experience in-depth are lacking. Although there are undeniable benefits to these pieces of research, as discussed above, experiences that do not fit the ‘norm’ are often not represented.

Thirdly, the research findings between reports can often be different, despite similarities in the issues explored. Mostly, these reflect small differences across reports in the proportions of individuals that share the same experiences. These instances are typically due to sample differences. However, sometimes there are more striking differences. These are generally accountable to differences in methodology: how the issues were explored and the context responses were collected within. By and large the research findings reporting learning experience during the pandemic have comparable narratives. Where the research findings were more varied, we highlighted these in the body of the report and identified potential reasons for the dissimilarity.

It is clear too that the literature has evolved over the duration of the pandemic. After the initial school closures, there was a focus on how teachers, students and parents were managing remote learning during the first lockdown in 2020. This research is largely comprised of surveys, which are a useful tool in being able to react quickly to changing circumstances, as they can be rapidly launched and analysed. As the pandemic continued, the focus of the literature generally shifted to looking at how the pandemic impacted the return to school, the degree to which students’ learning had been interrupted, the nature of lost learning, and how lost learning was being recovered. Like the initial array of research, survey data contribute to these findings, but this is complemented with in-school observations and measures of where students were at with their learning. What is noticeable is that the volume of research is much less as the pandemic continued through the autumn term, and into spring 2021. There could be a couple of reasons for this. This could be a result of the expected delay between undertaking research and disseminating it: as such it is likely that we will see a larger research response in future. Alternatively, research groups could be focused on issues that are not in scope of this report, such as using attainment to measure the scale of learning loss, focusing on arrangements for assessments in 2021, or thinking ahead to educational issues for 2022.

The literature included in this review is varied. It includes academic peer-reviewed journal articles, as well as ‘grey literature’. Grey literature refers to work that has not undergone a process of peer review. It is typically produced by those who have an interest in the topic and is considered to provide useful contributions to knowledge in its field (Adams, Smart & Huff, 2017; Sharma et al., 2015). A large body of literature referred to in this report has been undertaken by organisations that have an established interest in teaching, learning and student experiences. This is beneficial as these organisations often have access to information and means of gathering data that could otherwise be less easily and rapidly acquired. This has further positive implications for the ecological validity of the research, that is, the degree to which the data accurately reflects real experiences. Examples of this, for instance, are the Ofsted reports that reviewed schools’ teaching practices through in-school observations. Grey literature is not without its limitations, however, as it is possible that findings could reflect the organisational agendas by which they are produced. Because of this, additional care has been taken when evaluating findings and interpreting conclusions of these pieces of research for this review.

Overall, the coronavirus (COVID-19) pandemic has had a detrimental impact on learning in England. There were challenges to learning, both when it was remote and in-school, which resulted in a reduction in the quality and quantity of students’ learning.

Learning has been disrupted for most students. For a small proportion, learning has been severely disrupted, while for some others there have been some learning gains. Teachers report the most learning losses in literacy and maths. Practical qualifications and practical aspects of courses have also been particularly disrupted. The impacts of the pandemic on learning are reported by teachers to have been uneven. Learning has been the most disrupted for the most deprived and disadvantaged students, and least disrupted for socioeconomically advantaged students, although there will of course be exceptions to this.

While students with similar backgrounds are more likely to have had similar experiences of learning and learning loss, this report highlights the importance of considering individual experiences. Indeed, there are stark differences between and within contexts, which we note are driven by the complex interactions of the unique circumstances that each student is in and are therefore difficult to predict. It is therefore crucial that mitigations of lost learning, wider educational assessment policy-making and learning recovery programmes acknowledge this complexity to ensure that the benefits are fair and far-reaching.

A summary of features that have influenced teaching and learning during the pandemic.

School provisions.

• Online, live lessons
• Offline, independent study.
• Amount of remote learning provided
• Live interactive communication
• Pastoral care
• Focus on mental health and well-being
• Teaching in line with Covid-safety restrictions
• Pace of teaching and learning
• School resources
• Pattern of school closures

Home Provisions

• Engagement with home-schooling
• Time spent home-schooling
• Ability to home-school
• The presence of a parent during remote learning
• Single or two-parent households
• Number and age of siblings
• Vulnerable children
• Keyworker parents
• Access to digital devices and internet
• Suitable study spaces
• Private tuition
• Internal vs external sources of motivation
• Flexibility to learn remotely vs lack of structure
• Stress, anxiety, well-being and burnout
• Ability to study independently
• Need for pastoral care
• Multi-level: communities, schools and families
• School type
• State vs private schools
• Impact of Coronavirus (COVID-19)
• Low attainers

Aspects of learning that are reported as having the most notable learning losses.

• Fine and motor skills
• Reading and phonic knowledge
• Literacy: spelling, punctuation, grammar, handwriting, presentation and writing stamina
• Mathematical vocabulary, place value and recall
• Literacy: spelling, punctuation, grammar and spoken English
• Maths: fractions, trigonometry and problem solving.
• Modern foreign languages
• Practical aspects in sciences, PE, design and technology and music

Vocational and Technical qualifications

• Practical aspects such as in trades and beauty qualifications
• Skills in apprenticeships linked to the hardest hit sectors

Special schools

• Regression in communication skills
• Physical development
• Independence

More generally

• Unassessed content
• Enrichment activities
• Life skills

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Note, that while schools were closed, in-school provision was still available for keyworker and vulnerable children, and in June 2020 some year groups were invited back into schools. We explore these contexts further in the sections, ‘In-school provision for children of keyworkers and vulnerable students during the first lockdown, and ‘The return to school for some students in June 2020’ respectively.  ↩

Andrew et al. (2020a) estimate that 15% of secondary and 10% of primary students either did not have access to a computer, laptop or tablet for their remote learning or were using a mobile phone to access remote learning.  ↩

Defined by NFER as “the knowledge and skills that pupils are expected to acquire through the curriculum, including specific learning standards or objectives that they are expected to meet” (Sharp et al., 2020, p.14).  ↩

However, Education Endowment Foundation note that estimated rate of gap widening varied substantially between studies, meaning that there is a high level of uncertainty around this average. Plausible “good” and “bad” estimates range from the gap widening from 11% to 75%.  ↩

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• Published: 16 June 2020

COVID-19 impact on research, lessons learned from COVID-19 research, implications for pediatric research

• Debra L. Weiner 1 , 2 ,
• Vivek Balasubramaniam 3 ,
• Shetal I. Shah 4 &
• Joyce R. Javier 5 , 6

on behalf of the Pediatric Policy Council

Pediatric Research volume  88 ,  pages 148–150 ( 2020 ) Cite this article

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The COVID-19 pandemic has resulted in unprecedented research worldwide. The impact on research in progress at the time of the pandemic, the importance and challenges of real-time pandemic research, and the importance of a pediatrician-scientist workforce are all highlighted by this epic pandemic. As we navigate through and beyond this pandemic, which will have a long-lasting impact on our world, including research and the biomedical research enterprise, it is important to recognize and address opportunities and strategies for, and challenges of research and strengthening the pediatrician-scientist workforce.

