good research topics for sign language

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211 Research Topics in Linguistics To Get Top Grades

Many people find it hard to decide on their linguistics research topics because of the assumed complexities involved. They struggle to choose easy research paper topics for English language too because they think it could be too simple for a university or college level certificate.

All that you need to learn about Linguistics and English is sprawled across syntax, phonetics, morphology, phonology, semantics, grammar, vocabulary, and a few others. To easily create a top-notch essay or conduct a research study, you can consider this list of research topics in English language below for your university or college use. Note that you can fine-tune these to suit your interests.

Linguistics Research Paper Topics

If you want to study how language is applied and its importance in the world, you can consider these Linguistics topics for your research paper. They are:

• An analysis of romantic ideas and their expression amongst French people
• An overview of the hate language in the course against religion
• Identify the determinants of hate language and the means of propagation
• Evaluate a literature and examine how Linguistics is applied to the understanding of minor languages
• Consider the impact of social media in the development of slangs
• An overview of political slang and its use amongst New York teenagers
• Examine the relevance of Linguistics in a digitalized world
• Analyze foul language and how it’s used to oppress minors
• Identify the role of language in the national identity of a socially dynamic society
• Attempt an explanation to how the language barrier could affect the social life of an individual in a new society
• Discuss the means through which language can enrich cultural identities
• Examine the concept of bilingualism and how it applies in the real world
• Analyze the possible strategies for teaching a foreign language
• Discuss the priority of teachers in the teaching of grammar to non-native speakers
• Choose a school of your choice and observe the slang used by its students: analyze how it affects their social lives
• Attempt a critical overview of racist languages
• What does endangered language means and how does it apply in the real world?
• A critical overview of your second language and why it is a second language
• What are the motivators of speech and why are they relevant?
• Analyze the difference between the different types of communications and their significance to specially-abled persons
• Give a critical overview of five literature on sign language
• Evaluate the distinction between the means of language comprehension between an adult and a teenager
• Consider a native American group and evaluate how cultural diversity has influenced their language
• Analyze the complexities involved in code-switching and code-mixing
• Give a critical overview of the importance of language to a teenager
• Attempt a forensic overview of language accessibility and what it means
• What do you believe are the means of communications and what are their uniqueness?
• Attempt a study of Islamic poetry and its role in language development
• Attempt a study on the role of Literature in language development
• Evaluate the Influence of metaphors and other literary devices in the depth of each sentence
• Identify the role of literary devices in the development of proverbs in any African country
• Cognitive Linguistics: analyze two pieces of Literature that offers a critical view of perception
• Identify and analyze the complexities in unspoken words
• Expression is another kind of language: discuss
• Identify the significance of symbols in the evolution of language
• Discuss how learning more than a single language promote cross-cultural developments
• Analyze how the loss of a mother tongue affect the language Efficiency of a community
• Critically examine how sign language works
• Using literature from the medieval era, attempt a study of the evolution of language
• Identify how wars have led to the reduction in the popularity of a language of your choice across any country of the world
• Critically examine five Literature on why accent changes based on environment
• What are the forces that compel the comprehension of language in a child
• Identify and explain the difference between the listening and speaking skills and their significance in the understanding of language
• Give a critical overview of how natural language is processed
• Examine the influence of language on culture and vice versa
• It is possible to understand a language even without living in that society: discuss
• Identify the arguments regarding speech defects
• Discuss how the familiarity of language informs the creation of slangs
• Explain the significance of religious phrases and sacred languages
• Explore the roots and evolution of incantations in Africa

Sociolinguistic Research Topics

You may as well need interesting Linguistics topics based on sociolinguistic purposes for your research. Sociolinguistics is the study and recording of natural speech. It’s primarily the casual status of most informal conversations. You can consider the following Sociolinguistic research topics for your research:

• What makes language exceptional to a particular person?
• How does language form a unique means of expression to writers?
• Examine the kind of speech used in health and emergencies
• Analyze the language theory explored by family members during dinner
• Evaluate the possible variation of language based on class
• Evaluate the language of racism, social tension, and sexism
• Discuss how Language promotes social and cultural familiarities
• Give an overview of identity and language
• Examine why some language speakers enjoy listening to foreigners who speak their native language
• Give a forensic analysis of his the language of entertainment is different to the language in professional settings
• Give an understanding of how Language changes
• Examine the Sociolinguistics of the Caribbeans
• Consider an overview of metaphor in France
• Explain why the direct translation of written words is incomprehensible in Linguistics
• Discuss the use of language in marginalizing a community
• Analyze the history of Arabic and the culture that enhanced it
• Discuss the growth of French and the influences of other languages
• Examine how the English language developed and its interdependence on other languages
• Give an overview of cultural diversity and Linguistics in teaching
• Challenge the attachment of speech defect with disability of language listening and speaking abilities
• Explore the uniqueness of language between siblings
• Explore the means of making requests between a teenager and his parents
• Observe and comment on how students relate with their teachers through language
• Observe and comment on the communication of strategy of parents and teachers
• Examine the connection of understanding first language with academic excellence

Language Research Topics

Numerous languages exist in different societies. This is why you may seek to understand the motivations behind language through these Linguistics project ideas. You can consider the following interesting Linguistics topics and their application to language:

• What does language shift mean?
• Discuss the stages of English language development?
• Examine the position of ambiguity in a romantic Language of your choice
• Why are some languages called romantic languages?
• Observe the strategies of persuasion through Language
• Discuss the connection between symbols and words
• Identify the language of political speeches
• Discuss the effectiveness of language in an indigenous cultural revolution
• Trace the motivators for spoken language
• What does language acquisition mean to you?
• Examine three pieces of literature on language translation and its role in multilingual accessibility
• Identify the science involved in language reception
• Interrogate with the context of language disorders
• Examine how psychotherapy applies to victims of language disorders
• Study the growth of Hindi despite colonialism
• Critically appraise the term, language erasure
• Examine how colonialism and war is responsible for the loss of language
• Give an overview of the difference between sounds and letters and how they apply to the German language
• Explain why the placement of verb and preposition is different in German and English languages
• Choose two languages of your choice and examine their historical relationship
• Discuss the strategies employed by people while learning new languages
• Discuss the role of all the figures of speech in the advancement of language
• Analyze the complexities of autism and its victims
• Offer a linguist approach to language uniqueness between a Down Syndrome child and an autist
• Express dance as a language
• Express music as a language
• Express language as a form of language
• Evaluate the role of cultural diversity in the decline of languages in South Africa
• Discuss the development of the Greek language
• Critically review two literary texts, one from the medieval era and another published a decade ago, and examine the language shifts

Linguistics Essay Topics

You may also need Linguistics research topics for your Linguistics essays. As a linguist in the making, these can help you consider controversies in Linguistics as a discipline and address them through your study. You can consider:

• The connection of sociolinguistics in comprehending interests in multilingualism
• Write on your belief of how language encourages sexism
• What do you understand about the differences between British and American English?
• Discuss how slangs grew and how they started
• Consider how age leads to loss of language
• Review how language is used in formal and informal conversation
• Discuss what you understand by polite language
• Discuss what you know by hate language
• Evaluate how language has remained flexible throughout history
• Mimicking a teacher is a form of exercising hate Language: discuss
• Body Language and verbal speech are different things: discuss
• Language can be exploitative: discuss
• Do you think language is responsible for inciting aggression against the state?
• Can you justify the structural representation of any symbol of your choice?
• Religious symbols are not ordinary Language: what are your perspective on day-to-day languages and sacred ones?
• Consider the usage of language by an English man and someone of another culture
• Discuss the essence of code-mixing and code-switching
• Attempt a psychological assessment on the role of language in academic development
• How does language pose a challenge to studying?
• Choose a multicultural society of your choice and explain the problem they face
• What forms does Language use in expression?
• Identify the reasons behind unspoken words and actions
• Why do universal languages exist as a means of easy communication?
• Examine the role of the English language in the world
• Examine the role of Arabic in the world
• Examine the role of romantic languages in the world
• Evaluate the significance of each teaching Resources in a language classroom
• Consider an assessment of language analysis
• Why do people comprehend beyond what is written or expressed?
• What is the impact of hate speech on a woman?
• Do you believe that grammatical errors are how everyone’s comprehension of language is determined?
• Observe the Influence of technology in language learning and development
• Which parts of the body are responsible for understanding new languages
• How has language informed development?
• Would you say language has improved human relations or worsened it considering it as a tool for violence?
• Would you say language in a black populous state is different from its social culture in white populous states?
• Give an overview of the English language in Nigeria
• Give an overview of the English language in Uganda
• Give an overview of the English language in India
• Give an overview of Russian in Europe
• Give a conceptual analysis on stress and how it works
• Consider the means of vocabulary development and its role in cultural relationships
• Examine the effects of Linguistics in language
• Present your understanding of sign language
• What do you understand about descriptive language and prescriptive Language?

List of Research Topics in English Language

You may need English research topics for your next research. These are topics that are socially crafted for you as a student of language in any institution. You can consider the following for in-depth analysis:

• Examine the travail of women in any feminist text of your choice
• Examine the movement of feminist literature in the Industrial period
• Give an overview of five Gothic literature and what you understand from them
• Examine rock music and how it emerged as a genre
• Evaluate the cultural association with Nina Simone’s music
• What is the relevance of Shakespeare in English literature?
• How has literature promoted the English language?
• Identify the effect of spelling errors in the academic performance of students in an institution of your choice
• Critically survey a university and give rationalize the literary texts offered as Significant
• Examine the use of feminist literature in advancing the course against patriarchy
• Give an overview of the themes in William Shakespeare’s “Julius Caesar”
• Express the significance of Ernest Hemingway’s diction in contemporary literature
• Examine the predominant devices in the works of William Shakespeare
• Explain the predominant devices in the works of Christopher Marlowe
• Charles Dickens and his works: express the dominating themes in his Literature
• Why is Literature described as the mirror of society?
• Examine the issues of feminism in Sefi Atta’s “Everything Good Will Come” and Bernadine Evaristos’s “Girl, Woman, Other”
• Give an overview of the stylistics employed in the writing of “Girl, Woman, Other” by Bernadine Evaristo
• Describe the language of advertisement in social media and newspapers
• Describe what poetic Language means
• Examine the use of code-switching and code-mixing on Mexican Americans
• Examine the use of code-switching and code-mixing in Indian Americans
• Discuss the influence of George Orwell’s “Animal Farm” on satirical literature
• Examine the Linguistics features of “Native Son” by Richard Wright
• What is the role of indigenous literature in promoting cultural identities
• How has literature informed cultural consciousness?
• Analyze five literature on semantics and their Influence on the study
• Assess the role of grammar in day to day communications
• Observe the role of multidisciplinary approaches in understanding the English language
• What does stylistics mean while analyzing medieval literary texts?
• Analyze the views of philosophers on language, society, and culture

English Research Paper Topics for College Students

For your college work, you may need to undergo a study of any phenomenon in the world. Note that they could be Linguistics essay topics or mainly a research study of an idea of your choice. Thus, you can choose your research ideas from any of the following:

• The concept of fairness in a democratic Government
• The capacity of a leader isn’t in his or her academic degrees
• The concept of discrimination in education
• The theory of discrimination in Islamic states
• The idea of school policing
• A study on grade inflation and its consequences
• A study of taxation and Its importance to the economy from a citizen’s perspectives
• A study on how eloquence lead to discrimination amongst high school students
• A study of the influence of the music industry in teens
• An Evaluation of pornography and its impacts on College students
• A descriptive study of how the FBI works according to Hollywood
• A critical consideration of the cons and pros of vaccination
• The health effect of sleep disorders
• An overview of three literary texts across three genres of Literature and how they connect to you
• A critical overview of “King Oedipus”: the role of the supernatural in day to day life
• Examine the novel “12 Years a Slave” as a reflection of servitude and brutality exerted by white slave owners
• Rationalize the emergence of racist Literature with concrete examples
• A study of the limits of literature in accessing rural readers
• Analyze the perspectives of modern authors on the Influence of medieval Literature on their craft
• What do you understand by the mortality of a literary text?
• A study of controversial Literature and its role in shaping the discussion
• A critical overview of three literary texts that dealt with domestic abuse and their role in changing the narratives about domestic violence
• Choose three contemporary poets and analyze the themes of their works
• Do you believe that contemporary American literature is the repetition of unnecessary themes already treated in the past?
• A study of the evolution of Literature and its styles
• The use of sexual innuendos in literature
• The use of sexist languages in literature and its effect on the public
• The disaster associated with media reports of fake news
• Conduct a study on how language is used as a tool for manipulation
• Attempt a criticism of a controversial Literary text and why it shouldn’t be studied or sold in the first place

Finding Linguistics Hard To Write About?

