what is purpose of research

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What is Research? – Purpose of Research

By DiscoverPhDs
September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

Empirical – based on proven scientific methods derived from real-life observations and experiments.
Logical – follows sequential procedures based on valid principles.
Cyclic – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
Controlled – vigorous measures put into place to keep all variables constant, except those under investigation.
Hypothesis-based – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
Analytical – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
Objective – sound judgement is used by the researcher to ensure that the research findings are valid.
Statistical treatment – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

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Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

Identify potential and new customers
Understand existing customers
Set pragmatic goals
Develop productive market strategies
Address business challenges
Put together a business expansion plan
Identify new business opportunities
Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
The analysis is based on logical reasoning and involves both inductive and deductive methods.
Real-time data and knowledge is derived from actual observations in natural settings.
There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
It creates a path for generating new questions. Existing data helps create more research opportunities.
It is analytical and uses all the available data so that there is no ambiguity in inference.
Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

One-to-one Interview
Focus Groups
Ethnographic studies
Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

Survey research
Descriptive research
Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

Valid – founded, logical, rigorous, and impartial.
Accurate – free of errors and including required details.
Reliable – other people who investigate in the same way can produce similar results.
Timely – current and collected within an appropriate time frame.
Complete – includes all the data you need to support your business decisions.

Gather insights

Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
Keep track of the frequency with which each of the main findings appears.
Make a list of your findings from the most common to the least common.
Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
Prepare conclusions and recommendations about your study.
Act on your strategies
Look for gaps in the information, and consider doing additional inquiry if necessary
Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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2.1 Why Is Research Important?

Learning objectives.

By the end of this section, you will be able to:

Explain how scientific research addresses questions about behavior
Discuss how scientific research guides public policy
Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure 2.2 ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the explosion in our use of technology has led researchers to question whether this ultimately helps or hinders us. The use and implementation of technology in educational settings has become widespread over the last few decades. Researchers are coming to different conclusions regarding the use of technology. To illustrate this point, a study investigating a smartphone app targeting surgery residents (graduate students in surgery training) found that the use of this app can increase student engagement and raise test scores (Shaw & Tan, 2015). Conversely, another study found that the use of technology in undergraduate student populations had negative impacts on sleep, communication, and time management skills (Massimini & Peterson, 2009). Until sufficient amounts of research have been conducted, there will be no clear consensus on the effects that technology has on a student's acquisition of knowledge, study skills, and mental health.

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding early intervention programs. These programs are designed to help children who come from low-income backgrounds, have special needs, or face other disadvantages. These programs may involve providing a wide variety of services to maximize the children's development and position them for optimal levels of success in school and later in life (Blann, 2005). While such programs sound appealing, you would want to be sure that they also proved effective before investing additional money in these programs. Fortunately, psychologists and other scientists have conducted vast amounts of research on such programs and, in general, the programs are found to be effective (Neil & Christensen, 2009; Peters-Scheffer, Didden, Korzilius, & Sturmey, 2011). While not all programs are equally effective, and the short-term effects of many such programs are more pronounced, there is reason to believe that many of these programs produce long-term benefits for participants (Barnett, 2011). If you are committed to being a good steward of taxpayer money, you would want to look at research. Which programs are most effective? What characteristics of these programs make them effective? Which programs promote the best outcomes? After examining the research, you would be best equipped to make decisions about which programs to fund.

Link to Learning

Watch this video about early childhood program effectiveness to learn how scientists evaluate effectiveness and how best to invest money into programs that are most effective.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine that your sister, Maria, expresses concern about her two-year-old child, Umberto. Umberto does not speak as much or as clearly as the other children in his daycare or others in the family. Umberto's pediatrician undertakes some screening and recommends an evaluation by a speech pathologist, but does not refer Maria to any other specialists. Maria is concerned that Umberto's speech delays are signs of a developmental disorder, but Umberto's pediatrician does not; she sees indications of differences in Umberto's jaw and facial muscles. Hearing this, you do some internet searches, but you are overwhelmed by the breadth of information and the wide array of sources. You see blog posts, top-ten lists, advertisements from healthcare providers, and recommendations from several advocacy organizations. Why are there so many sites? Which are based in research, and which are not?

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

NOTABLE RESEARCHERS

Psychological research has a long history involving important figures from diverse backgrounds. While the introductory chapter discussed several researchers who made significant contributions to the discipline, there are many more individuals who deserve attention in considering how psychology has advanced as a science through their work ( Figure 2.3 ). For instance, Margaret Floy Washburn (1871–1939) was the first woman to earn a PhD in psychology. Her research focused on animal behavior and cognition (Margaret Floy Washburn, PhD, n.d.). Mary Whiton Calkins (1863–1930) was a preeminent first-generation American psychologist who opposed the behaviorist movement, conducted significant research into memory, and established one of the earliest experimental psychology labs in the United States (Mary Whiton Calkins, n.d.).

Francis Sumner (1895–1954) was the first African American to receive a PhD in psychology in 1920. His dissertation focused on issues related to psychoanalysis. Sumner also had research interests in racial bias and educational justice. Sumner was one of the founders of Howard University’s department of psychology, and because of his accomplishments, he is sometimes referred to as the “Father of Black Psychology.” Thirteen years later, Inez Beverly Prosser (1895–1934) became the first African American woman to receive a PhD in psychology. Prosser’s research highlighted issues related to education in segregated versus integrated schools, and ultimately, her work was very influential in the hallmark Brown v. Board of Education Supreme Court ruling that segregation of public schools was unconstitutional (Ethnicity and Health in America Series: Featured Psychologists, n.d.).

Although the establishment of psychology’s scientific roots occurred first in Europe and the United States, it did not take much time until researchers from around the world began to establish their own laboratories and research programs. For example, some of the first experimental psychology laboratories in South America were founded by Horatio Piñero (1869–1919) at two institutions in Buenos Aires, Argentina (Godoy & Brussino, 2010). In India, Gunamudian David Boaz (1908–1965) and Narendra Nath Sen Gupta (1889–1944) established the first independent departments of psychology at the University of Madras and the University of Calcutta, respectively. These developments provided an opportunity for Indian researchers to make important contributions to the field (Gunamudian David Boaz, n.d.; Narendra Nath Sen Gupta, n.d.).

When the American Psychological Association (APA) was first founded in 1892, all of the members were White males (Women and Minorities in Psychology, n.d.). However, by 1905, Mary Whiton Calkins was elected as the first female president of the APA, and by 1946, nearly one-quarter of American psychologists were female. Psychology became a popular degree option for students enrolled in the nation’s historically Black higher education institutions, increasing the number of Black Americans who went on to become psychologists. Given demographic shifts occurring in the United States and increased access to higher educational opportunities among historically underrepresented populations, there is reason to hope that the diversity of the field will increasingly match the larger population, and that the research contributions made by the psychologists of the future will better serve people of all backgrounds (Women and Minorities in Psychology, n.d.).

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested in the real world; in inductive reasoning , real-world observations lead to new ideas ( Figure 2.4 ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests Figure 2.5 .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( Figure 2.6 ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

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2.1 Why is Research Important

Learning objectives.

By the end of this section, you will be able to:

Explain how scientific research addresses questions about behavior
Discuss how scientific research guides public policy
Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession (figure below). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

A skull has a large hole bored through the forehead.

Some of our ancestors, across the work and over the centuries, believed that trephination – the practice of making a hole in the skull, as shown here – allowed evil spirits to leave the body, thus curing mental illness and other diseases (credit” “taiproject/Flickr)

We can easily observe the behavior of others around us. For example, if someone is crying, we can observe that behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes, asking about the underlying cognitions is as easy as asking the subject directly: “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In other situations, it may be hard to identify exactly why you feel the way you do. Think about times when you suddenly feel annoyed after a long day. There may be a specific trigger for your annoyance (a loud noise), or you may be tired, hungry, stressed, or all of the above. Human behavior is often a complicated mix of a variety of factors. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

USE OF RESEARCH INFORMATION

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? Science is always changing and new evidence is alwaus coming to light, thus this dash of skepticism should be applied to all research you interact with from now on. Yes, that includes the research presented in this textbook.

Evaluation of research findings can have widespread impact. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the D.A.R.E. (Drug Abuse Resistance Education) program in public schools (figure below). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in 75% of school districts in the United States and in more than 40 countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

A D.A.R.E. poster reads “D.A.R.E. to resist drugs and violence.”

The D.A.R.E. program continues to be popular in schools around the world despite research suggesting that it is ineffective.

It is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with a doctor or psychologist and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

THE PROCESS OF SCIENTIFIC RESEARCH

Two types of reasoning are used to make decisions within this model: Deductive and inductive. In deductive reasoning, ideas are tested against the empirical world. Think about a detective looking for clues and evidence to test their “hunch” about whodunit. In contrast, in inductive reasoning, empirical observations lead to new ideas. In other words, inductive reasoning involves gathering facts to create or refine a theory, rather than testing the theory by gathering facts (figure below). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

A diagram has a box at the top labeled “hypothesis or general premise” and a box at the bottom labeled “empirical observations.” On the left, an arrow labeled “inductive reasoning” goes from the bottom to top box. On the right, an arrow labeled “deductive reasoning” goes from the top to the bottom box.

Psychological research relies on both inductive and deductive reasoning.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider the famous example from Greek philosophy. A philosopher decided that human beings were “featherless bipeds”. Using deductive reasoning, all two-legged creatures without feathers must be human, right? Diogenes the Cynic (named because he was, well, a cynic) burst into the room with a freshly plucked chicken from the market and held it up exclaiming “Behold! I have brought you a man!”

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For example, you might be a biologist attempting to classify animals into groups. You notice that quite a large portion of animals are furry and produce milk for their young (cats, dogs, squirrels, horses, hippos, etc). Therefore, you might conclude that all mammals (the name you have chosen for this grouping) have hair and produce milk. This seems like a pretty great hypothesis that you could test with deductive reasoning. You go out an look at a whole bunch of things and stumble on an exception: The coconut. Coconuts have hair and produce milk, but they don’t “fit” your idea of what a mammal is. So, using inductive reasoning given the new evidence, you adjust your theory again for an other round of data collection. Inductive and deductive reasoning work in tandem to help build and improve scientific theories over time.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once. Instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our theory is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests (figure below).

A diagram has four boxes: the top is labeled “theory,” the right is labeled “hypothesis,” the bottom is labeled “research,” and the left is labeled “observation.” Arrows flow in the direction from top to right to bottom to left and back to the top, clockwise. The top right arrow is labeled “use the hypothesis to form a theory,” the bottom right arrow is labeled “design a study to test the hypothesis,” the bottom left arrow is labeled “perform the research,” and the top left arrow is labeled “create or modify the theory.”

The scientific method of research includes proposing hypotheses, conducting research, and creating or modifying theories based on results.

A scientific hypothesis is also falsifiable, or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors (figure below). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable. The essential characteristic of Freud’s building blocks of personality, the id, ego, and superego, is that they are unconscious, and therefore people can’t observe them. Because they cannot be observed or tested in any way, it is impossible to say that they don’t exist, so they cannot be considered scientific theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

(a)A photograph shows Freud holding a cigar. (b) The mind’s conscious and unconscious states are illustrated as an iceberg floating in water. Beneath the water’s surface in the “unconscious” area are the id, ego, and superego. The area just below the water’s surface is labeled “preconscious.” The area above the water’s surface is labeled “conscious.”

Many of the specifics of (a) Freud’s theories, such ad (b) his division on the mind into the id, ego, and superego, have fallen out of favor in recent decades because they are not falsifiable (i.e., cannot be verified through scientific investigation). In broader strokes, his views set the stage for much psychological thinking today, such as the idea that some psychological process occur at the level of the unconscious.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. IHaving good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Review Questions:

1. Scientific hypotheses are ________ and falsifiable.

a. observable

b. original

c. provable

d. testable

2. ________ are defined as observable realities.

a. behaviors

c. opinions

d. theories

3. Scientific knowledge is ________.

a. intuitive

b. empirical

c. permanent

d. subjective

4. A major criticism of Freud’s early theories involves the fact that his theories ________.

a. were too limited in scope

b. were too outrageous

c. were too broad

d. were not testable

Critical Thinking Questions:

1. In this section, the D.A.R.E. program was described as an incredibly popular program in schools across the United States despite the fact that research consistently suggests that this program is largely ineffective. How might one explain this discrepancy?