The first cases of what is now recognized as SARS-CoV-2 infection, termed COVID-19, were reported in Wuhan, China in December 2019 as cases of fatal pneumonia. By February 26, 2020, COVID-19 had been reported on all continents except Antarctica. As of May 4, 2020, 3.53 million cases and 248,169 deaths have been reported from 210 countries. 1

Impact of COVID-19 on ongoing research

The impact on research in progress prior to COVID-19 was rapid, dramatic, and no doubt will be long term. The pandemic curtailed most academic, industry, and government basic science and clinical research, or redirected research to COVID-19. Most clinical trials, except those testing life-saving therapies, have been paused, and most continuing trials are now closed to new enrollment. Ongoing clinical trials have been modified to enable home administration of treatment and virtual monitoring to minimize participant risk of COVID-19 infection, and to avoid diverting healthcare resources from pandemic response. In addition to short- and long-term patient impact, these research disruptions threaten the careers of physician-scientists, many of whom have had to shift efforts from research to patient care. To protect research in progress, as well as physician-scientist careers and the research workforce, ongoing support is critical. NIH ( https://grants.nih.gov/policy/natural-disasters/corona-virus.htm ), PCORI ( https://www.pcori.org/funding-opportunities/applicant-and-awardee-faqs-related-covid-19 ), and other funders acted swiftly to provide guidance on proposal submission and award management, and implement allowances that enable grant personnel to be paid and time lines to be relaxed. Research institutions have also implemented strategies to mitigate the long-term impact of research disruptions. Support throughout and beyond the pandemic to retain currently well-trained research personnel and research support teams, and to accommodate loss of research assets, including laboratory supplies and study participants, will be required to complete disrupted research and ultimately enable new research.

In the long term, it is likely that the pandemic will force reallocation of research dollars at the expense of research areas funded prior to the pandemic. It will be more important than ever for the pediatric research community to engage in discussion and decisions regarding prioritization of funding goals for dedicated pediatric research and meaningful inclusion of children in studies. The recently released 2020 National Institute of Child Health and Development (NICHD) strategic plan that engaged stakeholders, including scientists and patients, to shape the goals of the Institute, will require modification to best chart a path toward restoring normalcy within pediatric science.

COVID-19 research

This global pandemic once again highlights the importance of research, stable research infrastructure, and funding for public health emergency (PHE)/disaster preparedness, response, and resiliency. The stakes in this worldwide pandemic have never been higher as lives are lost, economies falter, and life has radically changed. Ultimate COVID-19 mitigation and crisis resolution is dependent on high-quality research aligned with top priority societal goals that yields trustworthy data and actionable information. While the highest priority goals are treatment and prevention, biomedical research also provides data critical to manage and restore economic and social welfare.

Scientific and technological knowledge and resources have never been greater and have been leveraged globally to perform COVID-19 research at warp speed. The number of studies related to COVID-19 increases daily, the scope and magnitude of engagement is stunning, and the extent of global collaboration unprecedented. On January 5, 2020, just weeks after the first cases of illness were reported, the genetic sequence, which identified the pathogen as a novel coronavirus, SARS-CoV-2, was released, providing information essential for identifying and developing treatments, vaccines, and diagnostics. As of May 3, 2020 1133 COVID-19 studies, including 148 related to hydroxychloroquine, 13 to remdesivir, 50 to vaccines, and 100 to diagnostic testing, were registered on ClinicalTrials.gov, and 980 different studies on the World Health Organization’s International Clinical Trials Registry Platform (WHO ICTRP), made possible, at least in part, by use of data libraries to inform development of antivirals, immunomodulators, antibody-based biologics, and vaccines. On April 7, 2020, the FDA launched the Coronavirus Treatment Acceleration Program (CTAP) ( https://www.fda.gov/drugs/coronavirus-covid-19-drugs/coronavirus-treatment-acceleration-program-ctap ). On April 17, 2020, NIH announced a partnership with industry to expedite vaccine development ( https://www.nih.gov/news-events/news-releases/nih-launch-public-private-partnership-speed-covid-19-vaccine-treatment-options ). As of May 1, 2020, remdesivir (Gilead), granted FDA emergency use authorization, is the only approved therapeutic for COVID-19. 2

The pandemic has intensified research challenges. In a rush for data already thousands of manuscripts, news reports, and blogs have been published, but to date, there is limited scientifically robust data. Some studies do not meet published clinical trial standards, which now include FDA’s COVID-19-specific standards, 3 , 4 , 5 and/or are published without peer review. Misinformation from studies diverts resources from development and testing of more promising therapeutic candidates and has endangered lives. Ibuprofen, initially reported as unsafe for patients with COVID-19, resulted in a shortage of acetaminophen, endangering individuals for whom ibuprofen is contraindicated. Hydroxychloroquine initially reported as potentially effective for treatment of COVID-19 resulted in shortages for patients with autoimmune diseases. Remdesivir, in rigorous trials, showed decrease in duration of COVID-19, with greater effect given early. 6 Given the limited availability and safety data, the use outside clinical trials is currently approved only for severe disease. Vaccines typically take 10–15 years to develop. As of May 3, 2020, of nearly 100 vaccines in development, 8 are in trial. Several vaccines are projected to have emergency approval within 12–18 months, possibly as early as the end of the year, 7 still an eternity for this pandemic, yet too soon for long-term effectiveness and safety data. Antibody testing, necessary for diagnosis, therapeutics, and vaccine testing, has presented some of the greatest research challenges, including validation, timing, availability and prioritization of testing, interpretation of test results, and appropriate patient and societal actions based on results. 8 Relaxing physical distancing without data regarding test validity, duration, and strength of immunity to different strains of COVID-19 could have catastrophic results. Understanding population differences and disparities, which have been further exposed during this pandemic, is critical for response and long-term pandemic recovery. The “Equitable Data Collection and Disclosure on COVID-19 Act” calls for the CDC (Centers for Disease Control and Prevention) and other HHS (United States Department of Health & Human Services) agencies to publicly release racial and demographic information ( https://bass.house.gov/sites/bass.house.gov/files/Equitable%20Data%20Collection%20and%20Dislosure%20on%20COVID19%20Act_FINAL.pdf )

Trusted sources of up-to-date, easily accessible information must be identified (e.g., WHO https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov , CDC https://www.cdc.gov/coronavirus/2019-nCoV/hcp/index.html , and for children AAP (American Academy of Pediatrics) https://www.aappublications.org/cc/covid-19 ) and should comment on quality of data and provide strategies and crisis standards to guide clinical practice.

Long-term, lessons learned from research during this pandemic could benefit the research enterprise worldwide beyond the pandemic and during other PHE/disasters with strategies for balancing multiple novel approaches and high-quality, time-efficient, cost-effective research. This challenge, at least in part, can be met by appropriate study design, collaboration, patient registries, automated data collection, artificial intelligence, data sharing, and ongoing consideration of appropriate regulatory approval processes. In addition, research to develop and evaluate innovative strategies and technologies to improve access to care, management of health and disease, and quality, safety, and cost effectiveness of care could revolutionize healthcare and healthcare systems. During PHE/disasters, crisis standards for research should be considered along with ongoing and just-in-time PHE/disaster training for researchers willing to share information that could be leveraged at time of crisis. A dedicated funded core workforce of PHE/disaster researchers and funded infrastructure should be considered, potentially as a consortium of networks, that includes physician-scientists, basic scientists, social scientists, mental health providers, global health experts, epidemiologists, public health experts, engineers, information technology experts, economists and educators to strategize, consult, review, monitor, interpret studies, guide appropriate clinical use of data, and inform decisions regarding effective use of resources for PHE/disaster research.

Differences between adult and pediatric COVID-19, the need for pediatric research

As reported by the CDC, from February 12 to April 2, 2020, of 149,760 cases of confirmed COVID-19 in the United States, 2572 (1.7%) were children aged <18 years, similar to published rates in China. 9 Severe illness has been rare. Of 749 children for whom hospitalization data is available, 147 (20%) required hospitalization (5.7% of total children), and 15 of 147 required ICU care (2.0%, 0.58% of total). Of the 95 children aged <1 year, 59 (62%) were hospitalized, and 5 (5.3%) required ICU admission. Among children there were three deaths. Despite children being relatively spared by COVID-19, spread of disease by children, and consequences for their health and pediatric healthcare are potentially profound with immediate and long-term impact on all of society.