With these topics, you can commence your research with ease. However, if you need professional writing help for any part of the research, you can scout here online for the best research paper writing service.

There are several expert writers on ENL hosted on our website that you can consider for a fast response on your research study at a cheap price.

As students, you may be unable to cover every part of your research on your own. This inability is the reason you should consider expert writers for custom research topics in Linguistics approved by your professor for high grades.

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• Open access
• Published: 09 October 2023

Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network

• Refat Khan Pathan 1 ,
• Munmun Biswas 2 ,
• Suraiya Yasmin 3 ,
• Mayeen Uddin Khandaker   ORCID: orcid.org/0000-0003-3772-294X 4 , 5 ,
• Mohammad Salman 6 &
• Ahmed A. F. Youssef 6  

Scientific Reports volume  13 , Article number:  16975 ( 2023 ) Cite this article

17k Accesses

14 Citations

Metrics details

• Computational science
• Image processing

Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a critical research topic for years. Although some of the previous studies have successfully recognized sign language, it requires many costly instruments including sensors, devices, and high-end processing power. However, such drawbacks can be easily overcome by employing artificial intelligence-based techniques. Since, in this modern era of advanced mobile technology, using a camera to take video or images is much easier, this study demonstrates a cost-effective technique to detect American Sign Language (ASL) using an image dataset. Here, “Finger Spelling, A” dataset has been used, with 24 letters (except j and z as they contain motion). The main reason for using this dataset is that these images have a complex background with different environments and scene colors. Two layers of image processing have been used: in the first layer, images are processed as a whole for training, and in the second layer, the hand landmarks are extracted. A multi-headed convolutional neural network (CNN) model has been proposed and tested with 30% of the dataset to train these two layers. To avoid the overfitting problem, data augmentation and dynamic learning rate reduction have been used. With the proposed model, 98.981% test accuracy has been achieved. It is expected that this study may help to develop an efficient human–machine communication system for a deaf-mute society.

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Introduction.

Spoken language is the medium of communication between a majority of the population. With spoken language, it would be workable for a massive extent of the population to impart. Nonetheless, despite spoken language, a section of the population cannot speak with most of the other population. Mute people cannot convey a proper meaning using spoken language. Hard of hearing is a handicap that weakens their hearing and makes them unfit to hear, while quiet is an incapacity that impedes their talking and makes them incapable of talking. Both are just handicapped in their hearing or potentially, therefore, cannot still do many other things. Communication is the only thing that isolates them from ordinary people 1 . As there are so many languages in the world, a unique language is needed to express their thoughts and opinions, which will be understandable to ordinary people, and such a language is named sign language. Understanding sign language is an arduous task, an ability that must be educated with training.

Many methods are available that use different things/tools like images (2D, 3D), sensor data (hand globe 2 , Kinect sensor 3 , neuromorphic sensor 4 ), videos, etc. All things are considered due to the fact that the captured images are excessively noisy. Therefore an elevated level of pre-processing is required. The available online datasets are already processed or taken in a lab environment where it becomes easy for recent advanced AI models to train and evaluate, causing prone to errors in real-life applications with different kinds of noises. Accordingly, it is a basic need to make a model that can deal with noisy images and also be able to deliver positive results. Different sorts of methods can be utilized to execute the classification and recognition of images using machine learning. Apart from recognizing static images, work has been done in depth-camera detecting and video processing 5 , 6 , 7 . Various cycles inserted in the system were created utilizing other programming languages to execute the procedural strategies for the final system's maximum adequacy. The issue can be addressed and deliberately coordinated into three comparable methodologies: initially using static image recognition techniques and pre-processing procedures, secondly by using deep learning models, and thirdly by using Hidden Markov Models.

Sign language guides this part of the community and empowers smooth communication in the community of people with trouble talking and hearing (deaf and dumb). They use hand signals along with facial expressions and body activities to cooperate. Yet, as a global language, not many people become familiar with communication via sign language gestures 8 . Hand motions comprise a significant part of communication through signing vocabulary. At the same time, facial expressions and body activities assume the jobs of underlining the words and phrases communicated by hand motions. Hand motions can be static or dynamic 9 , 10 . There are methodologies for motion discovery utilizing the dynamic vision sensor (DVS), a similar technique used in the framework introduced in this composition. For example, Arnon et al. 11 have presented an event-based gesture recognition system, which measures the event stream utilizing a natively event-based processor from International Business Machines called TrueNorth. They use a temporal filter cascade to create Spatio-temporal frames that CNN executes in the event-based processor, and they reported an accuracy of 96.46%. But in a real-life scenario, corresponding background situations are not static. Therefore the stated power saving process might not work properly. Jun Haeng Lee et al. 12 proposed a motion classification method with two DVSs to get a stereo-vision system. They used spike neurons to handle the approaching occasions with the same real-life issue. Static hand signals are also called hand acts and are framed in different shapes and directions of hands without speaking to any movement data. Dynamic hand motions comprise a sequence of hand stances with related movement information 13 . Using facial expressions, static hand images, and hand signals, communication through signing gives instruments to convey similarly as if communicated in dialects; there are different kinds of communication via gestures as well 14 .

In this work, we have applied a fusion of traditional image processing with extracted hand landmarks and trained on a multi-headed CNN so that it could complement each other’s weights on the concatenation layer. The main objective is to achieve a better detection rate without relying on a traditional single-channel CNN. This method has been proven to work well with less computational power and fewer epochs on medical image datasets 15 . The rest of the paper is divided into multiple sections as literature review in " Literature review " section, materials and methods in " Materials and methods " section with three subsections: dataset description in Dataset description , image pre-processing in " Pre-processing of image dataset " and working procedure in " Working procedure ", result analysis in " Result analysis " section, and conclusion in " Conclusion " section.

Literature review

State-of-the-art techniques centered after utilizing deep learning models to improve good accuracy and less execution time. CNNs have indicated huge improvements in visual object recognition 16 , natural language processing 17 , scene labeling 18 , medical image processing 15 , and so on. Despite these accomplishments, there is little work on applying CNNs to video classification. This is halfway because of the trouble in adjusting the CNNs to join both spatial and fleeting data. Model using exceptional hardware components such as a depth camera has been used to get the data on the depth variation in the image to locate an extra component for correlation, and then built up a CNN for getting the results 19 , still has low accuracy. An innovative technique that does not need a pre-trained model for executing the system was created using a capsule network and versatile pooling 11 .

Furthermore, it was revealed that lowering the layers of CNN, which employs a greedy way to do so, and developing a deep belief network produced superior outcomes compared to other fundamental methodologies 20 . Feature extraction using scale-invariant feature transform (SIFT) and classification using Neural Networks were developed to obtain the ideal results 21 . In one of the methods, the images were changed into an RGB conspire, the data was developed utilizing the movement depth channel lastly using 3D recurrent convolutional neural networks (3DRCNN) to build up a working system 5 , 22 where Canny edge detection oriented FAST and Rotated BRIEF (ORB) has been used. ORB feature detection technique and K-means clustering algorithm used to create the bag of feature model for all descriptors is described, but the plain background, easy to detect edges are totally dependent on edges; if the edges give wrong info, the model may fall accuracy and become the main problem to solve.

In recent years, utilizing deep learning approaches has become standard for improving the recognition accuracy of sign language models. Using Faster Region-based Convolutional Neural Network (Faster-RCNN) 23 , a CNN model is applied for hand recognition in the data image. Rastgoo et al. 24 proposed a method where they cropped an image properly, used fusion between RGB and depth image (RBM), added two noise types (Gaussian noise + salt n paper noise), and prepared the data for training. As a naturally propelled deep learning model, CNNs achieve every one of the three phases with a single framework that is prepared from crude pixel esteems to classifier yields, but extreme computation power was needed. Authors in ref. 25 proposed 3D CNNs where the third dimension joins both spatial and fleeting stamps. It accepts a few neighboring edges as input and performs 3D convolution in the convolutional layers. Along with them, the study reported in 26 followed similar thoughts and proposed regularizing the yields with high-level features, joining the expectations of a wide range of models. They applied the developed models to perceive human activities and accomplished better execution in examination than benchmark methods. But it is not sure it works with hand gestures as they detected face first and thenody movement 27 .

On the other hand, the Microsoft and Leap Motion companies have developed unmistakable approaches to identify and track a user’s hand and body movement by presenting Kinect and the leap motion controller (LMC) separately. Kinect recognizes the body skeleton and tracks the hands, whereas the LMC distinguishes and tracks hands with its underlying cameras and infrared sensors 3 , 28 . Using the provided framework, Sykora et al. 7 utilized the Kinect system to catch the depth data of 10 hand motions to classify them using a speeded-up robust features (SURF) technique that came up to an 82.8% accuracy, but it cannot test on more extensive database and modified feature extraction methods (SIFT, SURF) so it can be caused non-invariant to the orientation of gestures. Likewise, Huang et al. 29 proposed a 10-word-based ASL recognition system utilizing Kinect by tenfold cross-validation with an SVM that accomplished a precision pace of 97% using a set of frame-independent features, but the most significant problem in this method is segmentation.

The literature summarizes that most of the models used in this application either depend on a single variable or require high computational power. Also, their dataset choice for training and validating the model is in plain background, which is easier to detect. Our main aim is to show how to reduce the computational power for training and the dependency of model training on one layer.

Materials and methods

Dataset description.

Using a generalized single-color background to classify sign language is very common. We intended to avoid that single color background and use a complex background with many users’ hand images to increase the detection complexity. That’s why we have used the “ASL Finger Spelling” dataset 30 , which has images of different sizes, orientations, and complex backgrounds of over 500 images per sign (24 sign total) of 4 users (non-native to sign language). This dataset contains separate RGB and depth images; we have worked with the RGB images in this research. The photos were taken in 5 sessions with the same background and lighting. The dataset details are shown in Table 1 , and some sample images are shown in Fig.  1 .

Sample images from a dataset containing 24 signs from the same user.

Pre-processing of image dataset

Images were pre-processed for two operations: preparing the original image training set and extracting the hand landmarks. Traditional CNN has one input data channel and one output channel. We are using two input data channels and one output channel, so data needs to be prepared for both inputs individually.

Raw image processing

In raw image processing, we have converted the images from RGB to grayscale to reduce color complexity. Then we used a 2D kernel matrix for sharpening the images, as shown in Fig.  2 . After that, we resized the images into 50 × 50 pixels for evaluation through CNN. Finally, we have normalized the grayscale values (0–255) by dividing the pixel values by 255, so now the new pixel array contains value ranges (0–1). The primary advantage of this normalization is that CNN works faster in the (0–1) range rather than other limits.

Raw image pre-processing with ( a ) sharpening kernel.

Hand landmark detection

Google’s hand landmark model has an input channel of RGB and an image size of (224 × 224 × 3). So, we have taken the RGB images, converted pixel values into float32, and resized all the images into (256 × 256 × 3). After applying the model, it gives 21 coordinated 3-dimensional points. The landmark detection process is shown in Fig.  3 .

Hand landmarks detection and extraction of 21 coordinates.

Working procedure

The whole work is divided into two main parts, one is the raw image processing, and another one is the hand landmarks extraction. After both individual processing had been completed, a custom lightweight simple multi-headed CNN model was built to train both data. Before processing through a fully connected layer for classification, we merged both channel’s features so that the model could choose between the best weights. This working procedure is illustrated in Fig.  4 .

Flow diagram of working procedure.

Model building

In this research, we have used multi-headed CNN, meaning our model has two input data channels. Before this, we trained processed images and hand landmarks with two separate models to compare. Google’s model is not best for “in the wild” situations, so we needed original images to complement the low faults in Google’s model. In the first head of the model, we have used the processed images as input and hand landmarks data as the second head’s input. Two-dimensional Convolutional layers with filter size 50, 25, kernel (3, 3) with Relu, strides 1; MaxPooling 2D with pool size (2, 2), batch normalization, and Dropout layer has been used in the hand landmarks training side. Besides, the 2D Convolutional layer with filter size 32, 64, 128, 512, kernel (3, 3) with Relu; MaxPooling 2D with pool size (2, 2); batch normalization and dropout layer has been used in the image training side. After both flatten layers, two heads are concatenated and go through a dense, dropout layer. Finally, the output dense layer has 24 units with Softmax activation. This model has been compiled with Adam optimizer and MSE loss for 50 epochs. Figure  5 illustrates the proposed CNN architecture, and Table 2 shows the model details.

Proposed multi-headed CNN architecture. Bottom values are the number of filters and top values are output shapes.