2. The scientific method is often described as self-correcting and cyclical. Briefly describe your understanding of the scientific method with regard to these concepts.

Personal Application Questions:

1. Healthcare professionals cite an enormous number of health problems related to obesity, and many people have an understandable desire to attain a healthy weight. There are many diet programs, services, and products on the market to aid those who wish to lose weight. If a close friend was considering purchasing or participating in one of these products, programs, or services, how would you make sure your friend was fully aware of the potential consequences of this decision? What sort of information would you want to review before making such an investment or lifestyle change yourself?

deductive reasoning

falsifiable

hypothesis: (plural

inductive reasoning

Answers to Exercises

Review Questions:

1. There is probably tremendous political pressure to appear to be hard on drugs. Therefore, even though D.A.R.E. might be ineffective, it is a well-known program with which voters are familiar.

2. This cyclical, self-correcting process is primarily a function of the empirical nature of science. Theories are generated as explanations of real-world phenomena. From theories, specific hypotheses are developed and tested. As a function of this testing, theories will be revisited and modified or refined to generate new hypotheses that are again tested. This cyclical process ultimately allows for more and more precise (and presumably accurate) information to be collected.

deductive reasoning: results are predicted based on a general premise

empirical: grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing

fact: objective and verifiable observation, established using evidence collected through empirical research

falsifiable: able to be disproven by experimental results

hypothesis: (plural: hypotheses) tentative and testable statement about the relationship between two or more variables

inductive reasoning: conclusions are drawn from observations

opinion: personal judgments, conclusions, or attitudes that may or may not be accurate

theory: well-developed set of ideas that propose an explanation for observed phenomena

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1.3: What is the Purpose of Research?

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Anol Bhattacherjee
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Learning Objective

Differentiate between theory and laws.

The purpose of science is to create scientific knowledge. Scientific knowledge refers to a generalized body of laws and theories to explain a phenomenon or behavior of interest that are acquired using the scientific method. Laws are observed patterns of phenomena or behaviors, while theories are systematic explanations of the underlying phenomenon or behavior. For instance, in physics, the Newtonian Laws of Motion describe what happens when an object is in a state of rest or motion (Newton’s First Law), what force is needed to move a stationary object or stop a moving object (Newton’s Second Law), and what happens when two objects collide (Newton’s Third Law). Collectively, the three laws constitute the basis of classical mechanics – a theory of moving objects. Likewise, the theory of optics explains the properties of light and how it behaves in different media, electromagnetic theory explains the properties of electricity and how to generate it, quantum mechanics explains the properties of subatomic particles, and thermodynamics explains the properties of energy and mechanical work. An introductory college level text book in physics will likely contain separate chapters devoted to each of these theories. Similar theories are also available in social sciences. For instance, cognitive dissonance theory in psychology explains how people react when their observations of an event is different from what they expected of that event, general deterrence theory explains why some people engage in improper or criminal behaviors, such as illegally download music or commit software piracy, and the theory of planned behavior explains how people make conscious reasoned choices in their everyday lives.

The goal of scientific research is to discover laws and postulate theories that can explain natural or social phenomena, or in other words, build scientific knowledge. It is important to understand that this knowledge may be imperfect or even quite far from the truth. Sometimes, there may not be a single universal truth, but rather an equilibrium of “multiple truths.” We must understand that the theories, upon which scientific knowledge is based, are only explanations of a particular phenomenon, as suggested by a scientist. As such, there may be good or poor explanations, depending on the extent to which those explanations fit well with reality, and consequently, there may be good or poor theories. The progress of science is marked by our progression over time from poorer theories to better theories, through better observations using more accurate instruments and more informed logical reasoning.

We arrive at scientific laws or theories through a process of logic and evidence. Logic (theory) and evidence (observations) are the two, and only two, pillars upon which scientific knowledge is based. In science, theories and observations are interrelated and cannot exist without each other. Theories provide meaning and significance to what we observe, and observations help validate or refine existing theory or construct new theory. Any other means of knowledge acquisition, such as faith or authority cannot be considered science.

KEY TAKEAWAY

Theories are a means to build up to laws.

Research Basics

What Is Research?
Types of Research
Secondary Research | Literature Review
Developing Your Topic
Primary vs. Secondary Sources
Evaluating Sources
Responsible Conduct of Research
Additional Help

Research is formalized curiosity. It is poking and prying with a purpose. - Zora Neale Hurston

A good working definition of research might be:

Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge.

Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking up reviews of various products online, learning more about celebrities; these are all research.

Formal research includes the type of research most people think of when they hear the term “research”: scientists in white coats working in a fully equipped laboratory. But formal research is a much broader category that just this. Most people will never do laboratory research after graduating from college, but almost everybody will have to do some sort of formal research at some point in their careers.

So What Do We Mean By “Formal Research?”

Casual research is inward facing: it’s done to satisfy our own curiosity or meet our own needs, whether that’s choosing a reliable car or figuring out what to watch on TV. Formal research is outward facing. While it may satisfy our own curiosity, it’s primarily intended to be shared in order to achieve some purpose. That purpose could be anything: finding a cure for cancer, securing funding for a new business, improving some process at your workplace, proving the latest theory in quantum physics, or even just getting a good grade in your Humanities 200 class.

What sets formal research apart from casual research is the documentation of where you gathered your information from. This is done in the form of “citations” and “bibliographies.” Citing sources is covered in the section "Citing Your Sources."

Formal research also follows certain common patterns depending on what the research is trying to show or prove. These are covered in the section “Types of Research.”

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Last Updated: Dec 21, 2023 3:49 PM
URL: https://guides.library.iit.edu/research_basics

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What is Research?

Research is an often-misused term, its usage in everyday language very different from the strict scientific meaning.

This article is a part of the guide:

Definition of Research
Research Basics
Steps of the Scientific Method
Purpose of Research
What is the Scientific Method?

Browse Full Outline

1 Research Basics
2.1 What is Research?
2.2 What is the Scientific Method?
2.3 Empirical Research
3.1 Definition of Research
3.2 Definition of the Scientific Method
3.3 Definition of Science
4 Steps of the Scientific Method
5 Scientific Elements
6 Aims of Research
7 Purpose of Research
8 Science Misconceptions

In the field of science, it is important to move away from the looser meaning and use it only in its proper context. Scientific research adheres to a set of strict protocols and long established structures.

Definition of the Scientific Method

Often, we will talk about conducting internet research or say that we are researching in the library. In everyday language, it is perfectly correct grammatically, but in science , it gives a misleading impression. The correct and most common term used in science is that we are conducting a literature review .

The Guidelines

What is research ? For a successful career in science, you must understand the methodology behind any research and be aware of the correct protocols.

Science has developed these guidelines over many years as the benchmark for measuring the validity of the results obtained.

Failure to follow the guidelines will prevent your findings from being accepted and taken seriously. These protocols can vary slightly between scientific disciplines, but all follow the same basic structure.

Aims of Research

The general aims of research are:

Observe and Describe

Determination of the Causes

Purpose of Research - Why do we conduct research? Why is it necessary?

Steps of the Scientific Process

The steps of the scientific process has a structure similar to an hourglass - The structure starts with general questions, narrowing down to focus on one specific aspect , then designing research where we can observe and analyze this aspect. At last, the hourglass widens and the researcher concludes and generalizes the findings to the real world.

Summary of the Elements in Scientific Research

1) Setting a Goal

Research in all disciplines and subjects, not just science, must begin with a clearly defined goal . This usually, but not always, takes the form of a hypothesis .

For example, an anthropological study may not have a specific hypothesis or principle, but does have a specific goal, in studying the culture of a certain people and trying to understand and interpret their behavior.

The whole study is designed around this clearly defined goal, and it should address a unique issue, building upon previous research and scientifically accepted fundamentals. Whilst nothing in science can be regarded as truth, basic assumptions are made at all stages of the research, building upon widely accepted knowledge.

2) Interpretation of the Results

Research does require some interpretation and extrapolation of results.

In scientific research, there is always some kind of connection between data (information gathered) and why the scientist think that the data looks as it does. Often the researcher looks at the data gathered, and then comes to a conclusion of why the data looks like it does.

A history paper, for example, which just reorganizes facts and makes no commentary on the results, is not research but a review .

If you think of it this way, somebody writing a school textbook is not performing research and is offering no new insights. They are merely documenting pre-existing data into a new format.

If the same writer interjects their personal opinion and tries to prove or disprove a hypothesis , then they are moving into the area of genuine research. Science tends to use experimentation to study and interpret a specific hypothesis or question, allowing a gradual accumulation of knowledge that slowly becomes a basic assumption.

3) Replication and Gradual Accumulation

For any study, there must be a clear procedure so that the experiment can be replicated and the results verified.

Again, there is a bit of a grey area for observation-based research , as is found in anthropology, behavioral biology and social science, but they still fit most of the other criteria.

Planning and designing the experimental method , is an important part of the project and should revolve around answering specific predictions and questions . This will allow an exact duplication and verification by independent researchers, ensuring that the results are accepted as real.

Most scientific research looks at an area and breaks it down into easily tested pieces.

The gradual experimentation upon these individual pieces will allow the larger questions to be approached and answered, breaking down a large and seemingly insurmountable problem, into manageable chunks.

True research never gives a definitive answer but encourages more research in another direction. Even if a hypothesis is disproved, that will give an answer and generate new ideas, as it is refined and developed.

Research is cyclical, with the results generated leading to new areas or a refinement of the original process.

4) Conclusion

The term, research , is much stricter in science than in everyday life.

It revolves around using the scientific method to generate hypotheses and provide analyzable results. All scientific research has a goal and ultimate aim , repeated and refined experimentation gradually reaching an answer.

These results are a way of gradually uncovering truths and finding out about the processes that drive the universe around us. Only by having a rigid structure to experimentation, can results be verified as acceptable contributions to science.

Some other areas, such as history and economics, also perform true research, but tend to have their own structures in place for generating solid results. They also contribute to human knowledge but with different processes and systems.

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Martyn Shuttleworth (Feb 2, 2008). What is Research?. Retrieved Apr 21, 2024 from Explorable.com: https://explorable.com/what-is-research

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Airport Passenger-Related Processing Rates Guidebook (2009)

Chapter: chapter 3 - defining the research: purpose, focus, and potential uses.

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

14 Chapter 3 identifies roles, relationships, and responsibilities of stakeholders. It examines principal steps involved in planning an airport passenger-rate data collection effort. It begins with the ques- tion of whether the potential benefits of the proposed effort outweigh the anticipated cost; describes different types of research (i.e., exploratory, descriptive, inferential); summarizes the questions each type addresses; and notes the ends to which the data might be used. 3.1 Roles and Responsibilities When an airport data collection event is first mentioned, it invariably raises numerous ques- tions: Who is asking for the data? How will it be used? Whatâs the budget? Whatâs the schedule? What kind of resources can be made available? Without answers to these fundamental questions, the success of your research is in jeopardy. This section will help the researcher establish the role of key stakeholders and their interrelationships within the team. Many entities can sponsor a data collection study, including airports, airlines, manufacturers, and various agencies. Likewise, there are many ways of managing and staffing the event and pro- moting involvement with stakeholders. There are therefore myriad ways of organizing a study. Exhibit 3-1 is an example of how a study could be arranged with the airport as the sponsor. 3.1.1 Client/Sponsor For airports, oversight is guided by a board, commission, or an authority consisting of appointed or elected officials. While these agencies typically provide oversight to airport man- agement and approve long-term plans and large capital expenditures, usually it is the airport director or manager who makes day-to-day decisions. Depending on the size of the airport, there may be several departments, each having its own manager. In such cases, passenger terminal-related studies would typically fall within the purview of the planning and/or engineering department and would be managed by its director. Regardless of the affiliation of the project sponsor(s), it is essential that the following ques- tions be answered clearly and unambiguously as they pertain to the sponsor at the beginning of any project: â¢ Who has primary responsibility for defining the questions the study is intended to address? â¢ What preference does this person or group have regarding ongoing involvement with the project? â What information would they like to receive, in what format, and with what frequency? â Who should be the principal point-of-contact (POC) on the clientâs side for questions that might emerge related to the studyâs focus, direction, etc.? C H A P T E R 3 Defining the Research: Purpose, Focus, and Potential Uses