We have long been aware of the importance and value of pediatric research on children, and society. COVID-19 is no exception and highlights the imperative need for a pediatrician-scientist workforce. Understanding differences in epidemiology, susceptibility, manifestations, and treatment of COVID-19 in children can provide insights into this pathogen, pathogen–host interactions, pathophysiology, and host response for the entire population. Pediatric clinical registries of COVID-infected, COVID-exposed children can provide data and specimens for immediate and long-term research. Of the 1133 COVID-19 studies on ClinicalTrials.gov, 202 include children aged ≤17 years. Sixty-one of the 681 interventional trials include children. With less diagnostic testing and less pediatric research, we not only endanger children, but also adults by not identifying infected children and limiting spread by children.

Pediatric considerations and challenges related to treatment and vaccine research for COVID-19 include appropriate dosing, pediatric formulation, and pediatric specific short- and long-term effectiveness and safety. Typically, initial clinical trials exclude children until safety has been established in adults. But with time of the essence, deferring pediatric research risks the health of children, particularly those with special needs. Considerations specific to pregnant women, fetuses, and neonates must also be addressed. Childhood mental health in this demographic, already struggling with a mental health pandemic prior to COVID-19, is now further challenged by social disruption, food and housing insecurity, loss of loved ones, isolation from friends and family, and exposure to an infodemic of pandemic-related information. Interestingly, at present mental health visits along with all visits to pediatric emergency departments across the United States are dramatically decreased. Understanding factors that mitigate and worsen psychiatric symptoms should be a focus of research, and ideally will result in strategies for prevention and management in the long term, including beyond this pandemic. Social well-being of children must also be studied. Experts note that the pandemic is a perfect storm for child maltreatment given that vulnerable families are now socially isolated, facing unemployment, and stressed, and that children are not under the watch of mandated reporters in schools, daycare, and primary care. 10 Many states have observed a decrease in child abuse reports and an increase in severity of emergency department abuse cases. In the short term and long term, it will be important to study the impact of access to care, missed care, and disrupted education during COVID-19 on physical and cognitive development.

Training and supporting pediatrician-scientists, such as through NIH physician-scientist research training and career development programs ( https://researchtraining.nih.gov/infographics/physician-scientist ) at all stages of career, as well as fostering research for fellows, residents, and medical students willing to dedicate their research career to, or at least understand implications of their research for, PHE/disasters is important for having an ongoing, as well as a just-in-time surge pediatric-focused PHE/disaster workforce. In addition to including pediatric experts in collaborations and consortiums with broader population focus, consideration should be given to pediatric-focused multi-institutional, academic, industry, and/or government consortiums with infrastructure and ongoing funding for virtual training programs, research teams, and multidisciplinary oversight.

The impact of the COVID-19 pandemic on research and research in response to the pandemic once again highlights the importance of research, challenges of research particularly during PHE/disasters, and opportunities and resources for making research more efficient and cost effective. New paradigms and models for research will hopefully emerge from this pandemic. The importance of building sustained PHE/disaster research infrastructure and a research workforce that includes training and funding for pediatrician-scientists and integrates the pediatrician research workforce into high-quality research across demographics, supports the pediatrician-scientist workforce and pipeline, and benefits society.

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Department of Pediatrics, Division of Emergency Medicine, Boston Children’s Hospital, Boston, MA, USA

Debra L. Weiner

Harvard Medical School, Boston, MA, USA

Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

Vivek Balasubramaniam

Department of Pediatrics and Division of Neonatology, Maria Fareri Children’s Hospital at Westchester Medical Center, New York Medical College, Valhalla, NY, USA

Shetal I. Shah

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Joyce R. Javier

Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

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All authors made substantial contributions to conception and design, data acquisition and interpretation, drafting the manuscript, and providing critical revisions. All authors approve this final version of the manuscript.

Pediatric Policy Council

Scott C. Denne, MD, Chair, Pediatric Policy Council; Mona Patel, MD, Representative to the PPC from the Academic Pediatric Association; Jean L. Raphael, MD, MPH, Representative to the PPC from the Academic Pediatric Association; Jonathan Davis, MD, Representative to the PPC from the American Pediatric Society; DeWayne Pursley, MD, MPH, Representative to the PPC from the American Pediatric Society; Tina Cheng, MD, MPH, Representative to the PPC from the Association of Medical School Pediatric Department Chairs; Michael Artman, MD, Representative to the PPC from the Association of Medical School Pediatric Department Chairs; Shetal Shah, MD, Representative to the PPC from the Society for Pediatric Research; Joyce Javier, MD, MPH, MS, Representative to the PPC from the Society for Pediatric Research.

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Weiner, D.L., Balasubramaniam, V., Shah, S.I. et al. COVID-19 impact on research, lessons learned from COVID-19 research, implications for pediatric research. Pediatr Res 88 , 148–150 (2020). https://doi.org/10.1038/s41390-020-1006-3

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Informing evidence-based policy during the COVID-19 pandemic and recovery period: learning from a national evidence centre

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The COVID-19 pandemic demonstrated the vital need for research to inform policy decision-making and save lives. The Wales COVID-19 Evidence Centre (WCEC) was established in March 2021 and funded for two years, to make evidence about the impact of the pandemic and ongoing research priorities for Wales available and actionable to policy decision-makers, service leads and the public.

We describe the approaches we developed and our experiences, challenges and future vision.

Program implementation

The centre operated with a core team, including a public partnership group, and six experienced research groups as collaborating partners. Our rapid evidence delivery process had five stages: 1. Stakeholder engagement (continued throughout all stages); 2. Research question prioritisation; 3. Bespoke rapid evidence review methodology in a phased approach; 4. Rapid primary research; and 5. Knowledge Mobilisation to ensure the evidence was available for decision-makers.

Main achievements

Between March 2021–23 we engaged with 44 stakeholder groups, completed 35 Rapid Evidence Reviews, six Rapid Evidence Maps and 10 Rapid Evidence Summaries. We completed four primary research studies, with three published in peer reviewed journals, and seven ongoing. Our evidence informed policy decision-making and was cited in 19 Welsh Government papers. These included pandemic infection control measures, the Action Plan to tackle gender inequalities, and Education Renew and Reform policy. We conducted 24 Welsh Government evidence briefings and three public facing symposia.

Policy implications

Strong engagement with stakeholder groups, a phased rapid evidence review approach, and primary research to address key gaps in current knowledge enabled high-quality efficient, evidence outputs to be delivered to help inform Welsh policy decision-making during the pandemic. We learn from these processes to continue to deliver evidence from March 2023 as the Health and Care Research Wales Evidence Centre, with a broader remit of health and social care, to help inform policy and practice decisions during the recovery phase and beyond.

The COVID-19 pandemic showed the vital role research plays in informing policy and practice decisions to save lives [ 1 ]. Research was also needed to inform best strategies for managing direct and indirect harms of the pandemic, including increased surgical waiting lists and exacerbating inequalities [ 2 , 3 , 4 , 5 ]. However, traditional systematic literature reviews often take several years to complete and the academic journal publication process can be protracted with articles not always written in ways that make clear and practical recommendations. Sir Chris Whitty, the Chief Medical Officer for England during the pandemic, noted, ‘academics underestimate the speed of the policy process and publish excellent papers after a policy decision rather than good ones before it … the accurate synthesis of existing information is the most important offering by academics to the policy process [ 6 ].

The Wales COVID-19 Evidence Centre (WCEC), [ 7 , 8 ] was established in March 2021 and funded for two years, to join the global effort to co-ordinate COVID-19 related research, and to address the lag between policy needs arising and available evidence [ 9 ]. We needed to: understand the impact of the pandemic on research priorities for the health and wider needs of people and communities in Wales; quickly and rigorously provide relevant evidence; and make this evidence available and actionable to our stakeholders involved in policy-making and delivery of health and social care. We describe the novel approaches we developed to meet these objectives. We also discuss our experiences, challenges and learning to inform our future vision as we transition to become the Health and Care Research Wales Evidence Centre from March 2023.