Training and testing

The input images were augmented to generate more difficulty in training so that the model could not overfit. Image Data Generator did image augmentation with 10° rotation, 0.1 zoom range, 0.1 widths and height shift range, and horizontal flip. Being more conscious about the overfitting issues, we have used dynamic learning rates, monitoring the validation accuracy with patience 5, factor 0.5, and a minimum learning rate of 0.00001. For training, we have used 46,023 images, and for testing, 19,725 images. For 50 epochs, the training vs testing accuracy and loss has been shown in Fig.  6 .

Training versus testing accuracy and loss for 50 epochs.

For further evaluation, we have calculated the precision, recall, and F1 score of the proposed multi-headed CNN model, which shows excellent performance. To compute these values, we first calculated the confusion matrix (shown in Fig.  7 ). When a class is positive and also classified as so, it is called true positive (TP). Again, when a class is negative and classified as so, it is called true negative (TN). If a class is negative and classified as positive, it is called false positive (FP). Also, when a class is positive and classified as not negative, it is called false negative (FN). From these, we can conclude precision, recall, and F1 score like the below:

Confusion matrix of the testing dataset. Numerical values in X and Y axis means the sequential letters from A = 0 to Y = 24, number 9 and 25 is missing because dataset does not have letter J and Z.

Precision: Precision is the ratio of TP and total predicted positive observation.

Recall: It is the ratio of TP and total positive observations in the actual class.

F1 score: F1 score is the weighted average of precision and recall.

The Precision, Recall, and F1 score for 24 classes are shown in Table 3 .

Result analysis

In human action recognition tasks, sign language has an extra advantage as it can be used to communicate efficiently. Many techniques have been developed using image processing, sensor data processing, and motion detection by applying different dynamic algorithms and methods like machine learning and deep learning. Depending on methodologies, researchers have proposed their way of classifying sign languages. As technologies develop, we can explore the limitations of previous works and improve accuracy. In ref. 13 , this paper proposes a technique for acknowledging hand motions, which is an excellent part of gesture-based communication jargon, because of a proficient profound deep convolutional neural network (CNN) architecture. The proposed CNN design disposes of the requirement for recognition and division of hands from the captured images, decreasing the computational weight looked at during hand pose recognition with classical approaches. In our method, we used two input channels for the images and hand landmarks to get more robust data, making the process more efficient with a dynamic learning rate adjustment. Besides in ref 14 , the presented results were acquired by retraining and testing the sign language gestures dataset on a convolutional neural organization model utilizing Inception v3. The model comprises various convolution channel inputs that are prepared on a piece of similar information. A capsule-based deep neural network sign posture translator for an American Sign Language (ASL) fingerspelling (posture) 20 has been introduced where the idea concept of capsules and pooling are used simultaneously in the network. This exploration affirms that utilizing pooling and capsule routing on a similar network can improve the network's accuracy and convergence speed. In our method, we have used the pre-trained model of Google to extract the hand landmarks, almost like transfer learning. We have shown that utilizing two input channels could also improve accuracy.

Moreover, ref 5 proposed a 3DRCNN model integrating a 3D convolutional neural network (3DCNN) and upgraded completely associated recurrent neural network (FC-RNN), where 3DCNN learns multi-methodology features from RGB, motion, and depth channels, and FCRNN catch the fleeting data among short video clips divided from the original video. Consecutive clips with a similar semantic significance are singled out by applying the sliding window way to deal with a section of the clips on the whole video sequence. Combining a CNN and traditional feature extractors, capable of accurate and real-time hand posture recognition 26 where the architecture is assessed on three particular benchmark datasets and contrasted and the cutting edge convolutional neural networks. Extensive experimentation is directed utilizing binary, grayscale, and depth data and two different validation techniques. The proposed feature fusion-based CNN 31 is displayed to perform better across blends of approval procedures and image representation. Similarly, fusion-based CNN is demonstrated to improve the recognition rate in our study.

After worldwide motion analysis, the hand gesture image sequence was dissected for keyframe choice. The video sequences of a given gesture were divided in the RGB shading space before feature extraction. This progression enjoyed the benefit of shaded gloves worn by the endorsers. Samples of pixel vectors representative of the glove’s color were used to estimate the mean and covariance matrix of the shading, which was sectioned. So, the division interaction was computerized with no user intervention. The video frames were converted into color HSV (Hue-SaturationValue) space in the color object tracking method. Then the pixels with the following shading were distinguished and marked, and the resultant images were converted to a binary (Gray Scale image). The system identifies image districts compared to human skin by binarizing the input image with a proper threshold value. Then, at that point, small regions from the binarized image were eliminated by applying a morphological operator and selecting the districts to get an image as an applicant of hand.

In the proposed method we have used two-headed CNN to train the processed input images. Though the single image input stream is widely used, two input streams have an advantage among them. In the classification layer of CNN, if one layer is giving a false result, it could be complemented by the other layer’s weight, and it is possible that combining both results could provide a positive outcome. We used this theory and successfully improved the final validation and test results. Before combining image and hand landmark inputs, we tested both individually and acquired a test accuracy of 96.29% for the image and 98.42% for hand landmarks. We did not use binarization as it would affect the background of an image with skin color matched with hand color. This method is also suitable for wild situations as it is not entirely dependent on hand position in an image frame. A comparison of the literature and our work has been shown in Table 4 , which shows that our method overcomes most of the current position in accuracy gain.

Table 5 illustrates that the Combined Model, while having a larger number of parameters and consuming more memory, achieves the highest accuracy of 98.98%. This suggests that the combined approach, which incorporates both image and hand landmark information, is effective for the task when accuracy is priority. On the other hand, the Hand Landmarks Model, despite having fewer parameters and lower memory consumption, also performs impressively with an accuracy of 98.42%. But it has its own error and memory consumption rate in model training by Google. The Image Model, while consuming less memory, has a slightly lower accuracy of 96.29%. The choice between these models would depend on the specific application requirements, trade-offs between accuracy and resource utilization, and the importance of execution time.

This work proposes a methodology for perceiving the classification of sign language recognition. Sign language is the core medium of communication between deaf-mute and everyday people. It is highly implacable in real-world scenarios like communication, human–computer interaction, security, advanced AI, and much more. For a long time, researchers have been working in this field to make a reliable, low cost and publicly available SRL system using different sensors, images, videos, and many more techniques. Many datasets have been used, including numeric sensory, motion, and image datasets. Most datasets are prepared in a good lab condition to do experiments, but in the real world, it may not be a practical case. That’s why, looking into the real-world situation, the Fingerspelling dataset has been used, which contains real-world scenarios like complex backgrounds, uneven image shapes, and conditions. First, the raw images are processed and resized into a 50 × 50 size. Then, the hand landmark points are detected and extracted from these hand images. Making images goes through two processing techniques; now, there are two data channels. A multi-headed CNN architecture has been proposed for these two data channels. Total data has been augmented to avoid overfitting, and dynamic learning rate adjustment has been done. From the prepared data, 70–30% of the train test spilled has been done. With the 30% dataset, a validation accuracy of 98.98% has been achieved. In this kind of large dataset, this accuracy is much more reliable.

There are some limitations found in the proposed method compared with the literature. Some methods might work with low image dataset numbers, but as we use the simple CNN model, this method requires a good number of images for training. Also, the proposed method depends on the hand landmark extraction model. Other hand landmark model can cause different results. In raw image processing, it is possible to detect hand portions to reduce the image size, which may increase the recognition chance and reduce the model training time. Hence, we may try this method in future work. Currently, raw image processing takes a good amount of training time as we considered the whole image for training.

Data availability

The dataset used in this paper (ASL Fingerspelling Images (RGB & Depth)) is publicly available at Kaggle on this URL: https://www.kaggle.com/datasets/mrgeislinger/asl-rgb-depth-fingerspelling-spelling-it-out .

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Funding was provided by the American University of the Middle East, Egaila, Kuwait.

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Pathan, R.K., Biswas, M., Yasmin, S. et al. Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network. Sci Rep 13 , 16975 (2023). https://doi.org/10.1038/s41598-023-43852-x

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Best practices for sign language technology research

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Research on sign language technology (SLT) has steadily increased in recent decades, and yet, common mistakes and pitfalls have significantly hindered progress in the field. The purpose of this paper is to examine some of the most prominent issues and suggest practical steps to overcome them, outlining the best practices to consider when conducting SLT research. These practices cluster around the five following issues: (1) knowledge of the specific sign language at the centre of the research and of sign languages more generally; (2) involving deaf people at the centre of research, including researchers who are themselves deaf; (3) motivations of the researcher and the relationship to the views of the sign language community; (4) what sign language data needs to be considered; (5) full recognition of the challenges posed by such research.

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1 Introduction

Sign language technology (SLT) has become a prominent research area for the computer vision and natural language processing (NLP) communities in the last 30 years [ 55 , 86 , 95 ]. Initial progress has been made in research into technologies that can aid communication between hearing and deaf communities. However, common mistakes have held the field back. As interest expands into this research area, we believe that best practices must be established to enable effective, continued, and long-lasting progress.

In this paper, we detail the most prominent issues that regularly arise in the current SLT research landscape. Often researchers do not fully appreciate the complexity of sign languages and the importance of the deaf community (Sect.  2 ). There has been a lack of deaf involvement in SLT projects (Sect.  3 ). SLT research has focused on ‘problems’ identified by hearing non-signers that are not actually problems at all, whilst some have proposed tools/advancements that have been enormously over-hyped by the media (Sect.  4 ). The data available for use in SLT have also been limited (Sect.  5 ), with an as yet unmet requirement for continuous, diverse sign language datasets. Finally, the complexity of sign language translation has not been fully recognised, as multiple intermediary tasks must be tackled before this can be automated (Sect.  6 ).

To meet each of these challenges, this paper suggests practical steps, laying out best practice recommendations for SLT research. We hope this work can help establish effective guidelines for both new researchers and incumbents in the field, enabling meaningful progress. The main body of this paper describes the five points of consideration in more detail (Sects.  2 – 6 ) with conclusions in Sect.  7 .

Before we begin, we wish to provide some context. We are a team of deaf (NF) and hearing (BW, KC) sign language researchers. We are part of and/or have worked closely with British deaf communities for many years, and we are all fluent signers. Because we work primarily on British Sign Language (BSL), most of our observations here relate to BSL, but most hold true for SLT relating to other sign languages as well.

2 Learn about sign languages and deaf people

Sign languages are the languages developed in and used by deaf communities [ 81 ]. There are many different sign languages in the world, each with their own grammar and lexicon. The differences in the communicative channels used by spoken and sign languages result in differences in their linguistic structures. For example, spoken languages have access to only a single set of primary articulators (mouth, tongue, lips, teeth), while sign languages have two independent primary articulators (the two hands) and are thus able to make much greater use of simultaneous, rather than linear, grammar [ 91 ]. Additionally, in sign languages, communication is necessarily expressed both manually (hands) and non-manually (face and body poses) [ 84 ]. Fingerspellings (manual alphabets) are used within sign languages to represent the letters from the ambient written language for specific purposes, such as rendering proper names [ 65 ]. Fingerspelled words are distinct and different from the sign language lexicon, which is itself independent of the lexicon of the surrounding spoken/written language [ 85 ]. Understanding these complex linguistic features of sign languages is essential in conducting effective SLT research.

In sign languages studied to date, lexical signs are the most frequent form of sign—these are signs that have fairly conventional form and meaning, which can be expressed via one or more ‘translation equivalent’ words in another language [ 50 ] (although it should be noted that just as with translation between any two languages, there is often no one-to-one correspondence between signs and words.) But even lexical signs are produced less than 75% of the time in signed discourse [ 33 ]. Much of signed discourse involves pointing and/or depiction. Both pointing and depiction are context-dependent and involve some degree of improvisation. Pointings and depictions rarely look the same or mean the same thing more than once in any signed discourse, which makes them difficult to deal with in a machine learning context [ 48 ]. Their unconventionality means that in SLT they are treated as single sign tokens (see Sect.  5 on single tokens).

In addition to learning about how sign languages work, gaining basic deaf awareness is a minimal requirement for researchers in the field [ 4 ]. Some assume wrongly that deaf people have the same challenges as people with various disabilities, while others assume that deaf people have the same cultural norms as hearing people. Learning about deaf communities and the different ways in which deaf people view the world is fundamental to producing valid sign language research. Researchers also need to learn how deaf people do and do not refer to themselves, in order to avoid offensive terminology [ 12 ]. For example, terms such as ‘deaf and dumb’ and ‘deaf-mute’ are completely unacceptable and their use in sign language technology research has led to retractions by publishers (see, e.g. [ 39 , 58 ]). In addition, referring to sign languages as ‘gestures’, ‘mimicry’ or ‘communication tools’, or being ‘specifically developed for [deaf] people’ (as in, e.g. [ 6 , 8 , 45 , 87 ]; and many others) are inaccurate and offensive ways to talk about natural human languages. Börstell [ 9 ] has shown that this problem of ableist language use when referring to sign languages and deaf communities is far more prevalent in the field of technology than other fields like linguistics, education, and health—reflecting low levels of deaf awareness and deaf involvement in SLT research.