Defining the Research: Purpose, Focus, and Potential Uses 15 â¢ Who is the designated project manager, and what information would he or she like to receive, in what format, and with what frequency? â¢ If the person given responsibility for day-to-day issues pertaining to access, authorizations, etc. is different from the project manager, who is that person, and what is the scope of issues he or she is authorized to address? â¢ If problems or obstacles arise in implementing the study, and the project manager is not able or authorized to resolve them, what is the chain of persons through which the issue should be escalated? 3.1.2 Study Team The size of the study team will depend on the teamâs depth and organization, and the size, duration, and complexity of the study itself. For a typical medium- to large-scale study, the roles listed in the following sections are the most typical. Multiple roles might be assumed by a single person or distributed across multiple persons. Titles vary as well, but the functions are largely universal. Project Manager The project manager is typically a mid-level to senior person who has the long-term, day-to- day relationship with his or her client counterpart. The need for the passenger-related process- ing rate study may initially originate from discussions between the project manager and those within the airport or airline. Survey Manager The survey manager is usually a mid-level staff person. His/her role on the project would be to oversee the day-to-day management of the data processing rate study, including leading the development of the scope, schedule, and budget; developing the team; and assigning roles and responsibilities. The survey manager would have the responsibility of ensuring the survey goals were adequately defined and met. Decision Maker Survey Manager Admin. Support Staffing Source (e.g., airport personnel, mkt. research firm) Surveyor Surveyor Surveyor Sponsor/Client (Airport) (Large Airport: Dir./Mgr.) Project Manager (Large Airport: Dir. Planning/Eng.) (Small Airport: Apt. Mgr.) Project Manager (Typ. oversees multiple tasks of which survey is but one part) Study Team (Typically, Consultant) Statistical Technical Expert Survey Assistant Data Analyst IT Analyst Other Stakeholders â¢ Airlines â¢ Agencies â¢ Concessionaires Exhibit 3-1. Typical sponsor and study team roles (assuming an airport is the sponsor).

16 Airport Passenger-Related Processing Rates Guidebook Research and Statistical Expert A person(s) with expertise in research methodology and quantitative/statistical analysis should be consulted to develop, or provide comments and recommendations about, the overall methodology, the sampling plan, and so forth. Most of this personâs input would occur at the projectâs initiation. A distinction is sometimes drawn in the consulting literature among differ- ent approaches to consulting. One such approach, generally referred to as process consultation might be of particular appeal.1 When acting in this role, the consultant not only provides tech- nical expertise related to the specific project, but also works with the client to develop expertise. This arrangement has the goal of, over time, reducing the reliance on the consultant. Survey Assistant The survey assistant has primary responsibility for assisting the survey project manager and secondarily to assist others on the project team throughout the duration of the study. Typically, this staff person will be at a junior level. The degree of assistance this person can provide is based on his/her level of education and current skill sets. Data Analyst The data analyst should not only be well-versed in technical analysis, but should also have a strong familiarity with the airport terminal environment. This person could be a terminal or air- port planner or aviation architect. The analyst is often largely responsible for documenting results, and responsibilities might extend to presenting findings to the client. Administrative Support Data collection efforts are inherently complex and, as such, often require a significant level of coordination and administration. The staff person serving this function would be responsible for such things as making travel plans, scheduling visits to the airportâs security office, buying supplies, shipping and receiving materials, scheduling meetings, preparing invoices and con- tracts, and editing/proofing the report. Data Collection Staff For small studies (e.g., small airports where only a few functional elements are being observed for a limited time period), airport/airline or consultant staffing may be used. For larger studies, typically examining multiple functional elements of a medium or large airport over a multi-day period, a market-research firm is frequently employed. The data collection staff reports directly to the survey manager. 3.2 Is the Study Needed? While the need for data collection is often justifiable, the benefit of validating the need, and avoiding what might be a costly, and possibly unjustified, effort well exceeds the relatively minor cost of pausing to consider a few basic questions (see Appendix C for more information). Exhibit 3-2 illustrates these questions. 3.3 Research Fundamentals This section summarizes a number of fundamental issues and terms related to the research process. (Additional detail is included in Appendix C.) 1 Schein, E. H. (1999). Process Consultation Revisited: Building the Helping Relationship. NY: Addison Wesley.

Research is a dynamic process with both deductive and inductive dimensions. This differs in some ways from what some present as the âtraditionalâ approach to research, i.e., that theory drives hypothesis testing. Sometimes it does, but sometimes it doesnât work this way. 3.3.1 Theory, Hypotheses, and Evidence The word âtheoryâ often implies a formal set of laws, propositions, variables, and the like, whose relationships are clearly defined. A related implication is that theory may not be particu- larly germane to the everyday world of work. This view of theory is not incorrect, but neither is it complete. While theory can be abstract and complex in its detail, it does not necessarily have to be abstract, complex, or formal. It can be thought of more broadly and simply as an explanation of âhow the world works.â For exam- ple, an organization might develop a mission or a value statement (or both); engrave the words in a medium intended to last millennia; and prominently display the statement in the workplace with the intent of communicating to all its perspective clients on issues pertinent to its view. In Defining the Research: Purpose, Focus, and Potential Uses 17 Question Things to Consider Have relevant data been collected at this airport in the past that might be used rather than collecting new data? Might you be able to get data from another airport similar in key ways to this airport? Are there data available that might help answer the research question? Might access to the data be blocked due to proprietary or security issues? Sometimes the data are perceived to be so sensitive that the âownerâ of the data may not give permission to share it. Has the decision already been made, and the data are being collected to legitimize the decision? Is there anything to suggest that the study is an attempt to âproveâ something true or false? What role will the results play in the decision being considered? To what extent will the decision makers be persuaded by the results? What will the decision makers accept as credible evidence? Before collecting data, make certain that the research plan will result in data that the sponsors will accept. It is better to learn beforehand, for example, that the proposed sampling plan does not meet the sponsorâs criteria for rigor. What is the cost of the potential investment that the data will help inform? What is the cost of conducting the research? Does the benefit equal or outweigh the cost? Cost should be considered not only in economic terms, but as safety, inconvenience, and so forth. Exhibit 3-2. Considerations to determine need for data collection.

2008, British Airways announced a new venture: OpenSkies. The âtheoryâ OpenSkies used to define its clients is reflected in its advertising as shown in Exhibit 3-3. So, how does this relate to airport processing rate studies? It relates in the following two ways: 1. The published research literature may well contain formal theories relevant to what data to collect and how to collect it. For example, Appendix B includes a bibliography of recent research articles related to passenger and baggage processing in airports. It is intended to illustrate the scope and diversity of research available on a given topic. Before embarking on an investigation, review the literature to see how it might enhance the quality of the planned research. The Internet provides access to numerous sources for such scholarly documents. 2. Informally, the key decisions about how to go about collecting data are grounded in assump- tions about how things work (i.e., oneâs own theory). For example, you might choose to col- lect passenger security screening data between 6:00 a.m. and 8:00 a.m. on a Monday because your experience is that this time period reflects peak checkpoint activity. While this âtheoryâ may be correct in some circumstances, it may also be wrong in others. For example, at many vacation-oriented airports, the peak at the checkpoint occurs in the late morning due to check-out times at hotels. Another common view of research is of the stereotypical scientist, objectively testing hypothe- ses (or an âeducated guessâ) arising from theory. Exhibit 3-4 reflects this general approach to research. This is certainly one way in which research proceeds, but, similar to theory, it is not the only way. Before considering an âevidence firstâ approach, we wish to mention a variation on the tra- ditional approach displayed in Exhibit 3-4 that has been gaining dominance in recent years. In particular, this is a confidence interval (CI) approach rather than a hypothesis driven approach. In a hypothesis driven approach, the researcherâs primary interest is in testing a population parameter, and uses a sample drawn from the population. When the researcher takes a CI approach, the intent is to calculate an interval within which the population parameter is likely 18 Airport Passenger-Related Processing Rates Guidebook Exhibit 3-3. OpenSkies advertisement. Question key assumptions, even if they seem to be âcommon sense,â by checking with informants, look- ing at the literature, etc.

to fall. Hypotheses are stated before data collection; CIs are calculated after data are collected.2 In conducting passenger-processing rate research in airport environments, the CI approach is going to be the most appropriate in most instances. A markedly different approach to those described above is shown in Exhibit 3-5. In contrast to beginning with a theory and then collecting evidence to test the theory or estimate a popula- tion parameter within some CI, this approach begins with evidence for which one seeks poten- tial explanations, or âtheoriesâ to explain the evidence. This approach is subsumed under the broad heading of Bayesian Law, so named after the 18th Century English clergyman, Thomas Bayes, credited with developing the approach. Depending on where one begins can result in potentially dramatic conclusions (see Exhibit 3-6). This is important because limiting oneself to a particular perspective of how research should be conducted and how data ought to be gathered may impose unnecessary constraints. What is important is that the research is executed systematically and with rigor. The documented ways in which science proceeds are often idealized: portraying what is inherently a very dynamic and nonlinear process as logical and linear. 3.3.2 Research Questions and Purposes A basic issue in research is specifying the question the research will help answer. Penning a specific question also helps in determining what approach might be best used in seeking an Defining the Research: Purpose, Focus, and Potential Uses 19 Theory Drives questions & hypotheses Hypothesis: Installing n kiosks will reduce the average time of passengers waiting in line by 10% over check-in agents. Leading to a conclusion Drives data collection Followed by analysis Exhibit 3-4. Hypothesis driven approach. Evidence leads to speculation about possible explanations Which may or may not drive more data collection & analysis Theory Exhibit 3-5. Bayesian approach. 2 While these approaches are presented here as mutually exclusive, they might be integrated in practice.

answer. One classic text in research methodology5 suggests that a research question should express a relationship between two or more variables, and it should imply an empirical approach, that is, it should lend itself to being measured using data. A variable is, not surprisingly, some- thing that can vary, or assume different values. In the next section, illustrative questions are given, categorized by the purpose of research with which they are best matched. The five research purposes are presented as the following: 1. Explore, 2. Describe, 3. Test, 4. Evaluate, and 5. Predict. The distinctions among these purposes are not absolute, nor are they necessarily exclusive of one another. A research initiative might be directed at answering questions with multiple pur- poses. Indeed, this is but one of many ways of classifying research. In addition, the reader whose practice lies primarily in the arena of modeling and simulation might note their absence from this list. Although modeling and simulation applications require input data, for example, to gen- erate distributions and parameters for use as stochastic varieties in modeling, the techniques used to collect data are largely independent of specific applications (such as simulation and model- ing). Those issues unique to modeling are beyond the scope of this guidebook. Explore (Exploratory Research) Exploratory research is sometimes defined as âwhat to do when you donât know what you donât know.â Its aim is discovery and to develop an understanding of relevant variables and their interactions in a real (field) environment. Exploratory research, as such, is appropriate when the 20 Airport Passenger-Related Processing Rates Guidebook If your intent is toâ¦ And take action based onâ¦ Useâ¦ Example Test a hypothesis regarding a population parameter Whether you reject or fail to reject the null hypothesis Hypothesis testing approach The proportion of coach passengers checking in more than 60 min prior to scheduled departure is 80% H A : p > .80 3 H 0 : p .804 Estimate a population parameter The confidence interval selected CI approach Plus or minus 5%, what is the average time coach passengers check in prior to scheduled departure? Determine the likelihood of an event given some evidence The calculated probability Bayesian approach What is the probability that a passengerâs carry on- luggage will be subject to secondary security screening given that the passenger is boarding an international flight? Exhibit 3-6. Research approaches. 3 This is the research, or Alternative, hypothesis. It reads: The proportion is greater than 80%. 4 This is the null hypothesis. It is what is tested, and reads: The proportion is less than or equal to 80%. 5 Kerlinger F. & Lee, H. (2000). Foundations of Behavioral Research, 4th ed. NY: Harcourt Brace.