Our rapid evidence delivery processes are outlined in Fig.  1 and discussed below in more detail. These included: 1) stakeholder engagement throughout all processes [ 10 , 11 ]; 2) research question identification and prioritisation [ 10 ]; 3) bespoke phased rapid evidence review methodology [ 12 ]; 4) rapid primary research [ 13 , 14 , 15 ]; and 5) knowledge mobilisation [ 16 ].

Wales COVID-19 Evidence Centre (WCEC) rapid evidence delivery processes

Organisational structure

The WCEC operated with a core team and six Collaborating Partner research groups (Table  1 ). The core team included a Director (AE) and leads for, research identification and prioritisation and public involvement and engagement (NJW), stakeholder involvement (AC), rapid evidence synthesis (RL), rapid primary research methods (DW), and knowledge mobilisation (MG), with managerial support (AW, JG). During the pandemic, we worked closely with members of Welsh Government’s Technical Advisory Cell (RJL) who had a boundary spanning role to promote communication between the evidence centre and policy-makers; the role continues as the Welsh Government undergoes post-pandemic reorganisation.

The core team worked closely with a Public Partnership Group, consisting of eight members [ 11 ]. Established in March 2022 following open recruitment through Health and Care Research Wales, these individuals represented the views of the public with regards to COVID-19 research and were involved in all stages of our evidence synthesis work. They wrote lay summaries to accompany our evidence reports and co-authored our publications (AS). Additional public partners were sought specifically (through open recruitment via Health and Care Research Wales) based on the primary research topic focus [ 11 ].

The six Collaborating Partner research groups are independent Welsh research teams based in Universities or the NHS, each with their own areas of domain and methodology expertise on which to draw, depending on the research question (Table  1 ). A fortnightly methodology subgroup meeting included representation from all Collaborating Partner review teams for shared learning and iteration of processes. We also liaised with other national and international research partners (e.g. International Public Policy Observatory, National Institute of Clinical Excellence (NICE), UK Health Security Agency) to avoid duplication of effort and ensure complementary analyses.

Rapid evidence delivery process

• Stakeholder engagement

Stakeholder engagement and collaboration was integral throughout our processes to ensure that we delivered research evidence that was timely, of the highest priority, and directly relevant to policy and practice [ 10 ]. Important COVID-19-related research questions were invited from various health and social care stakeholder groups during several rounds of the Stakeholder Research Question Prioritisation Exercise (ScoPE) process (described in Section 2 below). Key stakeholders were identified through an inclusive stakeholder mapping exercise and included the public, policy leads, health, education, and social care service delivery organisations and professionals [ 10 , 11 ]. Further public engagement was sought via public facing symposium events in March 2021 and March 2022. We also conducted focus groups with communities that were disproportionately impacted by the pandemic to facilitate engagement, identify their priority questions and promote equity. This included black and ethnic minority groups, children and young people, housing association tenants, and disabled people [ 10 , 11 ].

When a proposed question was adopted onto our work program, the relevant stakeholders ( n  = 2–3) and at least one public member were invited to join a series of online stakeholder meetings (usually three) with the lead Collaborating Partner research team to clarify the research question, identify the evidence need and the urgency, discuss early findings, contribute their expertise and knowledge of key articles / research, and become involved in dissemination of findings.

Research question identification and prioritisation

Our prioritisation process aimed to identify and select research questions that were of highest priority for COVID-19 focused health and social care policy and practice in Wales, [ 10 , 11 ] in a situation where time did not allow for recognised formal prioritisation exercises such as James Lind [ 17 ]. Priority questions were invited through a bespoke, demand-driven Stakeholder Research Question Prioritisation Exercise (ScoPE) process via direct stakeholder consultation both within Welsh Government, and with external NHS, social care, professional, public, academic, industry and third sector groups [ 10 ]. The ScoPE process was formally conducted every six months, but was also reactive to accommodate emerging or urgent health, social care, or education research priorities needed to inform decision-making.

During the ScoPE exercise, stakeholder groups were invited to complete a proforma (please see supporting information 1) that ranked their ‘top research priorities’ (up to 10). Additional information requested included: relevance to the current or future COVID-19 context in Wales, importance of the evidence gap, potential benefits and for translation into practice, and urgency for the evidence. Submitted research questions were assessed against these criteria by the WCEC core team and public representatives for acceptance onto the work program. If necessary, further expert stakeholder advice was sought to clarify priorities and refine the research question. For efficiency, there was initial consideration of question overlap with work already undertaken or in progress (both within the Centre and externally), and whether evidence synthesis or primary research was needed. The work program was shared and discussed with Welsh Government representatives. Approved questions were then allocated to either the Evidence Synthesis Work Program or the Primary Research Work Program (see Sections 3 and 4 below).

Evidence synthesis work program

Research questions accepted onto the work program for evidence synthesis were allocated to one of our partner groups, with questions matched to experience within the group where possible. Our phased rapid review approach, [ 12 ] based on three types of products, was developed in line with international rapid review approaches to ensure we conducted and delivered robust, timely and efficient and effective evidence syntheses, [ 18 , 19 , 20 , 21 , 22 ] which also benefited from experience within the partner research groups [ 23 , 24 , 25 ].

Phase I: Rapid evidence summary (~ 1 week)

An initial introductory stakeholder meeting was set up, which included members from the WCEC core team and public representatives, the partner research group and key stakeholders. The meeting was held online and lasted about an hour. The aim was to clarify with the stakeholders the focus of the research question, how the evidence would be used, and proposed timelines.

The review team then conducted an exploratory review of key COVID-19 resources for existing reviews that may address the research question. A list of key resources was developed with information scientists to support the searches (see Supporting Information 2). This initial phase allowed the reviewers to familiarise themselves with the topic area, check the research question had not been addressed by another group and identify the likely extent and type of available evidence to inform the methods and design of the rapid review.

The output from this phase, based on abstracts and generally completed within a week, was presented as an annotated bibliography with key findings, called a Rapid Evidence Summary (RES), and discussed in a second online stakeholder meeting. This also provided the opportunity to present limited interim findings to stakeholders. If a relevant and current systematic review was identified that addressed the research question, then it could be summarised and appraised as a final product. For urgent decisions or where there was insufficient evidence to progress to a rapid review, the RES was published as the final product.

Phase II: Rapid review (1–2 months)

If sufficient evidence was identified in the RES, discussions during the second stakeholder meeting moved onto planning the Rapid Review (RR). This involved refining the research question and drafting the eligibility criteria (based on an evidence synthesis framework such as ‘PICO’) [ 26 ]. These discussions were also used to establish if there were particular equality considerations, and the potential economic impact of the evidence.

The rapid review was conducted using a variation of the systematic review approach, where components of the review process were abbreviated or omitted to generate the evidence to inform stakeholders within a short time frame whilst maintaining attention to bias. This offered the most rigorous and comprehensive product produced in a timely manner. As far as possible, the reviews followed methodological recommendations and minimum standards for conducting rapid reviews [ 18 , 19 , 20 , 21 , 22 ]. If timelines were tight, methodological decisions needed to be pragmatic. Approaches were described for transparency and included: a tertiary review (review of reviews), prioritising identified reviews for synthesis, and limiting searches for primary studies to countries with similar health and social care systems to the UK. When a focused review question could not be selected, an interim Rapid Evidence Map (REM) was conducted to support the selection of a substantive focus for the rapid review. The REM used abbreviated systematic mapping or scoping review methodology [ 27 , 28 ]. The output from this phase was a rapid review report (template in Supporting Information 2) which was presented and discussed in a third online stakeholder meeting.