3 Involve deaf people in research

The ultimate aim of SLT research is to develop technology for the deaf community, to aid communication and accessibility. It is only logical that deaf people must then be involved in the research itself [ 10 ]. Deaf perspectives bring the engagement with the community that a successful project should seek to include. Ideally, deaf people should be involved at every level including in the planning stages before any work begins [ 25 , 64 ], yet few projects and publications reflect this level of deaf involvement. Exceptions include work by Vogler and Metaxas [ 92 , 93 ], Padden and Gunsauls [ 65 ], Cormier, Fox, et al. [ 23 ], Glasser et al. [ 40 ], and EU projects such as EASIER ( https://www.project-easier.eu/ ) and SignOn ( https://signon-project.eu/ ) which have involved deaf organisations at every stage and deaf lay audiences in user testing. One weakness with many projects to date is that engagement has happened too late, after the main development work has taken place, and the perspective has become one of reporting back to the community, rather than ascertaining whether the community thinks the project is worthy in the first place [ 34 ].

One danger of involving deaf people in SLT research minimally is tokenism, and this should be avoided. Tokenism is not an issue as long as one aims for allyship instead [ 46 ]. To be an ally is to work towards improving deaf representation in the research in various ways—not just as participants, but also as researchers, advisors, investigators. In areas where deaf people are underrepresented in these roles, hearing allies should recruit and train them so that they can be leaders in the future. It should be an aim of the SLT research community to provide not only equal training opportunities for deaf researchers, but additional training, and fast track possibilities where funding allows, to enable professional development, including via non-traditional routes. Such opportunities apply not just in the day-to-day running of research projects but also in presenting the research, e.g. in publications and conference participation. In these contexts, visibility is key, and hearing allies can play a role in shaping this.

For example, hearing researchers who are invited to contribute to a publication or conference or keynote where the topic is focused on SLT should encourage the inclusion of deaf colleagues by the default provision of interpreting at SL conferences (see, e.g. [ 38 ]), and by giving space and time to deaf researchers to showcase their work. Additionally, any workshops and conferences covering sign languages that do not have deaf invited speakers or deaf authors in their proceedings, should be viewed as not deaf-inclusive.

4 Consider the reasons for carrying out the research

When conducting SLT research, ask yourself this: ‘What problem am I trying to solve? Is it actually a problem?’. Technology is never going to solve the problem of deaf signers and hearing non-signers understanding each other [ 41 ], but it can be used to develop tools to help towards this end [ 10 ]. If you are developing a tool, who exactly would use it and for what purpose [ 59 ]? By engaging early with deaf people and deaf communities [ 60 , 80 ], research can better meet their needs and preferences. Some topics, which could actually benefit deaf people, have received insufficient attention from the research community, while some technologies, such as ‘data gloves for deaf people’, at best have no practical purpose at all [ 30 , 47 ] and at worst ‘perpetuate cultural appropriation and audism’ [ 35 ].

Another problem to address is that many school and college projects, which are touted as technology which will help deaf people to communicate with the hearing community, are initiated almost exclusively by hearing people. The tools that are developed from these projects are clearly only prototypes, often dealing with limited aspects of communication among deaf people (e.g. recognition of fingerspelled handshapes [ 51 , 77 ] or with signs in isolation [ 57 ]) and receive no further development. More importantly, they often serve no useful purpose to deaf people at all. Despite this, because they appear innovative to hearing non-signers, such projects attract publicity and funding.

In addition to attracting funding, technological projects of this type are often picked up by the media and presented as technology that will remove barriers to communication between deaf and hearing people [ 11 , 20 , 21 ]. Media hype nearly always ends up alienating the deaf community as it comes from a mainly hearing perspective. Just as researchers need deaf perspectives, so do the media. This too would be improved with more deaf people involved in the research from the beginning. These responsibilities should also be shared with the funding bodies and their vetting process. If there was an obligation for funding bodies to ensure that their resources are appropriately allocated, it follows that deaf participation would increase and deaf perspectives would be more realistically reflected. The focus would thus shift from research as a self-perpetuating enterprise to one that aims to provide benefit to the community.

Despite the criticisms outlined above, there are some good candidates for useful SLT: for example, the deaf community might well welcome increased access to smart assistants/home control systems such as Siri and Alexa [ 31 ], or the ability to search signed videos [ 29 ], or a signed wiki [ 40 ]. Unfortunately, without awareness in private sector R&D departments that the needs of deaf people may be fundamentally different to those of hearing people, progress is unlikely.

5 Consider the type of source data needed

Sign language corpora exist for a growing number of sign languages around the world [ 26 , 27 , 44 , 75 , 100 ]. The sources and uses of these corpora are varied: continuous natural studio-recorded datasets originally designed for linguistic use [ 44 , 63 , 75 ], project-specific isolated studio-recorded datasets [ 16 , 26 ] or sign interpreted broadcast footage [ 1 , 3 , 13 , 15 , 18 , 22 , 36 ], to name a few.

The suitability of each type of dataset for SLT research on recognition and output must be considered before use. When considering which sign language dataset to use for SLT research, there are many important factors to be aware of [ 10 ]. These include the diversity of signers present in the data, variability across signers of different ages and different proficiency and age of acquisition, the size of the vocabulary, whether the data are isolated or continuous, whether the data are from a laboratory recording, the internet or broadcast footage, and what types of annotation have been undertaken. Yin et al. [ 98 ] provide a detailed breakdown of further properties to consider when selecting an appropriate sign language dataset.

In addition, datasets can vary between a spoken language source (interpreted into a signed language, e.g. with picture-in-picture interpreter) and a sign language source (interpreted via voice-over into a spoken language). The most widely used sign machine learning datasets have consisted of broadcast interpretations, most notably television weather reports [ 36 , 53 ]. Although these have proved useful, there are considerations and concerns about whether it is appropriate to use datasets from such restricted domains of discourse with limited vocabulary size [ 16 , 26 ], rather than the large domains found in spontaneous, natural signing [ 18 , 44 ]. One disadvantage, however, of very large domains such as spontaneous conversation is that many signs are represented with only a handful of instances, which poses difficulties for data-hungry machine learning algorithms.

A critical issue in research of this sort is ensuring that the data to be used as the source material represent the actual target of the analysis: in the case where material interpreted from English into BSL is used as the source data, the question arises of whether material comprised of BSL produced by hearing and deaf interpreters is appropriate as source material for developing automated translation from BSL to English. Additional questions arise in relation to automated translation from English to BSL. As with spoken languages, deaf fluent signers can and do make grammaticality and acceptability judgements, assessing whether other signers are fluent or not, whether they are native signers or not, and whether they use the language in everyday contexts. In this respect, there are three important questions to be addressed: (1) to what extent does scripted language (whether produced by hearing or deaf people) differ from the spontaneously produced BSL of deaf people?; (2) are there any differences between interpreted and spontaneously produced BSL?; (3) are there any differences between the interpreted BSL produced by hearing interpreters and that produced by deaf interpreters? This final question is of particular relevance in relation to automatic translation of sign language facilitated by recognition of mouthing patterns used by signers, since there is some evidence that hearing and deaf signers differ in their use of mouthing, both in terms of amount and of form [ 66 ].

In the general interpreting/translation literature, there is recognition that translated or interpreted language differs from the source (whether spontaneous or scripted) not only in terms of target language but also on a number of dimensions (so-called translation, or interpreting, ‘universals’ [ 5 , 24 , 37 , 78 , 79 ]). These differences include a number of features, such as a general tendency towards simplification, and because of their similarity across different source and output texts in different languages, they have been termed ‘interpretese’.

Shlesinger and Ordan [ 79 ] compared three types of text: interpreted texts, manually transcribed from the spoken outputs of four professional interpreters working in conference settings; translated written texts in (approximately) the same domains, rendered by professional translators; and original semi-scripted speech in (approximately) the same domains by conference presenters. They found that interpreted texts exhibited far more similarities to original speech than to written translation, reflecting that interpretese is more spoken than translated . On the other hand, they found that features such as simplification and lower type-token ratio (which are characteristic of translation) are found to be more salient in interpreted output, as compared to spontaneous language.

There is little literature in the field addressing these questions in relation to sign language interpreting, although there is evidence that there are differences between hearing and deaf interpreters [ 83 , 94 ]. Stone [ 83 ] addresses differences between hearing and deaf interpreters in the process of preparing a sign language interpretation from an English script, by examining prosodic features of these interpretations, for example in the use of non-manual features such as mouthing (with hearing interpreters more likely to produce multisyllabic mouthings). Additionally, signed translations can either be done from written scripts via autocue in real time or interpreted from a spoken language in real time. For broadcast television material, there are differences between deaf and hearing interpreters, although both produce their final version ‘live’. Hearing interpreters, although they have access to a written script to prepare, undertake limited preparation from these written forms and rely to a greater extent on hearing the spoken version to interpret in real time. In contrast, deaf interpreters prepare extensively from the written text, enabling them to create a translation rather than an interpretation, using the autocue to support the final version in real time [ 83 ].

In relation to the question of possible differences between deaf and hearing interpreters, silent mouthing of words from spoken language is also one possible source of difference. It is known that mouthing differs along sociolinguistic parameters such as region, gender, age, nativeness, and level of education, even among deaf signers [ 7 , 68 ]. No studies have explicitly explored mouthing differences between interpreters on the basis of hearing status. However, this is a topic worthy of research.

Another issue in considering choice of data source regardless of whether it is interpreted or not is annotation. In order to computationally process sign datasets, time-aligned machine-readable annotation is necessary. For machine learning SLT research, these annotations should be accurate and exhaustive, with detailed segmentation and ideally gloss labelling of each sign. However, this process is significantly labour-intensive and requires fluent signers.

It is also important to consider the extraction of data for computational processing, most commonly pose keypoints [ 19 , 99 ]. Computer models are able to accurately estimate 2D body pose [ 19 ], but hand pose estimation, especially with two hands, is still very challenging [ 43 ]. Recent work of Moryossef et al. [ 62 ] has shown that human body pose estimation quality is potentially a limiting factor when used for SLT and requires further research. To optimise pose estimation results, datasets of higher quality and resolution must be adopted [ 18 ].

6 Recognise the challenges of automatic sign language analysis

Automatic translation between signed and spoken languages is the ultimate aim of many SLT projects [ 18 , 23 , 28 ], yet this task is incredibly complex [ 89 ]. The computer science community often underestimates the linguistic complexity of sign languages and treats automatic translation as a standard video-to-text/text-to-video problem or as similar to a simple gesture recognition/production problem [ 56 , 90 ]. This oversimplifies translation models, leading to inaccurate end results and ultimately poor access for deaf people [ 52 , 97 ].

There are substantial differences between an automated sign-to-spoken language translation process compared to automated translation between two spoken languages. Spoken language translation can involve speech-to-text as a first stage, followed by translation from source language text to target language text, followed by text-to-speech. Sign languages lack a written form [ 84 ], and they must be represented in a continuous format for computation [ 71 ], in contrast to the discrete representation of written language. Therefore, there is a requirement for bespoke architectures specific to sign language.

In addition, when tackling sign language translation, the natural variability in human translation must be captured, as there is more than one way to translate an utterance between a spoken and a signed language, just as between spoken languages. Many translations are equally valid, but some may be judged as better or more accurate than others. It is important that computational models use judgements of accuracy to take natural variability into account. Currently, the most common SLT research areas are sign recognition: the recognition of isolated lexical signs from a video [ 42 , 57 ]; sign language translation: the translation of sign language videos to continuous spoken language [ 17 , 18 ]; and sign language production: the generation of sign language content from spoken language [ 73 , 82 , 96 ].

Although recognition is a logical first step when tackling a full automated translation task, any application of isolated sign recognition has limited use to deaf people. Isolated sign recognition is useful for some tasks such as searching for individual signs in videos and dictionaries but not for recognising sign language discourse. This continued focus on isolated recognition is indicative of a lack of progress in the field [ 10 , 53 ] and a lack of understanding of sign language and deaf needs. Although continuous sign translation [ 15 ] and production [ 71 ] are much harder tasks, they are considerably more helpful as tools. SLT research must turn towards continuous translation and production to progress.

However, before unconstrained sign language translation can be achieved, there are multiple additional intermediary tasks in sign language processing that must be tackled. Current intermediate problems include, but are not limited to, active signer detection [ 2 ], subtitle alignment [ 14 ], sign segmentation [ 69 ], visual anonymisation [ 70 , 72 ], visual representation learning [ 3 ], continuous recognition [ 54 ], sign animation [ 74 ], sign spotting [ 61 , 89 ], fingerspelling detection [ 67 , 76 ], detailed 3D human shape estimation [ 32 , 49 ], facial expressions, head pose and body movements [ 88 ], and multi-signer scenarios [ 64 ].