problem is not well defined. For example, passenger complaints about signs within a facility might prompt the following exploratory question: â¢ âWhere should signage be located to minimize passenger confusion?â As another example, if a new security checkpoint configuration is proposed, it may be too novel to rely on variables used in other studies. The question, therefore, might then be the following: â¢ âHow does a given alternative security checkpoint configuration affect capacity?â This type of research is often qualitative rather than quantitative. That is, it employs verbal descriptors of observations, rather than counts of those observations (see Appendix C for more information). Describe (Descriptive Research) Descriptive research, as the name implies, is intended to describe phenomena. While descrip- tive research might involve collecting qualitative data by asking open-ended questions in an interview, it typically employs quantitative methods resulting in reporting frequencies, calculat- ing averages, and the like. The following two questions illustrate the nature of descriptive research. Each implies that the relevant variables have been identified as well as the conditions under which the data should be collected. â¢ âWhat is the average number of passengers departing on international flights on weekday evenings in July at a given airport?â â¢ âHow many men use a given restroom at a particular location at a given time?â Test (Experimental and Quasi-experimental Research and Modeling) Often, the intent of the research is not simply to describe something, but to test the impact of some intervention. In an airport environment, such research might be initiated to evaluate the relative effectiveness of a security screening technology in accurately detecting contraband. It is similar in approach to research conducted to assess the relative effectiveness of an experimental drug in comparison to a control (placebo) or another drug. Variables are often manipulated and controlled. This research lies largely outside the scope of this guidebook and, as such, will not receive much attention. Examples of questions that might be asked in this type of research include the following: â¢ âWhat is the impact of posting airline personnel near check-in waiting lines on the average passenger waiting time?â In addition to the classic âexperiment,â simulation modeling might be used, employing rep- resentative data to help answer questions such as the following: â¢ âWhat would be the impact on processing time of a new security measure being considered?â â¢ âHow many agents are needed to keep passenger waiting time below an average of 10 min?â Evaluate (Evaluative Research) Sometimes, the intent of the research is to assess performance against some standard or stated requirement. Basically, evaluation research is concerned with seeing how well something is work- ing, with an eye toward improving performance, as illustrated by the following two questions: â¢ âIs the performance of a given piece of equipment in the field consistent with manufacturerâs specifications?â â¢ âOn average, what proportion of passengers waits in a security checkpoint line longer than the 10-minute maximum threshold specified by an airline?â Defining the Research: Purpose, Focus, and Potential Uses 21

Predict Finally, research might be initiated to attempt to predict or anticipate potential emerging pat- terns before they occur. This is related to environmental scanning, insofar as it represents a delib- erate attempt to monitor potential trends and their impact. For example, in the early 1970s, one might have posed the following question: â¢ âWhat would be the impact of an increase in the number of women in the workforce on air- port design?â There are numerous documented approaches to answering questions such as these. While well beyond the scope of this guidebook, here is one as illustrative: scenario planning. This method involves convening persons with relevant expertise to identify those areas that might most impact the industry (e.g., regulation, fuel costs, demographic changes), and then to systemati- cally consider what the best, worst, and might likely scenarios might be. The principal value of such an approach is that it facilitates deliberate consideration of future trends, and in so doing, presumably leaves people better prepared. When the goal of the research is to predict, data from multiple sources might be sought. The scenario planning example relies, to an extent, on the judgments of experts. Probabilities can also be drawn from historical data to help identify patterns and trends. Exhibit 3-7 is a summary of the key characteristics of each research type. 3.4 Developing the Research Plan Large research studies, particularly when funding is being requested, often require the researchers to adhere to a specific set of technical requirements. The Research Team is aware that the ad hoc and short timeline of many airport-planning research efforts makes developing a âfor- malâ research plan impracticable. Nonetheless, even though you might not have the âluxuryâ of 22 Airport Passenger-Related Processing Rates Guidebook Research Purpose Characteristics Explore Primary purpose: to better define or understand a situation. Data will help answer the research question. The benefit of conducting the research justifies the cost. Qualitative data are recorded, using observation. Describe Primary purpose: to provide descriptive information about something. Test Primary purpose: to assess the impact of a proposed change in procedure or policy. Evaluate Primary purpose: to assess performance against requirements. Predict Primary purpose: to consider possible future circumstances with the purpose of being better prepared for emerging trends. Exhibit 3-7. Summary of research types.

developing such a plan, there are benefits to considering the issues described in this section, as well as documenting basic information. The following are the three major elements the Research Team believes worth documenting, regardless of the size of the research endeavor.6 1. Goals or aims. 2. Background and significance. 3. Research design and methods. Each is described in the sections that follow. 3.4.1 Goals or Aims Specify the question the research is intended to help answer or the specific purpose of the research. The experience of having to translate an intended purpose into words can help clarify your intent. In addition, a written statement can serve as a way of ensuring that your understand- ing of the purpose of the research is consistent with that of the sponsor and other stakeholders. Two examples follow: Statement of PurposeâExample 1 The purpose of this study is to aid decision makers in determining if extending the dwell time of the airportâs automated guideway transit system (AGTS) vehicles from 30 sec to 35 sec at the Concourse C station might improve overall system capacity by providing more boarding time for passengers. Statement of PurposeâExample 2 The goal of this study is to provide airport management with recent data showing the percent- age of arriving flights whose first checked bag reaches the claim device within the airportâs goal of 15 min. 3.4.2 Background and Significance Document what is already known, and specify how the proposed research initiative will add to this knowledge. Consider a âdevilâs advocateâ perspective by asking what the consequences of not doing the research might be. 3.4.3 Research Design and Methods In this section, describe how you will go about collecting and analyzing data. Additional infor- mation about these issues, including sampling strategies and sample size, is presented in Chapter 5 and in Appendix C. The research plan does not need be lengthy. It should, however, capture key information that, were it not documented and those familiar with the research were not available, would be diffi- cult to ascertain. Defining the Research: Purpose, Focus, and Potential Uses 23 6 This section is partly based on guidelines published by the Agency for Healthcare Research and Quality, Department of Health and Human Services. http://www.ahrq.gov/fund/esstplan.htm.

TRB’s Airport Cooperative Research Program (ACRP) Report 23: Airport Passenger-Related Processing Rates Guidebook provides guidance on how to collect accurate passenger-related processing data for evaluating facility requirements to promote efficient and cost-effective airport terminal design.

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11.1 The Purpose of Research Writing

Learning objectives.

Identify reasons to research writing projects.
Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

Medical laboratory technician
Small business owner
Information technology professional
Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

Choose a topic.
Plan and schedule time to research and write.
Conduct research.
Organize research and ideas.
Draft your paper.
Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

In which steps of the research writing process are you allowed to change your thesis?
In step 2, which types of information should you include in your project schedule?
What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

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Doing Research in Education: Theory and Practice

Student resources, 1. the purpose of research: why do we do it.

Select SAGE Journal articles are available to give you even more insight into chapter topics. These are also an ideal resource to help support your literature reviews, dissertations and assignments.

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Brace, M., Herriotts, P., Mccullagh, A. and Nzegwu, F. (2007) ‘Why research — what research should be done?: Report of a collaborative workshop in the UK to discuss social research priorities on visual impairment’, British Journal of Visual Impairment , 25(2): 178–189.

Hannah, D.R. and Lautsch, B.A. (2010) ‘Counting in Qualitative Research: Why to Conduct it, When to Avoid it, and When to Closet it’, in Journal of Management Inquiry , 20(1): 14–22.

Nursing Research pp 1–17 Cite as

The purpose of qualitative research

Janice M. Morse 3 &
Peggy Anne Field 4

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Research fills a vital and important role in society: it is the means by which discoveries are made, ideas are confirmed or refuted, events controlled or predicted and theory developed or refined. All of these functions contribute to the development of knowledge. However, no single research approach fulfills all of these functions, and the contribution of qualitative research is both vital and unique to the goals of research in general. Qualitative research enables us to make sense of reality, to describe and explain the social world and to develop explanatory models and theories. It is the primary means by which the theoretical foundations of social sciences may be constructed or re-examined.

Research is to see what everybody has seen and to think what nobody has thought. (Albert Szent-Gyorgy)

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v.44(4); 2016 Aug

What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

Observational
Experimental
Descriptive
Retrospective
Prospective
Cross-sectional
Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

Case series
Surveillance studies

II. Analytical research

Observational studies: cohort, case control and cross- sectional research
Interventional research: quasi-experimental and clinical research
Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

Type-I (α) and type-II (β) error levels
Difference between groups (d-difference) and effect size (ES)
Distribution ratio of groups
Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

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14.1: The Purpose of Research Writing

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Amber Kinonen, Jennifer McCann, Todd McCann, & Erica Mead
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Introduction

You may know the answers to these questions off the top of your head; however, if you are like most people,you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Reasons for Research

The research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular— and effective—presentation forms is the research paper. A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. You may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. Because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally. For example, a medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

Choose a topic.
Plan and schedule time to research and write.
Conduct research.
Organize research and ideas.
Draft your paper.
Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

To narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question—a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis. You may use your research question and your working thesis to create a research proposal. In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

A topic might be too broad if it cannot be covered in detail in your assignment, if there is too much information (1000s of results), or all you can write is general statements. For example, the research question “What is communication?” is too broad for a four-page assignment. There is no way to adequately sum up all of the information about you will encounter about communication when trying to answer this question.

A topic might be too narrow if it can be discussed in great detail in less than the required size of your essay, or if there is little to no information or relevant results available. For example, the research question ‘What percentage of Ford Escorts were recalled in 2016 due to faulty airbags?” would be too narrow to adequately discuss in a four-page research paper. The question can be simply answered with a percentage, and the date of 2016 might be too current to retrieve enough research.

Step 2: Planning and Scheduling

In addition, it may be helpful (and even required by some instructors) to construct an outline that serves as a blueprint for your project. The outline will include your thesis statement, the main ideas that will support your thesis, examples to illustrate those main ideas, and counterarguments. By constructing an outline, you are more likely to stay focused and not repeat key ideas.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources. Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

Remember, your working thesis is a work in progress. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism, or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

In which steps of the research writing process are you allowed to change your thesis?
In step 2, which types of information should you include in your project schedule?
What might happen if you eliminated step 4 from the research writing process

key takeaways

People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

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The Health and Clinical Outcomes Research, Health Data Science Student Spotlight Series: Pham Quoc Anh Vu (’24)

Pham Quoc Anh Vu (’24) is a second-year student in the Master of Health Data Science program in the Saint Louis University School of Medicine.

He recently shared his thoughts about the program and why he pursued a career in Health Data Science, advice for incoming students, and what he hopes to do with his career.

What inspired you to pursue a degree in Health Data Science?

Initially, my motivation stemmed from a desire to further my career prospects, coupled with a quest for comprehension whenever my biology research colleagues would present their bio-informatic data. However, over time, my fascination deepened into a genuine passion for data science and love for the intricacies of coding.

I find immense gratification in witnessing how data informs our decision-making processes and debunking preconceived assumptions. The evolving landscape of data science continues to captivate me, driving my dedication to unraveling its complexities and contributing to its advancements, and the little spark of joy when seeing your code run perfectly.

What skills or knowledge have you gained that you believe will benefit your future career?

In addition to employing statistical methodologies and analyses for adapting machine learning models, the program has instilled in me a profound appreciation for the virtues of patience and flexibility. Through this journey, I've come to understand that while technical expertise is vital, the ability to patiently iterate, refine, and adapt models based on evolving data and insights is equally crucial.

Rather than fixating on a singular approach, I learned to embrace alternative perspectives when tackling complex problems. I have become more confident being proactive with the faculty and professors, asking questions whenever uncertain, and consistently interacting with and utilizing all available resources.

How has your involvement in extracurricular activities or research enhanced your academic journey?

I had the privilege of collaborating with Dr. (Noor) Al-Hammadi on a project that initially seemed straightforward. We anticipated that coding for a specific package would be a brief task, perhaps spanning a day or two. However, as we delved deeper, we encountered complexities beyond our expectations.

By meticulously scrutinizing every aspect of the package's design, I fortified its resilience, ensuring it could effortlessly evolve alongside the dynamic landscape of data science, ready to tackle new challenges with unwavering efficacy, and a sprinkle of finesse.

How has the support and mentorship from faculty and peers influenced your academic and personal growth?

The unwavering support and encouragement from both the staff and professors have been invaluable throughout this journey. Initially, I was plagued with self-doubt, particularly when confronted with the daunting world of coding, in which I had no experience. The transition from a research biology lab to this unfamiliar environment only compounded my fear. Yet, the professors went above and beyond, extending a guiding hand by inviting alumni to share their own experiences and offering clear, concise pathways to success. Their guidance proved indispensable.