Primary research work program

This additional work program was set up in March 2022. Fig.  2 (an elaboration of process 4 in Fig.  1 ) outlines the topic identification, assessment, review and allocation processes, again designed to promote efficiency and effectiveness, and described below. Primary research projects were identified through three main routes: key gaps identified by WCEC evidence synthesis outputs; the ScoPE process (see Section 2) [ 10 ]; and though applications submitted by research groups. All questions identified via these three routes were subject to assessment against the ScoPE process described above and following criteria:

Addressed the pandemic challenges (including recovery) in the context of Wales AND

Built on research already undertaken in Wales and with further unanswered questions OR

Utilised particular Welsh expertise for innovative work on COVID-19 illness, impacts & recovery OR

Was a high priority question, with clear policy implications for the context of Wales.

Wales COVID-19 Evidence Centre (WCEC) Primary Research Work Program topic identification, assessment, review, and allocation processes

All primary research needed to be deliverable in about 6 months, not be more suitable for alternative funding streams, and offer value for money and potential for impact. If criteria were met, researchers were invited to complete a full application form, which included further details regarding methods, pathway to impact and costings. Once received, the full application underwent peer review by one internal reviewer, one external reviewer (with topic / methodological expertise) and two public members. A grant funding panel met to discuss the applications, and successful projects received funding for the work.

We also had core team capacity and expertise to support a range of ‘in-house’ rapid primary research projects. Where the in-house team did not have the relevant specialist expertise, we commissioned appropriate Collaborating or external partners to conduct the work. For in-house and commissioned research, a similar process to the evidence synthesis program was used: three online meetings with the key stakeholders to clarify the research question, identify appropriate methods and analysis, provide expertise in the research process, and assist with knowledge mobilisation and the pathway to impact.

Knowledge mobilisation and impact

Our knowledge mobilisation processes were designed to ensure our products were accessible, timely and useful for our stakeholders to inform policy, practice and decision-making to promote effectivenss [ 16 ]. The process was iterative and tailored to meet the requirements of the stakeholders. The third online stakeholder meeting was used to present the findings from the evidence synthesis or primary research, address any queries, and support the development of a knowledge mobilisation plan, co-designed with the proposing stakeholders.

The templates for our rapid review final reports (Supporting Information 2) were based on recommendations for reporting evidence reviews for policy-makers and have been adapted for our primary research reporting [ 29 ]. For each report, a 'topline summary’ was developed highlighting the methodology, evidence base, research quality, key findings and implications for policy and practice. The report’s findings were also re-drafted into a lay summary by our public representatives to provide a widely accessible version, published alongside other outputs including infographics. Reports were published on pre-print servers and linked to the lay summaries on our WCEC website library.

Activities to promote the uptake and use of the evidence included fortnightly internal Welsh Government evidence briefings, where research findings were presented to a wider Welsh Government audience and invited key stakeholders. Here, implications of the evidence and practical next steps towards implementation were also discussed. A communication plan was in place, and we used social media through Health and Care Research Wales to disseminate findings including infographics and links to our review outputs and newsletters. We also recorded and tracked the impact of our work via ongoing engagement with stakeholders and an online survey. Our reports were made publicly available on our website, which was also linked to other COVID evidence resources (‘UK Health Security Agency- COVID Rapid Review Collections’ and internationally with COVID-END) [ 20 , 30 ].

During the two years the centre was operational (March 2021–23), we reached out to 52 stakeholder groups across policy, health, social care, education, third sector and the public; 44 (85%) submitted COVID-19 related research questions [ 8 , 10 , 11 ]. During this time, 22 key stakeholders completed our survey to provide feedback on our processes and additional feedback was collected via meetings. Survey feedback showed that 21/22 (95%) were satisfied or very satisfied with our engagement processes, meetings and the final report; 100% trusted the report findings.

‘The WCEC representatives involved with the project were highly responsive. Their suggestions were constructive, and they worked proactively to make meaningful progress that allowed our WG (Welsh Government) project team to quickly and conveniently locate relevant evidence that helped shape our policy proposals’.(WG Stakeholder)

The eight members of the public in our Public Partnership Group were involved in a number of activities. These included: prioritising research questions for our work program, contributing to evidence reviews and engagement events, writing lay summaries and contributing to our newsletter and supporting the write-up of four publications for peer reviewed journals. They have also peer-reviewed research applications submitted for the primary research work program and attended Grant Funding Panels as panel members [ 11 ].

Research Question identification and prioritisation

Three cycles of the ScoPE exercise were conducted (Spring 2021, Autumn 2021, Spring 2022). A total of 44 ScoPE forms were completed across the three cycles, with a total of 212 questions proposed via this route. We also received an additional 11 urgent Welsh Government requests [ 10 ]. Four focus groups were conducted with disproportionately affected groups between April and May 2022 to establish their ‘Top 10 research priorities’: children and young people (including representatives from the Centre for Development, Evaluation, Complexity and Implementation in Public Health Improvement’s ALPHA Group, Children’s Commissioner for Wales, Wolfson Centre), Disability Wales, Ethnic Minorities and Youth Support Team (EYST) Wales, and a local community housing group (Taff Housing, Cardiff) [ 11 ]. They proposed a total of 40 priority areas for research.

Attendees at the public facing WCEC symposium in March 2022 identified 57 priority areas (discussed during breakout rooms) which were ranked by participants following the event to establish their top 10 priorities to help inform our work program. After combining duplicate/similar themes/questions, a total of 58 questions were included in our work program [ 7 , 8 ]. (This was reviewed every 3 months to ensure the questions still had relevance and clear pathways to impact.)

Rapid evidence synthesis work program

Our evidence synthesis outputs conducted by our partner research groups (March 2021–23) included: 35 Rapid Reviews, six Rapid Evidence Maps and 10 Rapid Evidence Summaries [ 8 ]. Topics largely included education, inequalities, health and social care, for example, the effectiveness of innovations to address NHS surgical waiting lists and innovations to improve recruitment and retention of health and social care staff (Table  2 ).

‘Excellent process for defining questions, setting boundaries for research, discussing key findings.’ (Stakeholder feedback on the review process)

The WCEC core team also supported medical students at Cardiff University to conduct systematic reviews on: whether institutional racism contributed to adverse COVID-19 outcomes for ethnic minority healthcare staff; the effectiveness of antiracist interventions in healthcare; and the impact of the pandemic on homeless and prison populations. A living review exploring the risk of transmission of Sars-CoV-2 in vaccinated populations was conducted in collaboration with the UK Health Security Agency. An additional review team, The Biocomposites Centre, Bangor University, was commissioned to conduct a single review about the impact of the pandemic and changes in working practice on the environment, particularly greenhouse gas emissions. Several reviews over the pandemic highlighted evidence gaps and areas for further primary research, which were highlighted to funders.

Eleven studies were adopted onto our primary research work program (Table  3 ). Three grants were awarded to COVID-19 research teams; most studies were conducted ‘in-house’ or by our Collaborating Partner research teams. One study that required the research to be conducted through the medium of Welsh was commissioned to an external research group with appropriate expertise. Three of our completed primary studies were published in peer reviewed journals including the impact of the pandemic on cancer diagnosis in Wales, [ 13 ] and the diagnosis of 17 long term conditions including asthma, heart disease and diabetes [ 14 ]. Another cohort study showed that higher-risk adult community patients with COVID-19 in Wales treated with anti-viral therapy had a reduced the risk of hospitalisation or death [ 15 ] .