7 Conclusions

In this paper, we have outlined the current state of sign language technology (SLT) research, arguing that progress has been hindered by five prominent issues. To tackle this, we have proposed best practices every researcher should consider when conducting SLT research. We hope the insights provided here will enhance progress and value in the field for both hearing and deaf people.

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Acknowledgements

We would like to thank the following people for their contribution to and comments on an earlier version of this manuscript: Robert Adam, Ben Saunders, Necati Cihan Camgöz, Samuel Albanie, Gul Varol, Andrew Zisserman and Richard Bowden. Any errors remain our own.

This work was supported by the UK Engineering and Physical Sciences Research Council (‘ExTOL: End to End Translation of British Sign Language’, EP/R03298X/1) and also the European Union's Horizon 2020 research and innovation programme (‘EASIER: Intelligent Automatic Sign Language Translation’, 101016982).

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Most students turn to the internet to find research paper topics. Sadly, most sources provide unoriginal and basic topics. For this reason, this article provides some creative sample research topics for English majors.

Linguistics is a fascinating subject with so many research topic options. Check out the following creative research topics in language

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• Computers and their effect on language creation
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• Language barriers in the healthcare sector
• What percentage of kids below five struggle with languages?
• Understanding the increase in multilingual people
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• Social media and language: are language barriers existent in social media?
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• An analysis of how sociolinguistics can help people understand multi-lingual language choices
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• The role of sociolinguistics in children development
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• Types of indigenous languages
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• Theories that explain the origin and development of language
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• Language and gender: what is the correlation?
• How different genders perceive language
• Does a kid’s gender influence their grasp of languages?
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• How words acquire their meanings

While a good topic can help capture the reader and create a good impression, it is insufficient to earn you excellent grades. You also need quality content for your paper to get perfect grades. However, creating a high-quality research paper takes time, effort, and skill, which most students do not have.

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• Psychology General
• Developmental Psychology
• Language Acquisition & Development

Research Methods in Sign Language Studies: A Practical Guide

ISBN: 978-1-118-27141-4

Wiley-Blackwell

Digital Evaluation Copy

Eleni Orfanidou , Bencie Woll , Gary Morgan

Research Methods in Sign Language Studies is a landmark work on sign language research, which spans the fields of linguistics, experimental and developmental psychology, brain research, and language assessment.

• Examines a broad range of topics, including ethical and political issues, key methodologies, and the collection of linguistic, cognitive, neuroscientific, and neuropsychological data
• Provides tips and recommendations to improve research quality at all levels and encourages readers to approach the field from the perspective of diversity rather than disability
• Incorporates research on sign languages from Europe, Asia, North and South America, and Africa
• Brings together top researchers on the subject from around the world, including many who are themselves deaf

  Eleni Orfanidou is Lecturer of Cognitive/Experimental Psychology at the University of Crete, Greece. She was previously Postdoctoral Research Fellow at City University London, UK, and Research Fellow at the Deafness Cognition and Language Research Centre at University College London, UK. She has published on various aspects of psycholinguistics and neurolinguistics in Journal of Cognitive Neuroscience , Journal of Memory and Language , and Nature Communications .

Bencie Woll is Professor of Sign Language Studies and Director of the Deafness Cognition and Language Research Centre at University College London, UK. She was elected as a fellow of the British Academy in 2012. She is the co-author or co-editor of many books, including her most recent, Sign Language: An International Handbook (2012) and The Signs of a Savant (2010).

Gary Morgan is Professor of Psychology at City University London and Deputy Director of the Deafness Cognition and Language Research Centre at University College London, UK. He has published widely on sign language acquisition, theory of mind development, and psycholinguistic studies of sign languages, and he has developed several tests for assessing language skills in children. He is the co-author of several books, including Directions in Sign Language Acquisition (2002) and The Signs of a Savant (2010).

129 List Of Research Topics In English Language Teaching [updated]

English Language Teaching (ELT) is a field dedicated to teaching English to non-native speakers. It’s important because English is a global language used for communication, business, and education worldwide. Research in ELT helps improve teaching methods, making it easier for students to learn English effectively. This blog will explore a list of research topics in English language teaching.

What Are The Areas Of Research In English Language Teaching?

Table of Contents

Research in English Language Teaching (ELT) encompasses a wide range of areas, including:

• Language Learning: Understanding how people learn English well, like when they learn a new language and if there’s a best time to do it.
• Teaching Ways: Looking into different ways teachers teach, like using conversations, tasks, or mixing language with other subjects.
• Curriculum Design and Syllabus Development: Designing and evaluating language curricula and syllabi to meet the needs of diverse learners and contexts.
• Assessment and Evaluation: Developing and validating assessment tools, exploring alternative assessment methods, and investigating the effectiveness of feedback and error correction strategies.
• Technology in ELT: Exploring the integration of technology in language teaching and learning, including computer-assisted language learning (CALL), mobile-assisted language learning (MALL), and online learning platforms.
• Teacher Education and Professional Development: Investigating pre-service and in-service teacher education programs, reflective practices, and challenges in teacher training.
• Cultural and Sociolinguistic Aspects: Examining the role of culture in language teaching and learning, sociolinguistic competence, and addressing cultural diversity in the classroom.
• Learner Diversity and Inclusive Practices: Researching teaching strategies for diverse learners, including young learners, learners with learning disabilities, and learners from diverse linguistic and cultural backgrounds.
• Policy and Planning in ELT: Analyzing language policies at national and international levels, exploring the implementation of ELT programs, and examining the role of ELT in national development.
• Research Methodologies in ELT: Investigating qualitative, quantitative, and mixed-methods research approaches in ELT research, including action research conducted by teachers in their own classrooms.
• Future Trends and Innovations: Exploring emerging trends and innovations in ELT, such as the impact of globalization, the use of artificial intelligence (AI) in language learning, and innovative teaching strategies.

129 List Of Research Topics In English Language Teaching: Category Wise

Language acquisition and development.

• Second Language Acquisition Theories: Explore different theories explaining how learners acquire a second language.
• Critical Period Hypothesis: Investigate the idea of an optimal age range for language acquisition.
• Multilingualism and Language Development: Study how knowing multiple languages affects language development.
• Cognitive and Affective Factors in Language Learning: Examine the role of cognitive abilities and emotions in language learning.
• Language Learning Strategies: Investigate the strategies learners use to acquire and develop language skills.
• Input Hypothesis: Explore the role of comprehensible input in language acquisition.
• Interaction Hypothesis: Examine the importance of interaction in language learning.
• Fossilization in Second Language Learning: Study why some learners reach a plateau in their language development.

Teaching Methodologies and Approaches

• Communicative Language Teaching (CLT): Analyze the effectiveness of CLT in promoting communication skills.
• Task-Based Language Teaching (TBLT): Explore the use of real-world tasks to teach language.
• Content and Language Integrated Learning (CLIL): Investigate teaching subject content through English.
• Blended Learning in ELT: Study the integration of traditional and online teaching methods.
• Audio-Lingual Method: Assess the effectiveness of drills and repetition in language teaching.
• Grammar-Translation Method: Compare traditional grammar-focused methods with communicative approaches.
• Lexical Approach: Explore teaching vocabulary as a key component of language proficiency.
• Suggestopedia: Investigate the use of relaxation techniques to enhance language learning.

Curriculum Design and Syllabus Development

• Needs Analysis in ELT: Identify the language needs of learners and design appropriate curricula.
• Integrating Language Skills in Curriculum: Examine strategies for integrating reading, writing, listening, and speaking skills.
• Syllabus Types: Compare different types of syllabi, such as structural and task-based.
• Task-Based Syllabus Design: Design syllabi based on real-world tasks to promote language acquisition.
• Content-Based Instruction (CBI): Integrate language learning with academic content in syllabus design.
• Needs Analysis in Specific Contexts: Conduct needs analyses for learners in specific professional or academic contexts.
• Cross-Cultural Communication in Curriculum Design: Incorporate intercultural communication skills into language curricula.

Assessment and Evaluation

• Standardized Testing in ELT: Evaluate the reliability and validity of standardized English language tests.
• Alternative Assessment Approaches: Explore non-traditional assessment methods like portfolios and self-assessment.
• Feedback Strategies in Language Learning: Investigate effective feedback techniques for improving language proficiency.
• Washback Effect of Testing: Study how assessment practices influence teaching and learning.
• Authentic Assessment in ELT: Develop assessment tasks that mirror real-life language use situations.
• Portfolio Assessment: Investigate the use of portfolios to track language learning progress over time.
• Computer Adaptive Testing (CAT): Evaluate the feasibility and effectiveness of adaptive testing methods in ELT.

Technology in ELT

• Computer-Assisted Language Learning (CALL): Assess the impact of computer-based language learning programs.
• Mobile-Assisted Language Learning (MALL): Study the effectiveness of mobile devices in language learning.
• Online Learning Platforms for ELT: Analyze the features and usability of online platforms for language education.
• Virtual Reality (VR) in Language Learning: Explore immersive VR environments for language practice and instruction.
• Artificial Intelligence (AI) Tutoring Systems: Assess the effectiveness of AI-based tutors in providing personalized language instruction.
• Social Media in Language Learning: Study the role of social media platforms in informal language learning contexts.
• Gamification in ELT: Investigate the use of game elements to enhance engagement and motivation in language learning.

Teacher Education and Professional Development

• Pre-service Teacher Education Programs: Evaluate the effectiveness of teacher training programs.
• Reflective Practice in Teaching: Investigate how teachers reflect on their practice to improve teaching.
• Challenges in Teacher Education: Identify challenges faced by educators in training and development.
• Teacher Beliefs and Practices: Examine how teachers’ beliefs about language learning influence their instructional practices.
• Peer Observation in Teacher Development: Explore the benefits of peer observation and feedback for teacher professional growth.
• Mentoring Programs for New Teachers: Evaluate the effectiveness of mentoring programs in supporting novice teachers.
• Continuing Professional Development (CPD) Models: Compare different models of CPD for language teachers and their impact on teaching quality.

Cultural and Sociolinguistic Aspects

• Language and Culture Interrelationship: Explore the relationship between language and culture in ELT.
• Sociolinguistic Competence and Pragmatics: Study how social context influences language use and understanding.
• Gender and Identity in Language Learning: Investigate how gender identity affects language learning experiences.
• Intercultural Competence in Language Teaching: Develop strategies for promoting intercultural communicative competence in language learners.
• Language Policy and Minority Language Education: Analyze the impact of language policies on the education of minority language speakers.
• Gender and Language Learning Strategies: Investigate gender differences in language learning strategies and their implications for instruction.
• Code-Switching in Multilingual Classrooms: Study the role of code-switching in language learning and classroom interaction.

Learner Diversity and Inclusive Practices

• Teaching English to Young Learners (TEYL): Examine effective teaching strategies for children learning English.
• Addressing Learning Disabilities in ELT: Investigate methods for supporting learners with disabilities in language learning.
• ELT for Specific Purposes (ESP): Explore specialized English language instruction for specific fields.
• Differentiated Instruction in Language Teaching: Develop strategies for addressing diverse learner needs in the language classroom.
• Inclusive Pedagogies for Learners with Special Educational Needs: Design instructional approaches that accommodate learners with disabilities in language learning.
• Language Learning Strategies of Autistic Learners: Investigate effective language learning strategies for individuals on the autism spectrum.
• Language Identity and Learner Motivation: Explore the relationship between language identity and motivation in language learning.

Policy and Planning in ELT

• National and International Language Policies: Analyze policies governing English language education at different levels.
• ELT Program Implementation Challenges: Identify challenges in implementing ELT programs in diverse contexts.
• Role of ELT in National Development: Examine the contribution of English language education to national development goals.
• English as a Medium of Instruction (EMI) Policies: Analyze the impact of EMI policies on educational equity and access.
• Language Teacher Recruitment and Deployment Policies: Evaluate policies related to the recruitment and deployment of language teachers in diverse contexts.
• Language Assessment Policy Reform: Propose reforms to language assessment policies to promote fairness and validity.
• Biliteracy Development Policies: Study policies aimed at promoting biliteracy development among bilingual learners.

Research Methodologies in ELT

• Qualitative Research Methods in ELT: Explore qualitative approaches like interviews and case studies in ELT research.
• Quantitative Research Methods in ELT: Investigate quantitative methods such as surveys and experiments in language education research.
• Mixed-Methods Approaches in ELT Research: Combine qualitative and quantitative methods to gain a comprehensive understanding of research questions.
• Ethnographic Approaches to ELT Research: Conduct ethnographic studies to explore language learning and teaching in naturalistic settings.
• Case Study Research in Language Education: Investigate specific language learning contexts or programs through in-depth case studies.
• Corpus Linguistics in ELT Research: Analyze language use patterns and learner language production using corpus linguistic methods.
• Longitudinal Studies of Language Learning: Follow language learners over an extended period to examine developmental trajectories and factors influencing language acquisition.