As I reflect on my progress after the first year, I can confidently say that I've grown significantly more assured. Though occasional hesitations and setbacks still arise, especially in the realm of job hunting, I am fortified by the robust support system they've provided. With their unwavering backing, I feel empowered to navigate my path forward with newfound clarity and determination.

What advice do you have for incoming students interested in Health Data Science?

Aim for greatness. Embrace curiosity and never be afraid of seeking clarity. Each of you has journeyed far from your home to immerse yourselves in one of the most rapidly advancing and fiercely competitive domains. Spare no effort in your pursuit of success, yet let integrity and purpose guide every action; leave nothing left unsaid.

What are your Capstone Experience plans and how do you think it will help you prepare for the job hunt?

Having spent three years in a research laboratory conducting experiments, I am now seeking a new direction for my capstone project. My desire is to pursue an internship within the data management division of a hospital or research institution to truly expand my expertise as well as gain novel, invaluable experience which will help with my job search post-graduation.

About the Health Data Science, M.S.

Saint Louis University's Master of Science program in health data science is designed to prepare students for a career in today's data-driven health care industry. Successful data scientists possess an artful ability to blend, synthesize and communicate data for use in clinical decisions by patients and providers, as well as advancing quality improvement efforts across health systems.

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The mission of the Department of Health and Clinical Outcomes Research is to serve as the collaborative bridge between divisions, departments, and colleges/schools across medicine and the health sciences to support methodologically rigorous research to solve complex health problems. The Department of Health and Clinical Outcomes Research is a scholarly community of faculty, staff and students committed to strengthening the delivery and outcomes of medical care through education and training programs, innovative research, and consulting services.

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Race Is Central to Identity for Black Americans and Affects How They Connect With Each Other

Many learn about ancestors, u.s. black history from family, table of contents.

The importance of being Black for connections with other Black people
The importance of Blackness for knowing family history and U.S. Black history
Younger Black people are less likely to speak to relatives about ancestors
Black Americans differ by party on measures of identity and connection
The importance of race, ancestry and place to personal identity
The importance of gender and sexuality to personal identity
Black Americans and connectedness to other Black people
Intra-racial connections locally, nationally and globally
How Black Americans learn about their family history
Most Black adults say their ancestors were enslaved, but some are not sure
Most Black adults are at least somewhat informed about U.S. Black history
For many Black adults, where they live shapes how they think about themselves
Acknowledgments
The American Trends Panel survey methodology

A photo of a Black man in a dark blue suit and blue and white checkered button up underneath looking at reflection of himself on a building. (Photo credit: Getty Images)

Pew Research Center conducted this analysis to understand the rich diversity of Black people in the United States and their views of Black identity. This in-depth, robust survey explores differences among Black Americans in views of identity such as between U.S.-born Black people and Black immigrants; Black people living in different regions of the country; and between Black people of different ethnicities, political party affiliations, ages and income levels. The analysis is the latest in the Center’s series of in-depth surveys of public opinion among Black Americans (read the first, “ Faith Among Black Americans ”).

The online survey of 3,912 Black U.S. adults was conducted Oct. 4-17, 2021. The survey includes 1,025 Black adults on Pew Research Center’s American Trends Panel (ATP) and 2,887 Black adults on Ipsos’ KnowledgePanel. Respondents on both panels are recruited through national, random sampling of residential addresses.

Recruiting panelists by phone or mail ensures that nearly all U.S. Black adults have a chance of selection. This gives us confidence that any sample can represent the whole population (see our Methods 101 explainer on random sampling). Here are the questions used for the survey of Black adults , along with its responses and methodology .

The terms “Black Americans” , “Black people” and “Black adults” are used interchangeably throughout this report to refer to U.S. adults who self-identify as Black, either alone or in combination with other races or Hispanic identity.

Throughout this report, “Black, non-Hispanic” respondents are those who identify as single-race Black and say they have no Hispanic background. “Black Hispanic” respondents are those who identify as Black and say they have Hispanic background. We use the terms “Black Hispanic” and “Hispanic Black” interchangeably. “Multiracial” respondents are those who indicate two or more racial backgrounds (one of which is Black) and say they are not Hispanic.

Respondents were asked a question about how important being Black was to how they think about themselves. In this report, we use the terms “being Black” and “Blackness” interchangeably when referencing responses to this question.

In this report, “immigrant” refers to people who were not U.S. citizens at birth – in other words, those born outside the U.S., Puerto Rico or other U.S. territories to parents who were not U.S. citizens. We use the terms “immigrant” and “foreign-born” interchangeably.

Throughout this report, “Democrat and Democratic leaners” refers to respondents who say in they identify politically with the Democratic Party or are independent but lean toward the Democratic Party. “ Republican and Republican leaners” refers to respondents who identify politically with the Republican Party or are independent but lean toward the Republican Party.

To create the upper-, middle- and lower-income tiers, respondents’ 2020 family incomes were adjusted for differences in purchasing power by geographic region and household size. Respondents were then placed into income tiers: “Middle income” is defined as two-thirds to double the median annual income for the entire survey sample. “Lower income” falls below that range, and “upper income” lies above it. For more information about how the income tiers were created, read the methodology .

No matter where they are from, who they are, their economic circumstances or educational backgrounds, significant majorities of Black Americans say being Black is extremely or very important to how they think about themselves, with about three-quarters (76%) overall saying so.

Pie chart showing most Black adults say being Black is very important to how they see themselves

A significant share of Black Americans also say that when something happens to Black people in their local communities, across the nation or around the globe, it affects what happens in their own lives, highlighting a sense of connectedness. Black Americans say this even as they have diverse experiences and come from an array of backgrounds.

Even so, Black adults who say being Black is important to their sense of self are more likely than other Black adults to feel connected to other groups of Black people. They are also more likely to feel that what happens to Black people inside and outside the United States affects what happens in their own lives. These findings emerge from an extensive new survey of Black U.S. adults conducted by Pew Research Center.

A majority of non-Hispanic Black Americans (78%) say being Black is very or extremely important to how they think about themselves. This racial group is the largest among Black adults , accounting for 87% of the adult population, according to 2019 Census Bureau estimates. But among other Black Americans, roughly six-in-ten multiracial (57%) and Hispanic (58%) Black adults say this.

Black Americans also differ in key ways in their views about the importance of being Black to personal identity. While majorities of all age groups of Black people say being Black shapes how they think about themselves, younger Black Americans are less likely to say this – Black adults ages 50 and older are more likely than Black adults ages 18 to 29 to say that being Black is very or extremely important to how they think of themselves. Specifically, 76% of Black adults ages 30 to 49, 80% of those 50 to 64 and 83% of those 65 and older hold this view, while only 63% of those under 30 do.

Chart showing non-Hispanic Black adults most likely to say being Black is extremely or very important to how they see themselves

Black adults who identify with or lean toward the Democratic Party are more likely than those who identify with or lean toward the Republican Party to say being Black is important to how they see themselves – 86% vs. 58%. And Black women (80%) are more likely than Black men (72%) to say being Black is important to how they see themselves.

Still, some subgroups of Black Americans are about as likely as others to say that being Black is very or extremely important to how they think about themselves. For example, U.S.-born and immigrant Black adults are about as likely to say being Black is important to how they see their identity. However, not all Black Americans feel the same about the importance of being Black to their identity – 14% say it is only somewhat important to how they see themselves while 9% say it has little or no impact on their personal identity, reflecting the diversity of views about identity among Black Americans.

Bar chart showing that about half of Black adults say their fates are strongly linked with other Black people in the U.S.

Beyond the personal importance of Blackness – that is, the importance of being Black to personal identity – many Black Americans feel connected to each other. About five-in-ten (52%) say everything or most things that happen to Black people in the United States affect what happens in their own lives, with another 30% saying some things that happen nationally to Black people have a personal impact. And 43% say all or most things that happen to Black people in their local community affect what happens in their own lives, while another 35% say only some things in their lives are affected by these events. About four-in-ten Black adults in the U.S. (41%) say they feel their fates are strongly linked to Black people around the world, with 36% indicating that some things that happen to Black people around the world affect what happens in their own lives.

The survey also asked respondents how much they have in common with different groups of Black Americans. Some 17% of Black adults say they have everything or most things in common with Black people who are immigrants. But this sense of commonality differs sharply by nativity: 14% of U.S.-born Black adults say they have everything or most things in common with Black immigrants, while 43% of Black immigrants say the same. Conversely, only about one-in-four Black immigrants (26%) say they have everything or most things in common with U.S.-born Black people, a share that rises to 56% among U.S.-born Black people themselves.

About one-third of Black Americans (34%) say they have everything or most things in common with Black people who are poor, though smaller shares say the same about Black people who are wealthy (12%). Relatively few Black Americans (14%) say they have everything or most things in common with Black people who identify as lesbian, gay, bisexual, transgender or queer (LGBTQ). However, a larger share of Black Americans (25%) say they have at least some things in common with Black people who identify as LGBTQ. All these findings highlight the diversity of the U.S. Black population and how much Black people feel connected to each other.

These are among the key findings from a recent Pew Research Center survey of 3,912 Black Americans conducted online Oct. 4-17, 2021. This report is the latest in a series of Pew Research Center studies focused on describing the rich diversity of Black people in the United States.

The nation’s Black population stood at 47 million in 2020 , making up 14% of the U.S. population – up from 13% in 2000. While the vast majority of Black Americans say their racial background is Black alone (88% in 2020), growing numbers are also multiracial or Hispanic. Most were born in the U.S. and trace their roots back several generations in the country, but a growing share are immigrants (12%) or the U.S.-born children of immigrant parents (9%). Geographically, while 56% of Black Americans live in the nation’s South , the national Black population has also dispersed widely across the country.

It is this diversity – among U.S.-born Black people and Black immigrants; between Black people who live in different regions; and across different ethnicities, party affiliations, ages and income levels – that this report explores. The survey also provides a robust opportunity to examine the importance of race to Black Americans’ sense of self and their connections to other Black people.

Bar chart showing Black Americans who say being Black is important to them are more likely to feel connected to other Black people

The importance of being Black to personal identity is a significant factor in how connected Black Americans feel toward each other. Those who say that being Black is a very or extremely important part of their personal identity are more likely than those for whom Blackness is relatively less important to express a sense of common fate with Black people in their local communities (50% vs. 17%), in the United States overall (62% vs. 21%), and even around the world (48% vs. 18%).

They are also more likely to say that they have everything or most things in common with Black people who are poor (37% vs. 23%) and Black immigrants (19% vs. 9%). Even so, fewer than half of Black Americans, no matter how important Blackness is to their personal identity, say they have everything or most things in common with Black people who are poor, immigrants or LGBTQ.

The new survey also explores Black Americans’ knowledge about their family histories and the history of Black people in the United States, with the importance of Blackness linked to greater knowledge.

Bar chart showing Black adults who say being Black is important to them are more likely to learn about their ancestors from relatives

Nearly six-in-ten Black adults (57%) say their ancestors were enslaved either in the U.S. or another country, with nearly all who say so (52% of the Black adults surveyed) saying it was in the U.S., either in whole or in part. Black adults who say that being Black is a very or extremely important part of how they see themselves (61%) are more likely than those for whom being Black is less important (45%) to say that their ancestors were enslaved. In fact, Black adults for whom Blackness is very or extremely important (31%) are less likely than their counterparts (42%) to say that they are not sure if their ancestors were enslaved at all.

When it comes to learning more about their family histories, Black adults for whom Blackness is very or extremely important (81%) are more likely than those for whom Blackness is less important (59%) to have spoken to their relatives. They are about as likely to have researched their family’s history online (36% and 30%, respectively) and to have used a mail-in DNA service such as AncestryDNA or 23andMe (15% and 16%) to learn more about their ancestry.

The importance of Blackness also figures prominently into how informed Black Americans feel about U.S. Black history. Black adults who say Blackness is a significant part of their personal identity are more likely than those for whom Blackness is less important to say that they feel very or extremely informed about U.S. Black history (57% vs. 29%). Overall, about half of Black Americans say they feel very or extremely informed about the history of Black people in the United States.