Our work program, 53 reports (including 26 lay summaries in English and Welsh written by public members) and three Newsletters were published as open access via our website library [ 7 , 8 ]. We conducted 24 fortnightly Welsh Government evidence briefings (usual attendance 20–30 people) and findings were also presented to wider groups. For example, our healthcare education report was presented to UK heads of medical education; Long-Covid work was presented to the Senedd cross-party on Long-COVID; and the vaccination in pregnancy findings were presented to the heads of maternity in Wales. We held three public facing symposia (70–80 attendees) to help disseminate outputs and generate discussion on impacts and evidence gaps opened with presentations by senior Welsh Government Ministers or policy officials. The symposia presented findings from themes of work including: education and young people (Dec 2021), impact of the evidence centre (Mar 2022), and inequalities and vulnerable gorups (Sept 2022) [ 7 , 8 , 16 ].

‘The Symposium was very encouraging… in bringing academics and Welsh Government together to produce evidence-based policy and practice… also pleasing to hear that patient and public experience is at the heart of the Centre.’ Chair of the SUPER Group, public contributors who support research activities at PRIME Centre Wales

Our reports informed policy decision-making, with 19 of our reports referenced in Welsh Government papers (Table  2 ). Examples include: rapid reviews of face coverings to inform the move to Alert level 0 (August 2021); infection control measures in schools to inform schools’ re-opening in Sept 2021; disinfection methods in schools regarding ozone/CO 2 monitors in October 2021; vaccination for pregnant women (Public Health Wales campaign to women and midwives, Nov 2021); the Action Plan to tackle gender inequalities (Jan 2022); impact of COVID-19 on greenhouse gas emissions (June 2022); and 16–19 Education into Renew & Reform policy. One review directly led to re-profiling of £3 million funding towards provision of CO 2 monitors for schools across Wales [ 31 ].

In addition to publication on our website library, final reports were published on pre-print servers including medRxiv. This enabled wider sharing and the collection of metrics. For example, the abstract of a rapid review on the effectiveness of interventions and innovations relevant to the Welsh NHS context to support recruitment and retention of clinical staff, [ 32 ] was viewed 671 times, and the pdf was downloaded 181 times in the first 3 months. While some evidence was not directly included in Welsh Government papers, feedback from stakeholders indicated that information confirmed their knowledge and was useful:

‘The rapid evidence review highlighted that a multi-strategy approach was required. This reinforced the approach that was being taken and ensured that our practice was supported by the evidence available at that time.’ (Stakeholder feedback)

Key outputs

In two years of operation (March 2021–23), the WCEC engaged with 44 stakeholder groups across policy, health, social care, education, third sector and the public. Evidence synthesis outputs included: 35 Rapid Reviews, six Rapid Evidence Maps and 10 Rapid Evidence Summaries [ 8 ]. We completed four primary research studies, three published in peer-reviewed journals, and seven ongoing [ 13 , 14 , 15 ]. Our evidence informed policy decision-making and was cited in 19 Welsh Government papers. We conducted 24 Welsh Government evidence briefings, three public facing symposia and received positive feedback from stakeholders on our review process and timely accessible products [ 8 , 16 ].

Strengths and limitations

Our strengths include setting up the evidence centre and collaboration with the Welsh research groups in a short timeframe to assist the pandemic effort; also strong stakeholder engagement to ensure the correct questions were being asked and the evidence contributed to decisions. Our phased rapid review approach to identify existing work and publication of our work program on our website for global transparency avoided duplication of effort with other research groups, a problem recognised during the pandemic [ 33 ]. Incorporating the primary research work program to address evidence gaps identified from the evidence synthesis work is novel. Our demand driven approach used rapid methods to deliver evidence to meet the needs and timeframes of our stakeholder decision-makers. We developed various products to distil the evidence and improve impact. We recruited a public group because we can only ‘learn to live’ with COVID by learning from those who have lived through it. We encouraged student involvement, giving them an opportunity to learn about our processes and take on questions that require a longer timeframe with more rigorous methods (systematic reviews). We actively engaged with other research groups to avoid duplication and encouraged collaboration across different NHS, policy and academia groups.

Our short timeframes were a limitation, requiring modification to the systematic review process, such as one reviewer extracting data or conducting a quality assessment. Risks of error were mitigated through strong stakeholder engagement—identifying key papers and discussing and querying findings, also being transparent about the limitations of the analyses and syntheses. Challenges included meeting stakeholder expectation about what evidence can be delivered in a short time period and understanding limitations and quality of the available evidence. We mitigated this through discussion in the stakeholder meetings and ongoing email communication. Setting up online stakeholder meetings with representatives from all groups in short time frames with different timescales to traditional research projects was also a challenge, email communication was again used if stakeholders were unable to make a meeting. Specific primary research challenges included timely ethical approval, participant recruitment and ensuring Welsh language requirements were met. We plan to publish papers on each of the individual processes (prioritisation, rapid reviews, rapid primary synthesis and knowledge mobilisation) to describe this learning at each stage in more detail [ 10 , 11 , 12 , 16 ].

Comparison with other approaches

The COVID-19 pandemic highlighted the need for research evidence and its value in informing policy decisions, with the mantra of ‘Following the Science’ becoming common place. However, scientists may find themselves crossing boundaries and taking on public figure roles to which they are unaccustomed [ 34 ]. Pielke describes four idealised roles for scientists in decision-making: the pure scientist with no connection with how the evidence is understood and interpreted by Government Officials; the issue advocate who focusses on the implications of research for a particular political agenda; the science arbiter that responds to specific scientific questions raised by decision-makers; and the honest broker who seeks to integrate scientific knowledge with stakeholder concerns in the form of alternative possible courses of action [ 35 ]. Our rapid evidence reviews reflect the science arbiter role, focusing on a narrow research question to enable the review to be completed in a timely manner. However, by highlighting evidence gaps and addressing some of these in our primary research work program, the centre may be considered as an honest broker role—providing research relevant to the Welsh context and evidence for alternative options.

How the evidence is understood and interpreted by Government Officials, including politicians and policy-makers, and service leads, is also a challenge. Research-policy engagement initiatives can take many forms, most aiming to improve research dissemination or create relationships, but often not evaluated [ 36 , 37 , 38 ]. We have used strategies such as communication with stakeholders to tailor the research accordingly and short, concise and freely available reports in plain language to help at this interface. However, there is currently a lack of evidence regarding how to enhance the “evidence literacy” of policy decision-makers and “policy literacy” of scientists to enable a culture or environment to facilitate their collaboration and deliver both timely policy-driven evidence synthesis and evidence-based policy-making [ 39 ]. Our learning includes: engaging with stakeholders and public partners that will use the evidence; delivering an evidence product in time to help with decision-making; being clear about data quality and potential limitations of the evidence; sharing work programs to avoid duplication of effort with other research groups; and planning knowledge mobilisation strategies and the most useful outputs with stakeholders from the start [ 8 ]. These lessons learned are helpful as we transition to the Health and Care Research Wales Evidence Centre (March 2023), [ 40 ] and may be transferable to other evidence centres.

Further research

Further research is needed to understand and evaluate how to facilitate knowledge transfer at the Science-Policy-Practice-Interface and to evaluate the long term effectiveness and impact of evidence centres or similar units.

Conclusions

Strong engagement with stakeholder groups, a phased rapid evidence review approach, and primary research to address key gaps in current knowledge have enabled high-quality, efficient evidence outputs to be delivered, to effectively help inform Welsh policy decision-making during the pandemic. We learn from these processes to continue to deliver evidence to help inform policy and practice decisions in the post-pandemic recovery phase as the Health and Care Research Wales Evidence Centre.

Availability of data and materials

Not applicable.