Future Trends and Innovations

• Emerging Technologies in ELT: Study the integration of technologies like AI and VR in language teaching.
• Innovations in Teaching Strategies: Explore new approaches to teaching language, such as flipped classrooms and gamification.
• Future Directions in ELT Research: Investigate potential areas for future research in English language teaching.
• Wearable Technology in Language Learning: Explore the potential of wearable devices for delivering personalized language instruction.
• Data Analytics for Adaptive Learning: Develop data-driven approaches to adaptive learning in language education.
• Augmented Reality (AR) Applications in ELT: Design AR-enhanced language learning experiences for immersive language practice.
• Global Citizenship Education and Language Learning: Investigate the role of language education in fostering global citizenship skills.
• Eco-Linguistics and Language Education: Explore the intersection of language education and environmental sustainability.
• Metacognition and Language Learning: Explore how learners’ awareness of their own learning processes affects language acquisition.
• Peer Interaction in Language Learning: Investigate the role of peer collaboration and discussion in promoting language development.
• Heritage Language Education: Study strategies for maintaining and revitalizing heritage languages among immigrant and minority communities.
• Language Learning Motivation in Adolescents: Examine factors influencing motivation and engagement in adolescent language learners.
• Phonological Awareness in Language Learning: Investigate the role of phonological awareness in literacy development for language learners.
• Pragmatic Development in Language Learners: Explore how learners acquire pragmatic competence and understanding of language use in context.
• Digital Literacies and Language Learning: Examine how digital literacy skills contribute to language proficiency and communication in the digital age.
• Critical Language Awareness: Investigate approaches to developing learners’ critical awareness of language use and power dynamics.
• Language Teacher Identity: Study how language teachers’ identities shape their beliefs, practices, and interactions in the classroom.
• Collaborative Learning in Language Education: Explore the benefits and challenges of collaborative learning environments for language learners.
• Motivational Strategies in Language Teaching: Develop and evaluate motivational techniques to enhance student engagement and persistence in language learning.
• Heritage Language Maintenance: Investigate factors influencing the maintenance and transmission of heritage languages across generations.
• Phonics Instruction in Language Learning: Examine the effectiveness of phonics-based approaches for teaching reading and pronunciation.
• Language Policy Implementation: Analyze the challenges and successes of implementing language policies at the institutional, regional, and national levels.
• Language Teacher Cognition: Explore language teachers’ beliefs, knowledge, and decision-making processes in the classroom.
• Intercultural Communicative Competence: Develop strategies for fostering learners’ ability to communicate effectively across cultures.
• Critical Pedagogy in Language Education: Explore approaches to teaching language that promote critical thinking, social justice, and equity.
• Language Learning Strategies for Autodidacts: Investigate effective self-directed learning strategies for language learners outside formal educational settings.
• Content and Language Integrated Learning (CLIL) in Higher Education: Examine the implementation and outcomes of CLIL programs in tertiary education.
• Sociocultural Theory and Language Learning: Explore how social and cultural factors influence language acquisition and development.
• Language Socialization: Investigate how individuals learn language within social and cultural contexts, including family, peer groups, and communities.
• Speech Perception and Language Learning: Examine the relationship between speech perception abilities and language proficiency in second language learners.
• Genre-Based Approaches to Language Teaching: Explore the use of genre analysis and genre-based pedagogy to teach language skills in context.
• Learner Autonomy in Language Learning: Investigate strategies for promoting learner autonomy and independence in language education.
• Multimodal Literacy in Language Learning: Examine the integration of multiple modes of communication, such as text, image, and sound, in language instruction.
• Community-Based Language Learning: Study language learning initiatives that engage learners with their local communities and resources.
• English as a Lingua Franca (ELF) Communication: Explore the use of English as a global means of communication among speakers from diverse linguistic backgrounds.

Research in English Language Teaching covers a wide range of topics, from language acquisition theories to the impact of technology on learning. By exploring these topics (from a list of research topics in english language teaching), we can improve how English is taught and learned, making it more effective and accessible for everyone.

Continuous research and collaboration among educators, researchers, and policymakers are essential for the ongoing development of ELT.

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REVIEW article

Historical linguistics of sign languages: progress and problems.

• Department of Linguistics, University of Texas at Austin, Austin, TX, United States

In contrast to scholars and signers in the nineteenth century, William Stokoe conceived of American Sign Language (ASL) as a unique linguistic tradition with roots in nineteenth-century langue des signes française , a conception that is apparent in his earliest scholarship on ASL. Stokoe thus contributed to the theoretical foundations upon which the field of sign language historical linguistics would later develop. This review focuses on the development of sign language historical linguistics since Stokoe, including the field's significant progress and the theoretical and methodological problems that it still faces. The review examines the field's development through the lens of two related problems pertaining to how we understand sign language relationships and to our understanding of cognacy, as the term pertains to signs. It is suggested that the theoretical notions underlying these terms do not straightforwardly map onto the historical development of many sign languages. Recent approaches in sign language historical linguistics are highlighted and future directions for research are suggested to address the problems discussed in this review.

Introduction

Today, signers and scholars alike commonly view each sign language as representing a distinct linguistic tradition. We consider American Sign Language to be distinct from British Sign Language in part because distinct linguistic conventions have respectively evolved within the American and British signing communities. We also recognize the recent genesis of new traditions, such as the emergence of Nicaraguan Sign Language beginning in the 1970s ( Polich, 2005 ) and of Israeli Sign Language beginning in the 1930s ( Meir and Sandler, 2008 ). According to this contemporary view, a view that developed in significant part due to the ideas of William Stokoe, sign languages have histories.

However, a different view of sign languages, a universalist view, was common in the eighteenth and nineteenth centuries, the period during which many contemporary sign languages emerged in connection with schools for the deaf. Earlier scholars and signers thought of signed language as a universal human language, “the native language of man” ( Peet, 1853 ). For this reason, signed language was commonly called “the language of signs,” without social or geographic modifiers ( Baynton, 1996 ). Insofar as differences were recognized in the signing of geographically distinct communities, the differences were likened to dialectal variation in one common language ( Peet, 1853 ; Baynton, 2002 ). Thus, Laurent Clerc of France, shortly after arriving in the U.S. in 1816 and upon meeting Alice Cogswell, who would become his first student at the American School for the Deaf, was not surprised to find that he could easily communicate with her in sign: “so true it is, as I have often mentioned before, that the language of signs is universal and as simple as nature” ( Clerc, 1852 , p. 107).

As a universal language, signed language was not thought to have a historical dimension in the same way that spoken languages were thought to have. Around the mid-nineteenth century, August Schleicher and others had begun to trace the ramification of eight spoken language families from Indo-European (e.g., Schleicher, 1853 ). In roughly the same period, Thomas H. Gallaudet (1847 , p. 56) theorized that the “natural language of signs” had its origins in deaf children's “natural, spontaneous facility.” Gallaudet and his contemporaries held that the similarity of signs among deaf students in schools across Europe and the U.S., and even among Native American signers, had a simple explanation: “[these signs] originate from elements of this sign-language which nature furnishes to man wherever he is found” ( Gallaudet, 1847 , p. 59). On this view, as the universal, natural expression of all humans, both deaf and hearing, signed language transcended history. When nineteenth-century scholars of signed language, most of whom were professional educators, wrote about history, they most often had in mind the history of pedagogical approaches—with particular focus on manualist vs. oralist methods in deaf education—but not the history of the sign languages that had developed in signing communities ( Baynton, 1996 ; Edwards, 2012 ).

How has the contemporary view of sign languages as distinct traditions, each with its own unique history, come to differ so markedly from the earlier universalist view? Stokoe's work represents one critical inflection point in the intellectual history of the study of signed language and in the development of the historical linguistics of sign languages. For Stokoe (1960 , p. 5) “the natural language of signs” was a “false entity.” In contrast to the views of his universalist predecessors, Stokoe (1960 , p. 3) held that a “natural” sign language was “a language system of visual symbols” embedded in a language community, such as “the sign language of the American deaf.” Although historical linguistics was not the primary focus of Stokoe's scholarship, he conceived of ASL as a unique linguistic tradition with roots in nineteenth-century langue des signes française (LSF), a conception that is apparent in his earliest scholarship on ASL ( Stokoe, 1960 ; Stokoe et al., 1965 ). Thus, Stokoe contributed to the theoretical foundation upon which linguists would study not only the history of ASL but also the histories of many other sign languages. Only when sign languages came to be seen as the linguistic traditions of distinct signing communities could broader questions be foregrounded about their histories; and only then could a discipline develop that would focus on the historical linguistics of sign languages.

Sign Language Historical Linguistics Since Stokoe

Historical linguistics is broadly interested in understanding language change, including how languages change as they diversify from a common ancestral language and how languages change as the speakers and signers of distinct languages come into contact with one another. One principal aspect of the endeavor to understand language change has been the study of language relationships, an area that encompasses the reconstruction of protolanguages, the classification of languages in families, and the subgrouping of more closely-related languages within those families. Following Stokoe, the study of language relationships among sign languages has arguably been the primary area of focus for sign language historical linguists. When sign languages were seen to represent distinct linguistic traditions, the question naturally arose as to how those distinct traditions have developed in relation to one another.

From the 1960s onward, sign scholars have made important advances in our understanding of the histories of many sign languages and of language change in the gestural-visual modality; many of these advances are highlighted in Section Early progress in sign language historical linguistics. Notwithstanding these considerable achievements, I will argue that there remain fundamental theoretical and methodological problems that hinder further progress in sign language historical linguistics. Sign scholars have adopted notions from traditional historical linguistics, such as the language family and cognacy, to theorize the relationships of sign languages and the historical relations of their constituent signs and features. Scholars have also adapted historical comparative methods from that discipline, such as lexicostatistics, to study sign language relationships. The appropriateness of these theories and methods to the historical study of sign languages has, in my view, received insufficient attention to date.

Here I examine the development of sign language historical linguistics since Stokoe through the lens of two related problems pertaining to how we understand sign language relationships and to our understanding of cognacy, as that notion is used to describe the historical relations of signs. I will argue that the relevant theories and methods from historical linguistics do not straightforwardly map onto the historical development of many sign languages. I show how, in light of the problems highlighted here, sign scholars have developed alternative approaches to study the histories of sign languages. While these innovative approaches have provided insights into the histories of many sign languages, I will show that, in some cases, they have also masked important characteristics of sign language change.

In Section Relationships among spoken languages and among signed languages, I examine the first problem, which concerns our theorization of sign language relationships. Do sign languages that are said to be historically related indeed share the same type of relationship that characterizes the spoken languages in a language family ( Zeshan, 2006 , 2013 ; Campbell, 2018 ; Reagan, 2021 )? I will show that assumptions underlying theories about spoken language relationships, specifically those pertaining to the intergenerational transmission of language, do not hold for the diversification of sign languages in many sign language families.

The second problem (Section The identification of cognates) concerns our understanding of the cognacy relation among signs. This problem has both a theoretical and a methodological dimension. The theoretical dimension of this problem is related to the first problem mentioned above—the cognacy relation in traditional historical linguistics obtains only among lexical items and linguistic features that have been inherited via a specific process of diversification (e.g., Thomason and Kaufman, 1988 ; Ringe et al., 2002 ). Where this process has not characterized the diversification of sign languages, the cognacy relation may not be appropriate to describe the historical relations of signs. The methodological problem concerns our ability to identify patterns that uniquely differentiate inherited signs from those that have entered a language via processes other than inheritance, such as borrowing. I will show that sign scholars have not yet developed rigorous methods for identifying inherited signs. I argue that, lacking such methods, it is more appropriate to understand the relations of signs among sign languages that are thought to be related as an etymological relation, rather than a cognacy relation.

Early Progress in Sign Language Historical Linguistics

Stokoe's work on ASL played a pivotal role in the recognition that sign languages indeed have a historical dimension, but progress in understanding the particular histories of these languages, their relationships, and the processes driving historical change in them has been the work of other scholars. These scholars have benefited from the methodological and theoretical developments of the past two centuries in historical linguistics. Early in the development of sign language historical linguistics, lexicostatistics and glottochronology, quantitative approaches that had been developed to study the histories of spoken languages (e.g., Swadesh, 1955 ; Gudschinsky, 1956 ), were adapted to the study of sign language data, as was Swadesh's list of basic vocabulary ( Woodward, 1978 ). In interpreting the results of these methods, scholars adopted from historical linguistics the same metaphors to describe language relationships, such as the language family, that had developed in that discipline (see Reagan, 2021 for a recent discussion). They also adopted much of the same terminology that had developed to describe the historical relations of words, such as the relations of cognacy and borrowing, and applied these same notions to the historical relations of signs ( Woodward, 1978 , 1991 ). The emergence of many sign languages was theorized in terms that had developed for the analysis of spoken languages. For example, the emergence of ASL was characterized by some scholars as a creolization process with parallels to the emergence of spoken language creoles ( Fischer, 1978 ; Woodward, 1978 ; Meier, 1984 ; but see Lupton and Salmons, 1996 ).