Among Black adults who feel at least a little informed about U.S. Black history, the sources of their knowledge also differ by the importance of Blackness to personal identity. Nearly half of Black adults for whom Blackness is very or extremely important (48%) say they learned about Black history from their families and friends, making them more likely to say so than Black adults for whom Blackness is less important (30%). Similarly, those who say being Black is important to their identity are more likely than those who did not say this to have learned about Black history from nearly every source they were asked about, be it media (33% vs. 22%), the internet (30% vs. 18%) or college, if they attended (26% vs. 14%). The only source for which both groups were about equally likely to say they learned about Black history was their K-12 schools (24% and 21%, respectively).

Overall, among Black Americans who feel at least a little informed about U.S. Black history, 43% say they learned about it from their relatives and friends, 30% say they learned about it from the media, 27% from the internet, and 24% from college (if they attended) and 23% from K-12 school.

Black adults under 30 years old differ significantly from older Black adults in their views on the importance of Blackness to their personal identity. However, Black adults also differ by age in how they pursue knowledge of family history, how informed they feel about U.S. Black history, and their sense of connectedness to other Black people.

Chart showing younger Black adults less likely than their elders to feel informed about U.S. Black history

Black adults under 30 (50%) are less likely than those 65 and older (64%) to say their ancestors were enslaved. In fact, 40% of Black adults under 30 say that they are not sure whether their ancestors were enslaved. Black adults in the youngest age group (59%) are less likely than the oldest (87%) to have spoken to their relatives about family history or to have used a mail-in DNA service to learn about their ancestors (11% vs. 21%). They are only slightly less likely to have conducted research on their families online (26% vs. 39%).

Black adults under 30 have the lowest share who say they feel very or extremely informed about the history of Black people in the United States (40%), compared with 60% of Black adults 65 and older and about half each of Black adults 50 to 64 (53%) and 30 to 49 (51%). In fact, Black adults under 30 are more likely than those 50 and older to say they feel a little or not at all informed about Black history. While Black adults are generally most likely to cite family and friends as their source for learning about Black history, the share under 30 (38%) who also cite the internet as a source of information is higher than the shares ages 50 to 64 (22%) and 65 and older (14%) who say this.

These age differences persist in the sense of connectedness that Black Americans have with other Black people. Black adults under 30 are less likely than those 65 and older to say that everything or most things that happen to Black people in the United States will affect their own lives. This youngest group is also less likely than the oldest to have this sense of common fate with Black people in their local community. One exception to this pattern occurs when Black adults were asked how much they had in common with Black people who identify as LGBTQ. Black adults under 30 (21%) were considerably more likely than those 65 and older (10%) to say they have everything or most things in common with Black people who identify as LGBTQ.

Black Democrats and Republicans differ on how important Blackness is to their personal identities. However, there are also partisan gaps when it comes to their connectedness to other Black people. 1

Bar chart showing Black Democrats more likely than Republicans to say what happens to other Black people in the U.S. will affect their own lives

Black Democrats and those who lean to the Democratic Party are more likely than Black Republicans and Republican leaners to say that everything or most things that happen to Black people in the United States (57% vs. 39%) and their local communities (46% vs. 30%) affect what happens in their own lives. However, Black Republicans (24%) are more likely than Black Democrats (14%) to say that they have everything or most things in common with Black people who are LGBTQ. They are also more likely than Black Democrats to say they have everything or most things in common with Black people who are wealthy (25% vs. 11%).

When it comes to knowledge of family and racial histories, Black Democrats and Republicans do not differ. Democrats (59%) are just as likely as Republicans (54%) to know that their ancestors were enslaved. Nearly 80% of Black adults from both partisan coalitions say they have spoken to their relatives about their family history. Similar shares have also researched their family histories online and used mail-in DNA services.

Black Democrats are also not significantly more likely than Black Republicans to say they feel very or extremely informed about U.S. Black history (53% vs. 45%). And among those who feel at least a little informed about U.S. Black history, Democrats and Republicans are about equally likely to say they learned it from family and friends (45% vs. 38%).

Place is a key part of Black Americans’ personal identities

The majority of Black adults who live in the United States were born there, but an increasing portion of the population is comprised of immigrants. Of those immigrants, nearly 90% were born in the Caribbean or Africa . Regardless of their region of birth, 58% of Black adults say the country they were born in is very or extremely important to how they think about themselves. A smaller share say the same about the places where they grew up (46%).

Bar chart showing half of Black adults say where they currently live is an important part of their identity

Black adults also feel strongly about their current communities. About half of Black adults (52%) say that where they currently live is very or extremely important to how they think about themselves. And when it comes to the quality of their neighborhoods, 76% of Black adults rate them as at least good places to live, including 41% who say the quality of their community is very good or excellent.

Still, Black adults say there are concerning issues in the communities they live in. When asked in an open-ended question to list the issue that was most important in their neighborhoods, nearly one-in-five Black adults listed issues related to violence or crime (17%). Smaller shares listed other points of concern such as economic issues like poverty and homelessness (11%), housing (7%), COVID-19 and public health (6%), or infrastructure issues such as the availability of public transportation and the conditions of roads (5%).

While nearly one-in-five Black Americans (17%) say that individual people like themselves should be responsible for solving these problems, they are most likely to say that local community leaders should address these issues (48%). Smaller shares say the U.S. Congress (12%), the U.S. president (8%) or civil rights organizations (2%) bear responsibility.

According to the survey, 80% of Black adults say they identify with or lean toward the Democratic Party, 10% say the same of the Republican Party and 10% did not answer the question or indicated that they did not affiliate with either party. Among Black registered voters, the survey finds 85% identify with or lean toward the Democratic Party, 10% identify with or lean toward the Republican Party and 5% did not answer the question or indicated that they did not affiliate with either party. ↩

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Research showcases Indigenous stewardship’s role in forest ecosystem resilience

CORVALLIS, Oregon – Oregon State University researchers have teamed with the Karuk Tribe to create a novel computer simulation model that showcases Indigenous fire stewardship’s role in forest ecosystem health.

Western scientists and land managers have become increasingly cognizant of cultural burning but its extent and purpose are generally absent from fire modeling research, said Skye Greenler, who led the partnership when she was a graduate research fellow in the OSU College of Forestry.

“We developed this project in collaboration with the Karuk Tribe to explore the impact of cultural burning at a landscape scale in a completely new way,” she said. “The information that went into this model is not new at all – it’s been held by Karuk Tribal members for millennia – but we developed new methods to bring the knowledge together and display it in a way that showcases the extent of Indigenous cultural stewardship across this landscape.”

Greenler and collaborators including Chris Dunn and John Bailey of Oregon State say that understanding the interactions among humans, fire processes and pathways towards coexistence with wildfire has become increasingly urgent as the social, ecological and economic impacts of fire have intensified in recent years.

The research focused on 1,000 square miles of Karuk Aboriginal Territory in the western Klamath Mountains of northern California. Working with the Karuk Tribe Department of Natural Resources, OSU scientists developed historical estimates for cultural ignition locations, frequency and timing. Statistical parameters were collaboratively developed and honed with Tribal members and knowledge holders using interviews, historical and contemporary maps, ethnographies, recent ecological studies and generational knowledge.

Published in Ecological Applications, the findings show that before the arrival of European colonizers, cultural burning was extensive across the landscape, with an estimated 6,972 cultural ignitions occurring annually, averaging about 6.5 ignitions per year for each Indigenous fire steward.

The researchers, who included scientists from the University of Washington, the Mid-Klamath Watershed Council, and the U.S. Forest Service’s Pacific Northwest and Pacific Southwest research stations, found that the timing and location of burning was often guided by the ecology of specific cultural resources, fuel receptivity, seasonal movement patterns and spiritual practices.

“The ignition characteristics we document align closely with data on historical fire regimes and vegetation but differ substantially from the location and timing of the ignitions happening now,” Greenler said. “This work shows the importance of cultural burning for developing and maintaining the ecosystems present at the time of colonization and underscores the need to work collaboratively with Indigenous communities to restore ecocultural processes.”

Northern California’s western Klamath Mountains are a diverse and highly fire- prone ecosystem that historically burned frequently at low or moderate severity but have recently experienced many extensive or severe wildfires, the researchers point out.

“Collaboratively integrating western and Indigenous fire science and knowledge systems in this research will help reinstate fire on this landscape to achieve socioecological resource values with benefits both to tribes and the public,” said the Forest Service’s Frank Lake, a Karuk Tribal descendant who earned a doctorate from the OSU College of Forestry.

The study area is one of many fire-prone landscapes in the western United States that have a long history of cultural burning, defined as the purposeful use of fire by an Indigenous group to promote food, medicinal and material resources. Cultural burning also alters wildfire risk and how fires spread.

“It would be incredible to go back in time and experience the study landscape with open oak groves, hillsides of high quality and abundant first foods, frequent, small cultural burns in the mornings or late afternoons, and little fear of large wildfires when dry lightning storms passed over the mountains in August,” Greenler said. “A recent shift within western scientific and management communities is towards a greater interest in supporting Indigenous fire stewardship practices that better balance relationships between people and fire.”

The increased interest follows decades of work from Indigenous communities to assert sovereign rights to land stewardship, emphasize the importance of cultural burning and build collaborative relationships and policies that integrate cultural burning into research, management and restoration practices, the scientists say.

“The lens with which scientists view data in observational scientific studies affects their interpretation of the results,” Dunn said. “As our acceptance of Indigenous Knowledge grows, we are experiencing a shift in our interpretation of fire regimes, ecological outcomes and humans in these systems. This does not invalidate previous studies but builds upon them for a more accurate understanding of history, and with that, where we are going in the future.”

Indigenous fire stewardship is deeply place-based, Greenler said, meaning the collaborators’ findings are not directly transferable to other landscapes, but the process that was used to develop and model estimates of cultural ignitions could “absolutely be applied” in other landscapes to better understand the impacts and patterns of cultural burning.

“It was a real pleasure to work on this project,” said Bill Tripp, director of natural resources and environmental policy for the Karuk Tribe. “Being able to incorporate Karuk Indigenous Knowledge, practice and belief systems into a product that can help assess historic fire regimes in a way that protects our proprietary information and locational data in regard to the site-specific resources we are working to enhance is of vital importance to our ecocultural revitalization efforts.”

Greenler stresses the importance of remembering that cultural burning remains an important practice on many landscapes today, including in northern California. She would like the collaboration with the Karuk Tribe to help provide information for society to use in restoring balanced human-fire relationships – which in some ways may emulate historical practices and in other ways may not, she said.

“I hope for all of us that we can continue to learn from Indigenous communities, uplift Indigenous Knowledge and sovereignty, and work towards a future where we can better co-exist with fire on our landscapes,” Greenler said.

College of Forestry

About the OSU College of Forestry: For a century, the College of Forestry has been a world class center of teaching, learning and research. It offers graduate and undergraduate degree programs in sustaining ecosystems, managing forests and manufacturing wood products; conducts basic and applied research on the nature and use of forests; and operates more than 15,000 acres of college forests.

Steve Lundeberg, 541-737-4039, [email protected]

Skye Greenler, [email protected] ; Chris Dunn, 541-737-1194, [email protected]

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Annual assessment academy, aaa registration is now open click here to apply.

The purpose of the Howard University Annual Assessment Academy is to engage faculty and staff in the assessment of academic and administrative assessment reports and to offer professional development opportunities related to assessment. The Annual Assessment Academy will welcome colleagues to the assessment community and provide learning opportunities related to assessment foundations, how to utilize learning outcomes in the assessment process, and sharing assessment results.

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Throughout the academic year, all academic programs and many administrative programs submit an assessment report. These reports include a mission statement, a set of learning outcomes, appropriate measures to track student learning, targets, results, and suggested improvements. Using a rubric, faculty will rate reports over a four-week period. Colleagues will be trained by attending an informational meeting and participating in a calibration exercise. Trainings will be recorded and made available via Canvas.

How to Participate

If you are interested in participating in the Annual Assessment Academy, please complete the short application linked below. We hope to invite all participants who apply to participate, but may not be able to accommodate all who wish to participate depending on the number of applications.

To apply, click here.

Qualifications

All Howard University full-time and part-time faculty, and staff with assessment responsibilities are encouraged to participate.

Important Date(s)

The Annual Assessment Academy application will open April 22, 2024 and close on June 3, 2024.

Academy invitees will be informed on June 10, 2024 .