Abbreviations

Bangor Institute for Health and Medical Research

Health and Care Research Wales

Health Technology Wales

Knowledge Mobilisation

Public Health Wales Evidence Service

Public Partnership Group

Rapid Evidence Summary

Rapid Evidence Map

Rapid Review

Welsh Secure Anonymised Information Linkage Databank

Science Policy Practice Interface

Stakeholder Research Question Prioritisation Exercise

Specialist Unit for Review Evidence

Welsh Government’s Technical Advisory Cell

Wales COVID-19 Evidence Centre

Wales Centre for Evidence Based Care

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Acknowledgements

We would like to thank our stakeholders and collaborative partner groups: Bangor Institute for Health and Medical Research, Health Technology Wales, Public Health Wales Evidence Service, Specialist Unit for Review Evidence, Population Data Science team, Swansea University, Wales Centre for Evidence Based Care. We would like to thank Emma Small, Natasha Hulley, Emma Jones, Helen Freegard, Erin Wynands and Abubaker Sha’aban for their contributions.

The WCEC was funded by Health and Care Research Wales through Welsh Government.

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Alison Cooper, Ruth Lewis, Micaela Gal, Natalie Joseph-Williams, Jane Greenwell, Angela Watkins, Denitza Williams, Elizabeth Doe & Adrian Edwards

Division of Population Medicine, Cardiff University, Cardiff, Wales

Alison Cooper, Micaela Gal, Natalie Joseph-Williams, Jane Greenwell, Angela Watkins, Denitza Williams, Elizabeth Doe & Adrian Edwards

North Wales Centre for Primary Care Research, Bangor University, Bangor, Wales

Public Contributor, WCEC Public Partnership Group, Bangor, Wales

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Technical Advisory Cell, Welsh Government, Cardiff, Wales

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AC led the writing of this manuscript, and all authors read and approved the final version. RL led the rapid evidence synthesis methods supported by AC; MG led the knowledge mobilisation processes; NJW led the research question prioritisation process; JG and AW led centre management; liaison with public contributors and communication strategy; DW led the primary research work program supported by NJW; RJL had a boundary spanning role with Welsh Government; AS provided public contribution and AE was Director of WCEC.

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Correspondence to Alison Cooper .

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Cooper, A., Lewis, R., Gal, M. et al. Informing evidence-based policy during the COVID-19 pandemic and recovery period: learning from a national evidence centre. glob health res policy 9 , 18 (2024). https://doi.org/10.1186/s41256-024-00354-1

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COVID-19 pandemic left its mark on academics. Are students caught up from learning loss?

T he academic impact of the COVID-19 pandemic continues to be felt on the Treasure Coast, years after students returned to the classrooms without masks or quarantines.

During the months of distance learning and continual interruptions from quarantines, educators were concerned students would fall behind academically and take years to get back on track. While some school districts say students now have caught up in math and reading, others say students continue to struggle, just as federal money targeted for tutoring and intensive summer recovering programs is set to end this fall.

"Overall, we are still seeing the lingering effects on students, especially in key grades," said St. Lucie County schools Deputy Superintendent Helen Wild.

Still, not all students are behind. In 2023, Indian River County students scored higher on state standardized tests than they did pre-pandemic in 2019, Superintendent David Moore said.

"The district has moved on from the pandemic. It's one of four in the state that is actually in a better place today than it was before the pandemic," Moore said.

"We've done a lot of work to offset the effects of the pandemic," Moore said.

Treasure Coast reading, math scores improve in areas, but educators say more work is needed

The pandemic's impact on learning continues to be a national concern, long after the pandemic has ended. A 2023 Northwest Evaluation Association study showed that while students have made learning gains, student achievement still is behind pre-pandemic performance.

Students would need an additional 4½ months of math instruction and 4.1 additional months in reading to fully recover, according to the not-for-profit organization's national study. The organization studied 6.7 million students in grades 3-8, comparing pre-pandemic national test scores between the 2016 and 2019 school years to scores during the pandemic school years of 2020-2023.

Florida scores weren't included in the study because of incompatible software.

"We're starting to see some pretty sizable gaps," said Megan Kuhfeld, director of growth marketing and analytics for the Northwest Evaluation Association. Some gaps began closing in the spring of 2023, but "for the most part, students have not caught up."

Of concern nationally were the 2023-2024 eighth graders, the study said. These students would need 9.1 additional months of learning in math and 7.4 months of additional learning in reading to get back to grade level, the study said.

"In other words, when these students enter their freshman year of high school, they will need to accomplish almost five years of learning during their four years of high school," the study said. An updated study, using 2024 test scores, is expected this summer.

St. Lucie's fourth graders — who were in first grade at the start of the pandemic — struggled in reading, Wild said. They were learning letter sounds and phonics when schools went remote, she said, and learning these skills online is difficult. When students returned, they and their teachers were wearing masks, impeding their progress further, she said.

"These are critical years when you are learning how to read," according to Wild.

Seventh graders — who were in third grade when schools shut down — also are behind in reading for the same reasons, Wild said. Then-third graders were making the transition from learning to read to learning to comprehend, something that is challenging with remote learning, she said.

Indian River County students were impacted in math, Moore said.

"You look at math as rungs on a ladder," Moore said. When students missed some of the sequential components, it impacted their skills. "It really made it challenging."

The district had to make sure students had the tools they needed to get back on track, he said.

St. Lucie schools provided students with intensive reading and phonics instruction as well as intervention after school and during the summer, Wild said. Students have the challenge of trying to keep pace with their current grade material while trying to get caught up, she said.

This year, as in previous years since the pandemic, St. Lucie schools offers free intensive summer learning programs that help students catch up while providing fun hands-on activities in science, math and technology STEM activities. Transportation and meals are provided at no cost, Wild said.

St. Lucie will put greater focus on math achievement in order to improve district's ranking

High school graduation rates here exceed Florida state average despite COVID-19 pandemic

While the summer programs have been successful, this year is the last opportunity students have to catch up on their learning loss. The federal COVID-relief money is ending, which means an end to the fully intensive summer program, she said.

"It's always tough when a major funding source sunsets. We knew this was temporary," Wild explained. The district plans to continue offering a summer program, as it did before the pandemic, but on a smaller scale, she said.

Overall, students are showing more promising recovery, said Kuhfeld.

Districts such as Indian River County dislike talking about the pandemic and focusing on learning loss. The district is moving forward, Moore said.

"We have moved beyond the pandemic," Moore stressed. "We do not use it as an excuse."

The Indian River County district had an aggressive plan to return students early, with restrictions such as mandatory mask policies and quarantines, Moore said. Teachers received training on interventions to help students improve, he said. Instruction was drastically different, as education plans were very individualized to meet the needs of the students, he said.

Intensive programs were implemented to raise the bar academically, Moore said.

"We had to make sure they were getting what they needed," he said.

This year, Indian River was the only Treasure Coast school district to receive an "A" grade from the state. Unlike prior years, learning gains were not considered in the grading formula because the state changed standardized tests and required a baseline year.

Indian River school district gets an A in state rankings; St. Lucie, Martin score B grades

In Martin County, school officials implemented proper accommodations, access and interventions to help bridge any performance gaps, Troy LaBarbara, Martin County schools' assistant superintendent of academics, said in a statement.

"The impact of the pandemic on academic performance varies widely among students. Overall, most of our students have closed the achievement gap caused by the pandemic," LaBarbara said in the statement. "Some students are still struggling with factors like access to resources, support systems and individual circumstances."

Third graders, who were in kindergarten when the pandemic struck, follow a statewide decline in math and reading, LaBarbara said.

"To continue to address this, we have infused a strong multitiered process in our core academic areas.  Summer school interventions will include personalized learning plans tailored to address individual areas of weakness, small-group instruction focusing on essential skills, targeted tutoring sessions and enrichment programs to engage students in accelerated areas," the statement said.

Beyond academics, local school districts had to reteach students the importance of attending school and, in some cases, how to behave.

"(Students) got used to doing their work online," Wild said. "They had to relearn these good-attendance habits."

Students got into the habit of staying home instead of going to school, and turning in work via the computer, she said. While students still should stay home if they are sick, they're again encouraged to come to school because that's where they learn better, she said.