As with the study of language relationships, the study of change in sign languages was influenced by the theories and methods of traditional historical linguistics. Frishberg's (1975) seminal study of historical change in ASL drew connections between the processes driving change in that language and processes such as assimilation and lexicalization in diachronic change in spoken languages. Frishberg argued that other changes, such as the centralization of signs articulated below the neck and the lateralization of signs articulated at the face, reflected tendencies toward articulatory and perceptual ease. Both of these mechanisms of change have parallels in theories of spoken language change ( Ohala, 1981 , 1993 ). Battison et al. (1975) adopted the type of variationist approach that had been introduced by Weinreich et al. (1968) to argue that thumb extension in a class of ASL signs—specifically, signs with an extended index finger—represented a historical change in progress in the American deaf community.

By adapting the methods and theories of historical linguistics to the study of sign languages, early scholars made important advances in our understanding of sign language relationships. Woodward (1978) showed that historical relationships among sign languages can be reflected in contemporary linguistic data. Based on quantitative measures of shared cognates, he estimated that ASL and LSF—two languages that were thought to be related on extralinguistic grounds—share 61% of their basic vocabularies. He also studied the intergenerational transmission of ASL signs in the American deaf community, finding that greater than 99% of the signs seen in videos of ASL signers from the early twentieth century have reflexes in contemporary ASL. Thus, Woodward's early work suggested that a historical signal can be identified and measured both in the diversification of sign languages and in the intergenerational transmission of a sign language.

Other studies suggested that related and unrelated sign languages could be reliably differentiated by using the historical comparative methods that had been adapted to study sign languages. In their comparison of British, Australian, and New Zealand Sign Languages, three languages that were hypothesized to be related, McKee and Kennedy (2000) found that between 79 and 87% of these languages' basic vocabularies were cognate—though their operationalization of the term “cognate,” and perhaps also their theory underlying that notion, differed from Woodward's (see Woodward, 2011 for a discussion). In contrast, when these languages were compared with ASL, which was hypothesized to be unrelated to any of the other languages, only between 26 and 32% of their basic vocabularies were found to be, in their terms, cognate. Similarly, in a study of the sources of vocabulary in Lengua de Señas Mexicana (LSM), Guerra Currie et al. (2002) found a relatively high percentage of phonologically-similar vocabulary (38%) when comparing that language with LSF, a language that was hypothesized to be related. In contrast, when comparing LSM with Lengua de Signos Española and with Nihon Syuwa (Japanese Sign Language)—two languages thought to be unrelated to LSM—the percentages of phonologically-similar vocabulary were lower (33 and 23%, respectively). 1

As in the two studies just mentioned, the methods first used by Woodward to study the relationship of ASL and LSF have been applied to study sign language relationships in other parts of the world. Woodward himself conducted several historical comparative studies of sign languages in Costa Rica, South Asia, Thailand, and Vietnam ( Woodward, 1991 , 1993 , 1996 , 2000 , 2011 ). In each of those studies, Woodward used lexicostatistical methods together with quantitative thresholds that were based on expected levels of shared cognates to decide whether the sign varieties that he studied were dialects of the same language. Sign varieties that were inferred to be distinct languages were classified into families. In more recent work, Clark (2017) used a similar approach to study sign varieties in Peru, finding that there are two distinct sign languages in use in that country and that a third variety is a hybridized variety with elements of the two distinct languages. Other scholars have adapted Woodward's methods to argue for the historical relationships, inter alia, of sign languages in Eastern Europe, such as Russkii Zhestovyi Yazyk and Ukrayinska Zhestova Mova (Russian and Ukrainian Sign Languages; Bickford, 2005 ), of Nihon Syuwa and Táiwān Shǒuyǔ (Japanese and Taiwan Sign Languages; Sasaki, 2007 ), and of sign languages in the Middle East, such as Lughat il-Ishaarah il-Urduniah and Lughat al-Ishārāt al-Filisṭ &# x00131;̄niyyah (Jordanian and Palestinian Sign Languages; Al-Fityani and Padden, 2010 ).

In addition to the advances in our understanding of the historical relationships among sign languages and in the methods for studying those relationships, sign scholars have also made progress in understanding language change in the gestural-visual modality. Radutzky's (1989) study of historical change in Lingua dei Segni Italiana (LIS) investigated the categories of change that had been identified in Frishberg (1975) . She found that many of the same diachronic changes that Frishberg had described for ASL, such as changes in the shape of the nondominant hand and in the lateralization of signs articulated at the face, had also occurred in LIS. She also found that one diachronic change in LIS paralleled the type of change in thumb extension that had been identified by Battison et al. (1975) as an ongoing change in the American deaf community. As with Frishberg's account of diachronic changes in ASL, Radutzky identified articulatory and perceptual ease as important drivers of change in LIS.

Like Frishberg, Supalla and Clark (2015) investigated historical sources—particularly, video recordings of ASL signers in the early twentieth century—to understand the origins of lexical signs and grammatical constructions in ASL. Their analysis of video recordings in addition to more static sources, such as historical dictionaries (see Frishberg's analysis of Long, 1918 ), allowed them to observe historical signs in a range of phrase- and discourse-level contexts. They observed that many signs in contemporary ASL have developed from historical compounds and collocations, which have undergone diachronic processes of reduction and semantic shift. They argued that many changes affecting forms in the ASL of the early twentieth century had been driven by grammaticalization processes (see Hopper and Traugott, 1993 ).

Just as Battison et al. (1975) used a variationist approach to study changes in handshapes, later scholars took a similar approach to investigate changes in the locations of signs. Lucas et al. (2001) examined a class of signs in ASL that is defined phonetically by articulation at the forehead or temple in citation form. They found a positive correlation between the height of signers' articulations and their ages: older signers produced more tokens at higher locations on the head, while middle-aged and younger signers produced more tokens with lower articulations. The authors tentatively concluded that the differences in location in this class of signs represented a change in progress in the American deaf community. In a study examining a similar class of signs in Australian and New Zealand Sign Languages, Schembri et al. (2009) also found that sign articulations were positively correlated with signers' ages. In both studies, the authors hypothesized that the mechanism driving the diachronic changes was articulatory ease, since higher articulations presumably require more effort compared to lower articulations ( Mauk, 2003 ; Napoli et al., 2014 ).

In sum, the preceding brief survey of sign language historical linguistics has highlighted two critical areas of progress since Stokoe. First, scholars have developed methods that can identify historical signal in contemporary sign data; that historical signal is sufficiently robust to differentiate sign languages that are thought to be related on extralinguistic grounds from those that are thought to be unrelated. Second, real time and apparent time studies of change in sign languages have identified diachronic changes that have occurred in more than one sign language. These discoveries suggest that the field might eventually identify a comprehensive set of common diachronic changes that occur in languages in the gestural-visual modality. The changes that have already been identified have been argued to be driven by mechanisms, such as ease of articulation and perception, that have also driven many changes in spoken languages.

Relationships Among Spoken Languages and Among Signed Languages

What does it mean to say that languages are related ? The word related has multiple senses; one of these senses means “connected or having relation to something else” ( Oxford English Dictionary, 2021b ). Thus, one answer to the initial question could be that two languages are related—that is, connected—if they share words or linguistic features. This view of language relationships would be unconcerned with how shared words and features have entered languages; instead, the main consideration on this view would be how closely connected, or perhaps how similar, the two languages are at a particular point in time, given some metric of connection. Hence two previously unrelated languages could become related, if, for example, the speakers of these languages begin to borrow words from one another; conversely, two related languages could become unrelated, if speakers would cease to use the words or features they once had in common. Because the connections among languages and their similarity may change over time, so too, on this view, might language relationships change.

The term related in traditional historical linguistics differs from the view just described. When deciding whether two languages are related, historical linguists are not concerned with their similarity or with connections among their speakers per se , but rather with the processes that have resulted in these languages' shared words and features. Language relationships in historical linguistics are theorized in a way that parallels the evolutionary relationships of organisms ( Atkinson and Gray, 2005 ). For example, birds and bats share many morphological similarities; yet from an evolutionary perspective, bats are more closely related to humans than they are to birds because bats and humans share a more recent common ancestor ( Morrison et al., 2015 ).

In historical linguistics, common ancestry has been fundamental to the meaning of language relationships. Just as offspring inherit DNA from an ancestor, a younger generation of speakers is thought to acquire, or inherit, a language system from an older generation, including that language's words and features. For example, the Proto-West-Germanic verb * laidijan “lead” ( Ringe and Taylor, 2014 ) is thought to have been inherited by successive generations of children along a chain of language transmission events down to the present day. As Proto-West-Germanic diversified, * laidijan came to be inherited in distinct speech communities, in which the word subsequently underwent distinct sound changes, resulting in, for example, Old English ( lædan ), Old Dutch ( leiden ), and Old High German ( leiten ) ( Ringe and Taylor, 2014 ). Although the contemporary reflexes of these words—namely, English lead , Dutch leiden , and German leiten —differ in their phonological forms, they have all been inherited along chains of language transmission events that trace back to a common ancestor, namely, Proto-West-Germanic.

In contrast to the process of inheritance, consider the process of borrowing, which represents a different pathway by which words and linguistic features may enter a language. During the 1940s, adult speakers of American English, initially soldiers, evidently borrowed the word ‘honcho', meaning leader or person in charge, from Japanese hancho [ han “corps, squad” and cho “head, chief”; ( Online Etymological Dictionary, 2021 ; Oxford English Dictionary, 2021a )]. Although in this case a word with etymological origins in Japanese entered into American English, and although American English and Japanese have become, in a sense, more closely connected after this borrowing event, historical linguists would not say that the two languages are related because of the borrowing event. The American English word honcho and the Japanese word hancho were not intergenerationally inherited from a common ancestral language as constituents of that language system.

Genetic Language Relationships

Characteristics of the language transmission process itself play a fundamental role in how language relationships are understood in historical linguistics. 2 These characteristics are not fixed; instead, language transmission is sensitive to social and cultural variation. The network of social connections through which language transmission occurs can differ. For example, language can be transmitted from parent to child, from nonparental adult to child, and among peers; and many children are exposed to multiple languages along these various pathways ( Cavalli-Sforza and Feldman, 1981 ; Mufwene, 2008 ). The typical settings within which language is transmitted can also differ. For example, in some speech communities, language may be primarily transmitted to children in the home, at least early on. Sign languages too may be primarily transmitted to children in the home in some village signing communities ( Zeshan and de Vos, 2012 ), in multi-generational family signing communities ( Dikyuva, 2012 ), in relatively small networks of families with deaf members ( Hou, 2016 ), and, in general, in any setting in which older generations sign with younger generations ( Newport and Meier, 1985 ; van den Bogaerde and Baker, 2016 ; German, 2021 ). But, in some signing communities, an important setting for language transmission to children has been the deaf school and dormitory ( Singleton and Meier, 2021 ).

Language transmission can also occur at differing ages and hence at differing stages of cognitive development. Power and Meier (2021) report that there were few young children at the American School for the Deaf in Hartford during the school's first 50 years because its minimum age for admission was 8 years old or higher. Less than 1% of 1,700 students were under age 8 at enrollment during that period, and the average age at enrollment was 14.4 years old ( SD = 5.2 years). The school's admission policy likely caused many deaf children, particularly those without access to visual language at home, to experience language deprivation in childhood, an experience which can have negative consequences for language acquisition. The age at which an individual acquires a sign language has been shown to affect language processing ( Morford, 2003 ), second language acquisition ( Mayberry et al., 2002 ), as well as the acquisition of verbs and basic word order in ASL ( Newport, 1988 ; Cheng and Mayberry, 2020 ). When late learners transmit language to a subsequent generation, the language system itself may have varying levels of complexity and consistency ( Senghas and Coppola, 2001 ; Singleton and Newport, 2004 ). In sum, it seems that many aspects of the language transmission scenario can vary—including characteristics of the transmitter, transmission pathway, language, setting, and acquirer.