Trainings and calibration exercises will be held on July 8th (administrative) and 9th (academic) . While we ask that participants attend synchronously, they will be recorded with the aim of ensuring that participants can participate asynchronously.

The assessment window for assessment reports and learning activities will be open from July 1, 2024 until July 31, 2024 .

April 19, 2024

Related Announcements

SUMMARY: Findings of research misconduct have been made against Gian-Stefano Brigidi, Ph.D. (Respondent), who was a Postdoctoral Fellow, Department of Neurobiology, University of California San Diego (UCSD), and was an Assistant Professor, Department of Neurobiology, University of Utah (UU). Respondent engaged in research misconduct in research supported by U.S. Public Health Service (PHS) funds, specifically National Institute of Mental Health (NIMH), National Institutes of Health (NIH), grant F32 MH110141, National Human Genome Research Institute (NHGRI), NIH, grant T32 HG000044, National Institute of Neurological Disorders and Stroke (NINDS), NIH, grant P30 NS047101, and National Library of Medicine (NLM), NIH, grant T15 LM011271. The research was included in grant applications submitted for PHS funds, specifically R01 NS131809-01, R01 NS133405-01, DP2 NS127276-01, and R01 NS111162-01A1 submitted to NINDS, NIH, and R21 MH121860-01, R21 MH121860-01A1, F32 MH110141-01, F32 MH110141-01A1, and F32 MH110141-01AS1 submitted to NIMH, NIH. The administrative actions, including supervision for a period of five (5) years, were implemented beginning on March 24, 2024, and are detailed below.

FOR FURTHER INFORMATION CONTACT: Sheila Garrity, JD, MPH, MBA, Director, Office of Research Integrity, 1101 Wootton Parkway, Suite 240, Rockville, MD 20852, (240) 453-8200

SUPPLEMENTARY INFORMATION: Notice is hereby given that the Office of Research Integrity (ORI) has taken final action in the following case:

Gian-Stefano Brigidi, Ph.D., University of California San Diego (UCSD) and University of Utah (UU): Based on the report of an assessment conducted by UU, and inquiry conducted by UCSD, the Respondent's admission, and additional analysis conducted by ORI in its oversight review, ORI found that Dr. Gian-Stefano Brigidi, former Postdoctoral Fellow in the Department of Neurobiology, UCSD, and former Assistant Professor, Department of Neurobiology, UU, engaged in research misconduct in research supported by PHS funds, specifically NIMH, NIH, grant F32 MH110141, NHGRI, NIH, grant T32 HG000044, NINDS, NIH, grant P30 NS047101, and NLM, NIH, grant T15 LM011271. The research was included in grant applications submitted for PHS funds, specifically R01 NS131809-01, R01 NS133405-01, DP2 NS127276-01, and R01 NS111162-01A1 submitted to NINDS, NIH, and R21 MH121860-01, R21 MH121860-01A1, F32 MH110141-01, F32 MH110141-01A1, and F32 MH110141-01AS1 submitted to NIMH, NIH.

ORI found that Respondent engaged in research misconduct by knowingly or intentionally falsifying and/or fabricating data and results by manipulating primary data values to falsely increase the n-value, manipulating fluorescence micrographs and their quantification graphs to augment the role of ITFs in murine hippocampal neurons, and/or manipulating confocal images that were obtained through different experimental conditions in twenty (20) figures of one (1) published paper and four (4) PHS grant applications, one (1) panel of one (1) poster, and seven (7) slides of one (1) presentation:

Genomic Decoding of Neuronal Depolarization by Stimulus-Specific NPAS4 Heterodimers. Cell . 2019 Oct 3;179(2):373-391.e27. doi: 10.1016/j.cell.2019.09.004 (hereafter referred to as “ Cell 2019”).
Genomic mechanisms linking neuronal activity history with present and future functions. Poster for “The Brigidi Lab--a neuronal activity lab in the Department of Neurobiology at the University of Utah” (hereafter referred to as the “UU Department of Neurobiology poster”).
Decoding neural circuit stimuli into spatially organized gene regulation. Presentation presented to the UU Department of Neurobiology & Anatomy on January 23, 2020 (hereafter referred to as “UU Department of Neurobiology presentation”).
DP2 NS127276-01, “Decoding neuronal activity history at the genome through the spatially segregated inducible transcription factors,” submitted to NINDS, NIH, on August 20, 2020, Awarded Project Dates: September 15, 2021-August 1, 2023.
F32 MH110141-01, “Regulation of excitatory-inhibitory balance by the local translation of the immediate early gene Npas4,” submitted to NIMH, NIH, on August 10, 2015.
F32 MH110141-01A1, “Regulation of Excitatory-Inhibitory Balance by Local Translation of the Immediate Early Gene Npas4,” submitted to NIMH, NIH, on December 8, 2015, Awarded Project Dates: August 1, 2016-July 31, 2018.
F32 MH110141-01A1S1, “Regulation of Excitatory-Inhibitory Balance by Local Translation of the Immediate Early Gene Npas4,” submitted to NIMH, NIH, on December 8, 2016, Awarded Project Dates: December 1, 2016-July 31, 2017.

The falsified and/or fabricated data also were included in twenty-three (23) figures in the following five (5) PHS grant applications:

R01 NS131809-01, “Regulation and function of dendritic mRNA that encodes the neuronal transcription factor Npas4,” submitted to NINDS, NIH, on June 6, 2022.
R01 NS133405-01, “Assessing the impact of the inducible transcription factor NPAS4 on spatial tuning in the mouse hippocampus,” submitted to NINDS, NIH, on October 5, 2022.
R01 NS111162-01A1, “Molecular and cellular mechanisms underlying activity dependent gene regulation in neurons,” submitted to NINDS, NIH, on March 5, 2019, Awarded Project Dates: December 15, 2019-November 30, 2024.
R21 MH121860-01, “Identification of dendritically-localized transcription factor mRNAs as a mechanism for conveying multiple streams of information to the nucleus,” submitted to NIMH, NIH, on February 19, 2019.
R21 MH121860-01A1, “Identification of dendritically-localized transcription factor mRNAs,” submitted to NIMH, NIH, on March 16, 2020.

Specifically, ORI found that:

Respondent knowingly or intentionally combined two to three real data sets and two to five fabricated data sets to falsely increase the n-values reported in:
Figures 1B, 1D, 1E, 1G, 1I, 1J, 1M-1O, 1Q-1T, S2B-S2D, S2F-S2H, S3I, S3L, S3M, and S6H of Cell 2019 and Slides 6-10, 13, and 28 of the UU Department of Neurobiology presentation representing the quantification of NPAS4 immunohistofluorescence.
Figures 2H, 2I, 2K, 2P, 3C, 3E, 4D-4G, 4K-4N, 4P-4Q, S3G, S5B, and S5C of Cell 2019 representing the quantification of Npas4 mRNA or puro-PLA puncta.
Figures S1E, S1G, and S1H of Cell 2019 representing the quantification of whole-cell clamp recordings of CA1 PN.
Figures 2 (lower panel) and 3c of F32 MH110141-01, Figures 1g, 2b, 2d, and 4 of F32 MH110141-01A1S1, and Figures 1g, 2b, 2d, and 4 of F32 MH110141-01A1 representing time points of NPAS4 quantification after no stimulation or post-stimulation in the alveus or radiatum SR, SO, SP, SLM, with or without the addition of an inhibitor.
Respondent knowingly or intentionally manipulated confocal images that were obtained through different experimental conditions in:
Figures 1A, 1C, and 1F of Cell 2019 and Slides 6-9 of the UU Department of Neurobiology presentation representing confocal images of hippocampal slices immunostained for NPAS4 and Neu.
Figures S2A and S2E of Cell 2019 by manipulating and misrepresenting the GFP signals as NPAS4 signals in wildtype mice.
Figures 1H, 1L, 1P, S3K, S6F, and S6G of Cell 2019 and Slides 9 and 28 of the UU Department of Neurobiology presentation by manipulating the raw images of hippocampal slices immunostained with NPAS4 and Neu and/or ARNT1 or ARNT2 by generating a mask of NPAS4 immunofluorescent signal through GFP signal from tissue obtained from Thy1-GFP mice to intentionally enhance the appearance of the dendritic NPAS4 signal.
Figures S6F and S6G of Cell 2019 by manipulating the raw images of hippocampus slices by overlaying a GFP channel over ARNT1 channel and using the multiply feature in Photoshop to restrict ARNT1 signal through GFP to enhance the ARNT1 signal in three panels.
Slides 7, 9, and 28 of the UU Department of Neurobiology presentation by manipulating six images representing post-stimulation with different time points by using a GFP mask overlaid on top of raw NPAS4 immunofluorescence.
Figure 4 of DP2 NS127276-01 and panel 1 of the UU Department of Neurobiology poster representing twelve images in columns 2-4 labeled EGR, FOS, ATF4 by mislabeling the microscope images as immunofluorescent stained with antibodies against EGR, FOS, and ATF4 when they actually were stained with anti-NPAS4 and selected images to support the immunofluorescence data in the ITF induction graphs.
Figure 5 of DP2 NS127276-01 representing two confocal images in the far-right column by intentionally and selectively enhancing the brightness of the anti-NPAS4 immunofluorescent channel within the dashed box and left brightness unchanged in surrounding areas of the images.
Figure 6 of DP2 NS127276-01 in twelve images in columns 2-5 labeled Egr2, Fos, and Atf4 by intentionally mislabeling the microscope images as RNA in situ hybridization with probes against Egr2, Fos, and Atf4 when they actually were stained with NPAS4 probes and intentionally selecting and quantifying images in the quantification graphs to support the conclusions of the grant application.
Respondent knowingly or intentionally manipulated the fluorescence micrographs and their quantification graphs to augment the role of ITFs in murine hippocampal neurons in Figures 2B-2G, 2J, 2L-2O, 3B, 3D, 3F-3H, 4C, 4J, 4O, S1A-S1D, S1F, S1I-S1J, S3A-S3F, S3H, S3J, S3N-S3T, S5D-S5G, and S6A-S6E of Cell 2019; the falsified/fabricated data also were included in Figures 2B-2H, 3, 4B-4E, and 5C-5G of R21 MH121860-01, Figures 2, 3B-3E, 4B-4C, 4E-4I, and 5B-5E of R21 MH121860-01A1, Figures 3, 5, 6B, 7, 8, 10B-10D, 11A-11C, and 11E-11F in R01 NS131809-01, Figure 8 of R01 NS133405-01, and Figures 3B-3C, 3E-3I, 4B-4I, 5, 9, 10B-10E, and 11-12 of R01 NS111162-01A1.

Respondent entered into a Voluntary Settlement Agreement (Agreement) and voluntarily agreed to the following:

Respondent will have his research supervised for a period of five (5) years beginning on March 24, 2024 (the “Supervision Period”). Prior to the submission of an application for PHS support for a research project on which Respondent's participation is proposed and prior to Respondent's participation in any capacity in PHS-supported research, Respondent will submit a plan for supervision of Respondent's duties to ORI for approval. The supervision plan must be designed to ensure the integrity of Respondent's research. Respondent will not participate in any PHS-supported research until such a supervision plan is approved by ORI. Respondent will comply with the agreed-upon supervision plan.
A committee of 2-3 senior faculty members at the institution who are familiar with Respondent's field of research, but not including Respondent's supervisor or collaborators, will provide oversight and guidance for a period of five (5) years from the effective date of the Agreement. The committee will review primary data from Respondent's laboratory on a quarterly basis and submit a report to ORI at six (6) month intervals setting forth the committee meeting dates and Respondent's compliance with appropriate research standards and confirming the integrity of Respondent's research.
The committee will conduct an advance review of each application for PHS funds, or report, manuscript, or abstract involving PHS-supported research in which Respondent is involved. The review will include a discussion with Respondent of the primary data represented in those documents and will include a certification to ORI that the data presented in the proposed application, report, manuscript, or abstract are supported by the research record.
During the Supervision Period, Respondent will ensure that any institution employing him submits, in conjunction with each application for PHS funds, or report, manuscript, or abstract involving PHS-supported research in which Respondent is involved, a certification to ORI that the data provided by Respondent are based on actual experiments or are otherwise legitimately derived and that the data, procedures, and methodology are accurately reported and not plagiarized in the application, report, manuscript, or abstract.
If no supervision plan is provided to ORI, Respondent will provide certification to ORI at the conclusion of the Supervision Period that his participation was not proposed on a research project for which an application for PHS support was submitted and that he has not participated in any capacity in PHS-supported research.
During the Supervision Period, Respondent will exclude himself voluntarily from serving in any advisory or consultant capacity to PHS including, but not limited to, service on any PHS advisory committee, board, and/or peer review committee.
Respondent will request that the following paper be corrected or retracted:
Cell . 2019 Oct 3;179(2):373-391.e27. doi: 10.1016/j.cell.2019.09.004.