When students returned full-time, some in Indian River County struggled with re-acclimating socially in an environment with behavior rules and dress codes and where they had to engage with others, Moore pointed out. The district implemented strict behavior expectations and made students adhere to a code of conduct.

Part of the district's successful recovery, he said, was getting 60% of its students to return to in-person instruction in that first year back.

"When you have more students return to brick-and-mortar, you're going to see a better result," he said. It's more than just academics, said Moore. Students need exposure to socialization skills.

Colleen Wixon is the education reporter for TCPalm and Treasure Coast Newspapers. Contact her at [email protected].

This article originally appeared on Treasure Coast Newspapers: COVID-19 pandemic left its mark on academics. Are students caught up from learning loss?

Associate Professor Neeti Pathare’s Impactful Teaching and Research at Tufts DPT

Neeti Pathare, PhD, MS, is a faculty member in the Tufts accelerated, hybrid DPT Boston program. She was recently recognized with an “Excellence in Online Teaching Award.” Professor Pathare cites her training in Social-Emotional Learning and Universal Design of Learning as part of what has led to her effectiveness in the online classroom. She has integrated these principles to make classes interactive, relevant to learners of diverse backgrounds, supportive, and safe.

“That is my motivator in the classroom,” she says. “Teaching is a very reciprocal process. It’s the energy that students bring to the classroom that allows faculty to go that extra mile.” 

Considering Emotional Health Alongside PT Management

It’s no surprise, then, that Pathare has published research that considers PT management alongside emotional health. For example, in her paper, “Physical therapy management of an individual with post-COVID fatigue considering emotional health in an outpatient setting: A case report,” 1 Pathare and colleague Dylan MacPhail provide a plan of care “with an emphasis on patient education and consideration of emotional health for a patient with post-COVID fatigue in an outpatient setting.”

Their 50-year-old, female patient with ten-weeks post-COVID syndrome participated in an examination that revealed deficits in exercise capacity, strength, breathing pattern, mild depression, emotional breakdown, and mild anxiety accompanied by “brain fog” with activity. The patient’s main complaint was fatigue that prevented her from returning to work.

The patient participated in 20 biweekly sessions with a focus on “patient education, supporting  emotional health, aerobic training, strengthening exercises, breathing exercises, and home exercise program.” At completion of the treatment period, the patient’s “exercise capacity, muscle strength, dyspnea, and depression improved,” and the patient had no anxiety with activity and was able to return to work safely.

Pathare’s work highlights the importance of psychosocial wellbeing in a plan of care for this population. 

The Tufts DPT Coaching Model

Pathare values the social-emotional health of patients and students alike. She notes that connection, collaboration, and mentorship are a big part of what makes the Tufts DPT program special . The coaching model is a key piece of the puzzle.

Each faculty member coaches 7-9 students each year, depending on which students show alignment with faculty based on a strengths finder assessment. This provides rich opportunities for mentorship and collaborative research, Pathare notes. 

Award-Winning Collaborative Research with Students

Recently, two of Pathare’s students worked with her on a research project that received the New York Physical Therapy Association Robert Salant Research award for poster presentation: “Effect of inpatient pulmonary rehabilitation on pulmonary outcomes in individuals with COVID-19: A systematic review.” 2

Pathare and her students determined that while there is much research around Pulmonary Rehabilitation (PR), there is a lack of concrete information on inpatient PR specifically. To address this gap, DPT students worked with Pathare to synthesize studies on the efficacy of inpatient PR on pulmonary outcomes in individuals with COVID-19. Using PubMed, Web of Science, Cochrane Library, and Embase, the researchers screened 474 articles for eligibility with relevant search terms. The pooled sample consisted of 718 participants (F 5 35.2%, age 5 36-71 y).

While the researchers flag that findings should be interpreted with caution due to the high  heterogeneity, sample sizes, and quality of designs of the included studies, the review found that inpatient PR was safe, feasible, and induced large improvements in exercise capacity in individuals with COVID-19. In fact, their study provides valuable evidence that inpatient PR is not only safe but may actually accelerate improvement in exercise capacity in individuals with COVID-19.

Student Teams and Other Methods for Creating a Collaborative Environment for DPT

Pathare notes that Tufts DPT works to build a sense of belonging with the support of student leadership. Many activities have grown out of this work throughout the duration of the program, from pre-orientation to orientation and throughout the hybrid, accelerated DPT program.

Each semester, for example, students are grouped into teams of 3-5 students that work together during sessions, breakout rooms, assessments during class, and even in integrated interprofessional education activities with peers from the Tufts Physician Assistant (PA) program and Occupational Therapy (OT) program. Student teams change every semester to give students a diverse network.

Tufts DPT Students Benefit From Collaboration Across Disciplines

Pathare notes that collaboration across the disciplines is a big part of Tufts DPT. “We are fortunate to have very talented faculty in the Tufts PA and OT programs to collaborate with. It is inspiring to work with people who elevate your knowledge.”

Pathare points out that all Tufts School of Medicine programs emphasize interprofessional collaboration. This helps students practice using their strengths while working with professionals with complimentary areas of knowledge to provide the best plan of care possible for patients. This reflects contemporary practices in the field. 

Studying the Value of Interprofessional Education

Virtual interprofessional education (IPE) is reported to f acilitate clinical decision making and teamwork in students . However, limited studies exist on its effectiveness. Therefore, faculty from the PA and DPT programs, including Pathare, conducted a study 3 of this approach within the Tufts DPT and PA programs to evaluate its effectiveness for Tufts student teams. The guiding question was: “does a case-based, virtual interprofessional education (IPE) experience improve students’ knowledge and attitudes of collaborative team skills”?

Faculty used the Interprofessional Collaborative Competencies Attainment Scale (ICCAS) to assess effectiveness. Tufts students surveyed included those in first-year PA and DPT programs (n = 130, PA = 48, DPT = 82). Students completed the ICCAS survey before and after attendance of a mandatory virtual IPE event. The virtual IPE session centered on “designing a collaborative plan of care for an individual with congestive heart failure in an outpatient setting.”

Ultimately, 122 students (PA = 46, DPT = 76) provided complete survey data. Statistically significant improvement was noted for all 20 questions (P < .001), without any statistically significant differences noted between the 2 disciplines.

The study found that virtual IPE experiences may help improve students’ attitude and knowledge related to IPEC during the initial year of PA and DPT programs. This is a benefit to Tufts DPT and PA students in developing teamwork competencies in healthcare programs.

Setting Up DPT Students to Succeed 

From her award-winning teaching, to her collaborative research with students and beyond, Pathare’s work helps build a welcoming and collaborative learning environment for Tufts DPT students. She notes that while the accelerated nature of the program is challenging, “students know they have a lot of support from faculty and program administrators: faculty mentors, student teams, one on one tutoring, group tutoring, learning specialists, and more. Our culture of belonging, engagement, and collaboration make learning at Tufts DPT enjoyable.”

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1 Neeti Pathare & Dylan MacPhail (15 Jun 2023): “Physical therapy management of an individual with post-COVID fatigue considering emotional health in an outpatient setting: A case report,”  Physiotherapy Theory and Practice , DOI: 10.1080/09593985.2023.2225185 

2 Pathare N Harrod Clark H, Marks K. “Effect of inpatient pulmonary rehabilitation on pulmonary outcomes in individuals with COVID-19: A systematic review,” New York Physical Therapy Association, Oct 2023. 

3 Pathare, Neeti PT, MSPT, PhD; Loder, Rayne MHS, PA-C; Washington, Rosanne MHS, PA-C. "Building interprofessional competency through a virtual cardiopulmonary case collaboration,"  The Journal of Physician Assistant Education , April 30, 2024, DOI: 10.1097/JPA.0000000000000588

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