Respondent will copy ORI and the Research Integrity Officer at UCSD on the correspondence with the journal.

Please direct all inquiries to:

Sheila Garrity, JD, MPH, MBA, Director

Office of Research Integrity

1101 Wootton Parkway, Suite 240

Rockville, MD 20852

(240) 453-8200

Note: For help accessing PDF, RTF, MS Word, Excel, PowerPoint, Audio or Video files, see Help Downloading Files .

Ancient monument 'unlike anything archaeologists have seen before' unearthed in France

A sprawling monument spanning centuries or even millennia has been unearthed in eastern France , in what archaeologists are hailing as an “unprecedented” discovery.

A team from the country’s National Institute for Preventive Archaeological Research (Inrap) were excavating an area of Marliens, about 20km east of Dijon, when they found the remnants of settlements spanning from the Neolithic Age (between 10000BC and 2200BC) and the Iron Age (1200BC to 550BC).

The oldest occupation – meaning a layer of remains left by a single culture – was the most intriguing to the experts.

It featured an eight metre (26-foot)-long "horseshoe" enclosure attached to a circular structure measuring 11 metres (36 feet) in diameter, with another open enclosure alongside that.

All three structures are believed to be from the same time period and a layer of gravel in the side enclosures indicated that a fence had once stood there.

And yet, the Inrap experts currently have no idea what the purpose of the enclosures was.

“This type of monument seems unprecedented and currently no comparison [with other sites has been possible],” the researchers wrote in a press release (in French).

“The dating still remains uncertain, however, the only artefacts discovered [on the site] correspond to cut flints which would suggest [they came from] the Neolithic period,” they added.

“Radiocarbon analyses are now underway to clarify the chronology of this monument.”

Elsewhere in the excavation area, which measures 60,000 square metres (nearly 200,000 square feet) the team found several objects underneath a level of topsoil: seven flint arrowheads; two archer's arm guards; a flint lighter; and a copper alloy dagger.

The team said traces of iron oxide were found on one of the armbands, corresponding to pyrite, an essential element for lighting fires.

They noted that this series of objects most often accompanies a burial, however, they have not yet been able to confirm whether this was indeed such a site.

“Analyses of the composition of the copper alloy of the dagger should make it possible to establish its origin and provide us with information on commercial exchanges at that time,” they noted.

In addition, the archaeologists unearthed several wells dating back to the early Bronze Age (around 3000BC), and an ancient cemetery “characterised by the discovery of six cremations dating from the First Iron Age”.

“The urns, covered by a lid, contained a single bone deposit sometimes accompanied by ornaments (bracelets and/or rings in copper alloy and iron),” they said.

Inrap confirmed that analysis of the cremated bones is now underway to determine funerary practices at the time of the burials.

The discovery of the complex leaves many questions to answer, with the experts hoping that studies will reveal the purpose it once served and how the land, and its people, evolved over the ages.

A triple enclosure unearthed in eastern France is like nothing archaeologists have ever seen before

Microsoft Research Blog

Sammo: a general-purpose framework for prompt optimization.

Published April 18, 2024

By Tobias Schnabel , Senior Researcher Jennifer Neville , Partner Research Manager

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SAMMO optimizer diagram showing progression from starting prompt to optimized prompt.

Large language models (LLMs) have revolutionized a wide range of tasks and applications that were previously reliant on manually crafted machine learning (ML) solutions, streamlining through automation. However, despite these advances, a notable challenge persists: the need for extensive prompt engineering to adapt these models to new tasks. New generations of language models like GPT-4 and Mixtral 8x7B advance the capability to process long input texts. This progress enables the use of longer inputs, providing richer context and detailed instructions to language models. A common technique that uses this enhanced capacity is the Retrieval Augmented Generation (RAG) approach. RAG dynamically incorporates information into the prompt based on the specific input example. This process is illustrated in Figure 1, which shows a RAG prompt designed to translate user queries into a domain-specific language (DSL), also known as semantic parsing.

A table showing an example metaprompt for a semantic parsing task. The underlying metaprompt consists of three larger parts, each of which comes with a variety of aspects that can be optimized. For example, the input example can be rendered using different formats, the few shot example included can be retrieved using various similarity functions, or the task description can be paraphrased.

The example in Figure 1 combines three distinct structures to construct the final prompt. The first structure, the task description, remains static and independent of the input as a result of conventional prompt optimization techniques. However, RAG contains two input-specific structures: the example retriever and the input text itself. These introduce numerous optimization opportunities that surpass the scope of most traditional approaches. Despite previous efforts in prompt optimization, the evolution towards more complex prompt structures has rendered many older strategies ineffective in this new context.

SAMMO: A prompt optimization approach

Download SAMMO

To address these challenges, we developed the Structure-Aware Multi-objective Metaprompt Optimization (SAMMO) framework. SAMMO is a new open-source tool that streamlines the optimization of prompts, particularly those that combine different types of structural information like in the RAG example above. It can make structural changes, such as removing entire components or replacing them with different ones. These features enable AI practitioners and researchers to efficiently refine their prompts with little manual effort.

Central to SAMMO’s innovation is its approach to treating prompts not just as static text inputs but as dynamic, programmable entities— metaprompts . SAMMO represents these metaprompts as function graphs, where individual components and substructures can be modified to optimize performance, similar to the optimization process that occurs during traditional program compilation.

The following key features contribute to SAMMO’s effectiveness:

Structured optimization: Unlike current methods that focus on text-level changes, SAMMO focuses on optimizing the structure of metaprompts. This granular approach facilitates precise modifications and enables the straightforward integration of domain knowledge, for instance, through rewrite operations targeting specific stylistic objectives. Multi-objective search: SAMMO’s flexibility enables it to simultaneously address multiple objectives, such as improving accuracy and computational efficiency. Our paper illustrates how SAMMO can be used to compress prompts without compromising their accuracy.

General purpose application: SAMMO has proven to deliver significant performance improvements across a variety of tasks, including instruction tuning, RAG, and prompt compression.

Microsoft Research Podcast

Collaborators: Renewable energy storage with Bichlien Nguyen and David Kwabi

Dr. Bichlien Nguyen and Dr. David Kwabi explore their work in flow batteries and how machine learning can help more effectively search the vast organic chemistry space to identify compounds with properties just right for storing waterpower and other renewables.

Exploring SAMMO’s impact through use cases

Use case 1: rag optimization .

A common application of LLMs involves translating natural user queries into domain-specific language (DSL) constructions, often to communicate with external APIs. For example, Figure 1 shows how an LLM can be used to map user queries about geography facts to a custom DSL.

In a realistic RAG scenario, SAMMO demonstrates significant performance improvements. To demonstrate this, we conducted experiments across three semantic parsing datasets of varying complexity: GeoQuery, SMCalFlow, and Overnight. Given the often limited availability of data in practical settings, we trained and tested the model on a subsampled dataset (training and retrieval set n=600, test set n=100). We compared SAMMO against a manually designed competitive baseline, using enumerative search within a search space of 24 configurations. This included variations in data formats, the number of few-shot examples, and DSL specifications.

Evaluation

As illustrated in Figure 2, SAMMO improved accuracy across different datasets and backend LLMs in almost all cases, with the most notable gains observed in older generation models. However, even newer models like GPT-4, SAMMO facilitated accuracy improvements exceeding 100 percent.

A series of four bar charts showing the performance of SAMMO on semantic parsing tasks. SAMMO achieves substantial improvements for most backend models and datasets.

Use case 2: Instruction tuning

Instruction tuning addresses the optimization of static instructions given to LLMs that provide the goal and constraints of a task. To show that SAMMO extends beyond many previous prompt tuning methods, we applied this conventional setting.

To align with previous research, we used eight zero-shot BigBench classification tasks where the baseline prompt for GPT-3.5 achieved an accuracy of less than 0.9. We compared it against Automatic Prompt Optimization (APO) and GrIPS, applying open-source models Mixtral 7x8B and Llama-2 70B, alongside GPT-3.5 as backend LLMs. We did not include GPT-4 due to minimal improvement potential identified in pilot experiments. The results, shown in Figure 3, demonstrate that SAMMO outperformed all baselines regardless of the backend model, proving its effectiveness with even more complex metaprompts.

A series of three bar charts comparing the accuracy of different methods on instruction tuning. SAMMO matches or exceeds the performance of competing methods for instruction tuning on classification tasks.

Implications and looking forward

SAMMO introduces a new and flexible approach to optimize prompts for specific requirements. Its design works with any LLM, and it features versatile components and operators suitable for a broad range of applications.

We are excited to integrate and apply SAMMO to the components and pipelines behind AI-powered assistant technologies. We also hope to establish a user-driven community centered around SAMMO, where people can exchange best practices and patterns, and encourage the expansion of the existing set of search operators.

Related publications

Prompts as programs: a structure-aware approach to efficient compile-time prompt optimization, meet the authors.

Tobias Schnabel

Senior Researcher

Jennifer Neville

Partner Research Manager

Continue reading

Improving LLM understanding of structured data and exploring advanced prompting methods

First page of the "Learning Hierarchical Prompt with Structured Linguistic Knowledge for Language Models" publication to the right of the AAAI conference on a blue and purple gradient background

Structured knowledge from LLMs improves prompt learning for visual language models

LLMLingua: Innovating LLM efficiency with prompt compression

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DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

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The purpose of the Howard University Annual Assessment Academy is to engage faculty and staff in the assessment of academic and administrative assessment reports and to offer professional development opportunities related to assessment. ... Institutional Research and Assessment (IRA) Administration Building, Suite G20 Washington, D.C. 20059 ...
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Purpose. SUMMARY: Findings of research misconduct have been made against Gian-Stefano Brigidi, Ph.D. (Respondent), who was a Postdoctoral Fellow, Department of Neurobiology, University of California San Diego (UCSD), and was an Assistant Professor, Department of Neurobiology, University of Utah (UU). ... and was an Assistant Professor ...
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SAMMO: A general-purpose framework for prompt optimization
General purpose application: SAMMO has proven to deliver significant performance improvements across a variety of tasks, including instruction tuning, RAG, and prompt compression. Spotlight: Event Series. Microsoft Research Forum. ... To align with previous research, we used eight zero-shot BigBench classification tasks where the baseline ...

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What is Research? – Purpose of Research

What is Research

What is the Purpose of Research

Characteristics of Research

Types of Research

Basic Research

Applied Research

Methods of Research

Qualitative Research

Quantitative Research

What does Research Involve?

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What is Research: Definition, Methods, Types & Examples

What is Research?

Qualitative methods

What is the purpose of research?

Types of research methods and Examples

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2.1 Why Is Research Important?

Use of Research Information

Link to Learning

NOTABLE RESEARCHERS

The Process of Scientific Research

2.1 Why is Research Important

USE OF RESEARCH INFORMATION

THE PROCESS OF SCIENTIFIC RESEARCH

Answers to Exercises

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1.3: What is the Purpose of Research?

Learning Objective

KEY TAKEAWAY

Research Basics

So What Do We Mean By “Formal Research?”

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What is Research?

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The Guidelines

Aims of Research

Steps of the Scientific Process

1) Setting a Goal

2) Interpretation of the Results

3) Replication and Gradual Accumulation

4) Conclusion

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11.1 The Purpose of Research Writing

Reasons for Research

Research Writing and the Academic Paper

Research Writing at Work

Writing at Work

Steps of the Research Writing Process

Step 1: Choosing a Topic

Step 2: Planning and Scheduling

Step 3: Conducting Research

Step 4: Organizing Research and the Writer’s Ideas

Step 5: Drafting Your Paper

Step 6: Revising and Editing Your Paper

Key Takeaways

Doing Research in Education: Theory and Practice

The purpose of qualitative research

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