Among the overall set of potential language transmission scenarios, one scenario has been termed normal , or typical, because it arguably occurs under typical social conditions. 3 According to Thomason and Kaufman (1988 , p. 9–10), normal transmission occurs “from parent generation to child generation and/or via peer group from immediately older to immediately younger, with relatively small degrees of change over the short run, given a reasonably stable sociolinguistic context.” When successive generations inherit a language via this type of transmission, the process results in a chain of languages, each one having been derived from the immediately preceding language. Ringe et al. (2002 , p. 63) refer to this process as linguistic descent , which they define in the following way: “A language (or dialect) Y at a given time is said to be descended from language (or dialect) X of an earlier time if and only if X developed into Y by an unbroken sequence of instances of native-language acquisition by children.” The process parallels asexual biological reproduction in that each derived language is thought to have just one antecedent language.

The notions of normal transmission and linguistic descent have been critical to the understanding of language relationships in historical linguistics. Languages are related and belong to the same language family if they are derived via linguistic descent from a common ancestral language ( Thomason and Kaufman, 1988 ; Thomason, 2002 ; but see DeGraff, 2001 ; Mufwene, 2003 for critiques). In the terminology of many historical linguists, languages that are related in the way just described are said to share a specifically genetic relationship.

Nongenetic Language Relationships?

How do we characterize the relationships of languages that are not derived from a common ancestral language via linguistic descent? Historical linguists consider many languages, such as English and Japanese, to be unrelated because no plausible common ancestral language has yet been reconstructed for them; and perhaps none can be, if no such ancestral language existed. English and Japanese have genetic relationships to other languages—just not to each other. Language isolates, such as Basque and Ainu, are also thought to lack genetic relationships to any existing or extant languages ( Campbell, 2013 ). However, language isolates may once have had genetic relationships to some language or group of languages that are now extinct. And, importantly, an isolate is presumably linked via linguistic descent to antecedent stages in its own historical development.

What happens if the chain of linguistic descent is broken in a language's historical development—as the development of a creole language has been thought to entail? What if the intergenerational transmission of language differs from the type of transmission described above? How do we characterize the relationships of languages that have not developed via linguistic descent? According to Thomason and Kaufman (1988 , p. 10), if the chain of linguistic descent is broken at any point, the relationship between languages on either side of the break is not genetic: “the label ‘genetic relationship' does not properly apply when transmission is imperfect.” In addition, as we have seen, in linguistic descent exactly one ancestral language develops into a derived language. Thus, any language that is descended from more than one ancestral language—as creole languages and many sign languages are thought to be—has no genetic relationships to any antecedent language or to any other languages that have descended from those antecedents. These languages with multiple sources “[have] followed a nongenetic pathway of development” ( Thomason and Kaufman, 1988 , p. 8).

Scholars of creole languages have debated how to characterize the relationships of a creole to its lexifier and its substrates ( DeGraff, 2001 ; Thomason, 2002 ; Mufwene, 2003 ). How does a creole's history connect with the histories of the languages that have, at least in part, formed the basis of its lexicon and grammar? If linguistic descent is taken to be definitional in the theory of language relationships, a creole has no genetic relationship to its antecedents because its linguistic system has multiple sources. For example, Thomason and Kaufman (1988 , p. 11) contend that mixed languages “by definition...are unrelated genetically to the source(s) of any of their multiple components”; and, similarly, that “a claim of genetic relationship entails systematic correspondences in all parts of the language because this is what results from normal transmission: what is transmitted is an entire language.” Thus, on this view, any language with heterogeneous sources has no genetic relationships to its antecedents or to the contemporary languages that have descended from those antecedents. While these relationships are not considered genetic, the theory does not make clear how to positively define the relationship; witness the unwieldy term “genetic nonrelatedness” in Thomason (2002 , p. 105).

The Diversification of Sign Languages via Processes Other Than Linguistic Descent

Sign languages have been grouped into language families based on a variety of types of evidence, including extra-linguistic evidence, such as historical connections among deaf educators and educational institutions, linguistic evidence, and a combination of both types of evidence (see Fischer, 2015 ; Reagan, 2021 for recent discussions). For example, contemporary ASL and LSF are typically classified together with other sign languages that have some historical connection to the variety or varieties of LSF used in eighteenth- and nineteenth-century schools for the deaf in France, including European sign languages such as Nederlandse Gebarentaal, Teanga Chomhartha í ochta na hÉireann , and Lingua dei Segni Italiana (Sign Language of the Netherlands, Irish Sign Language, and Italian Sign Language) and sign languages of Latin America such as Lengua de Señas Mexicana and L í ngua Brasileira de Sinais ( Anderson, 1979 ; Quer et al., 2010 ; Abner et al., 2020 ; Power et al., 2020 ). Other proposed sign language families include, inter alia, the family of British, Australian, and New Zealand Sign Languages ( McKee and Kennedy, 2000 ), the family including svenskt teckenspråk and L í ngua gestual portuguesa (Swedish and Portuguese Sign Languages; Bergman and Engberg-Pedersen, 2010 ), and the family including Nihon Syuwa, Táiwān Shǒuyǔ , and Hanguk Sueo (Japanese, Taiwan, and Korean Sign Languages; Sasaki, 2007 ).

However, many languages in the sign language families that have been proposed to date evidently are not derived via linguistic descent from a common ancestral language because, (i) as with creole languages, many sign languages are thought to have multiple sources; and (ii) the diversification of these languages implicated a break in their intergenerational transmission. First, some scholars have characterized the emergence of ASL as the creolization of LSF with the indigenous sign varieties of nineteenth-century American deaf signers ( Woodward, 1978 ; Groce, 1985 ). Fischer (1978 , p. 329) hypothesized that ASL has been “recreolized” by deaf children in each generation since the early nineteenth century (see also Meier, 1984 ) because most deaf children do not acquire ASL from birth—roughly 90% do not ( Mitchell and Karchmer, 2004 ). Guerra Currie (1999) speculates that Lengua de Señas Mexicana may have emerged in a similar way—that is, the indigenous sign varieties of Mexican deaf signers may have creolized with LSF in the emergence of Lengua de Señas Mexicana . The emigration to Israel of Jewish deaf people from a variety of countries in the first half of the twentieth century is thought to have played an important role in the diversification of that language from Deutsche Gebärdensprache (German Sign Language) and other sources ( Meir and Sandler, 2008 ). Insofar as the emergence of these and other sign languages have implicated multiple sources, they may not be genetically related to each other in the way that the languages in a spoken language family have been thought to be.

Second, many of the historical relationships among sign languages that are thought to have resulted from connections among deaf institutions and the travels of deaf educators have not been characterized by linguistic descent. For example, the historical relationship between ASL and LSF is understood to be based in large part on the transmission of LSF by Laurent Clerc, a deaf educator who moved from Paris to the U.S. in 1816 in order to teach at the American School for the Deaf in Hartford ( Edwards, 2012 ). Clerc himself had acquired LSF at the age of 12, when he moved to Paris from La Balme to attend the Paris National Institute ( Lane, 1984 ). Arguably, Clerc's acquisition of LSF does not straightforwardly map onto the type of intergenerational transmission said to define genetic spoken language relationships because he did not acquire that language as a child. Additionally, as we have seen, some 99% of Clerc's students in Hartford during the school's first 50 years were above the age of 8 at the time of their enrollment; and the average student enrolled in adolescence ( Power and Meier, 2021 ). Thus, both Clerc's acquisition of LSF and his transmission of that language to his American students arguably were not characteristic of linguistic descent, in the sense under discussion here. Instead, the diversification of ASL from a nineteenth-century variety of LSF evidently entailed a break in the intergenerational transmission of that language.

As with the early development of ASL, the diversification of many other sign languages may not have occurred via linguistic descent. For example, another French deaf educator, Édouard Huet, who had apparently acquired LSF at age 12, established schools for the deaf in Brazil (est. 1857) and Mexico (est. 1867; Guerra Currie, 1999 ). The sign languages that later developed in those countries—namely, L í ngua Brasileira de Sinais and Lengua de Señas Mexicana —have been thought to be historically related to LSF ( Quinto-Pozos, 2008 ). However, while Huet may have driven the establishment of the schools in Brazil and Mexico, Ramsey and Quinto-Pozos (2010 , p. 49–50) speculate that, in Brazil, Huet's LSF-origin signs may have “mixed with the varieties of signing that Brazilian Deaf students brought to the school”; and, regarding Mexico, the authors report that “neither sign-medium instruction nor Deaf teachers played a major role in the school” following its establishment.

A deaf Norwegian, Andreas Christian Møller, began attending the school for the deaf in Copenhagen at age 16; he later returned to Norway and established the first school for the deaf in that country in Trondheim ( Greftegreff et al., 2015 ). Norsk tegnspråk and Dansk tegnsprog (Norwegian and Danish Sign Languages) have been thought to be historically related ( Schröder, 1993 ). In sum, the diversification of L í ngua Brasileira de Sinais and Lengua de Señas Mexicana from a nineteenth-century variety of LSF and of Norsk tegnspråk from a nineteenth-century variety of Dansk tegnsprog evidently occurred via transmission from late learners of those languages.

While Huet and Møller were themselves deaf, the diversification of many other sign languages has occurred in part via hearing educators, who were not likely native users of those languages. For example, a hearing priest, Father Tomaso Silvestri, received training in sign language and in pedagogical methods at the Paris National Institute before founding the first public school for the deaf in Italy in 1784 ( Quer et al., 2010 ). A hearing educator of the deaf from Sweden, Per Aron Borg, helped to establish a school for the deaf in Portugal (est. 1823–1828), in which he introduced aspects of svenskt teckenspråk to his Portuguese deaf students ( Bergman and Engberg-Pedersen, 2010 ). A hearing teacher, Dorcas Mitchell, introduced a variety of British Sign Language to deaf students in New Zealand in 1868 ( Schembri et al., 2010 ). 4 Hearing Irish nuns, after learning a variety of LSF during a visit to a school in Normandy, introduced that variety in a school for female deaf students in Dublin; later, the nuns shared their variety with hearing teachers at another school for male deaf students in Dublin ( LeMaster and Dwyer, 1991 ). A variety of BSL was introduced by a hearing teacher and her two deaf children, who had moved from England to establish the first school for the deaf in Uganda ( Lule and Wallin, 2010 ; Lutallo-Kiingi and De Clerck, 2015 ). The origins of Ishorai Tojiki (Tajik Sign Language) have been linked to the introduction of a second language variety of Russkii Zhestovyi Yazyk (Russian Sign Language) by a group of hearing educators in the former Soviet Union, who established a school for the deaf in Tajikistan around the 1940s ( Power, 2020 ). In each of these cases, and in many other cases around the world like them, sign languages have been classified in the same language family, even though their diversification has not occurred via successive instances of the native acquisition of language by children—that is, not via linguistic descent.

Not all sign languages have diversified in close connection with educational institutions in the ways just described. For example, the diversification of Australian Sign Language may have initially occurred via the migration of at least one signer of British Sign Language, John Carmichael, who had attended the school for the deaf in Edinburgh ( Schembri et al., 2010 ). Other British Sign Language users immigrated to Australia soon after, such as Carmichael's schoolmate, Thomas Pattison, who would later establish the first school for the deaf in Australia in 1860 ( Schembri et al., 2010 ). Carmichael had five children, at least one of whom, Edward Feeney Carmichael, was deaf ( Eaton, 2015 ). Thus, following their presumptive native acquisition of British Sign Language from their father, Carmichael's hearing children and his deaf son may have played a role in the diversification of Australian Sign Language from the British Sign Language of the nineteenth century via linguistic descent. However, Carmichael himself apparently began attending the Edinburgh school at age 9 ( Eaton, 2015 ); similarly, Pattison may have begun his studies there at around age 8 ( Cooper, 2014 ). Prior to their attendance at the Edinburgh school, it is unclear whether either of these individuals had had any exposure to British Sign Language. When viewed through the lens of the theory of genetic language relationships, these signers' relatively late acquisition of British Sign Language may have resulted in a break in the type of chain of child language acquisition events that has been thought to characterize linguistic descent ( Ringe et al., 2002 ; see Section Genetic language relationships).

In sum, the relationships of sign languages in many sign language families arguably differ from the types of relationships that are thought to characterize spoken language families because, in many cases, the diversification of languages in these sign families has not occurred via linguistic descent. The diversification of many sign languages from antecedent sign languages—such as the diversification of ASL from LSF—may more closely resemble the process described by Mufwene (2009) as “indigenization.” In the context of the diversification of world Englishes from varieties of British English, Mufwene (2009 , p. 353) defines linguistic indigenization as a “process whereby a language is adapted to the communicative habits and needs of its (new) speakers in a novel ecology.” In the case of the diversification of ASL from LSF in the early nineteenth century, the novel ecology into which LSF was introduced—initially, New England—certainly differed in numerous ways from the ecology within which LSF had developed to that point. In its adaptation to the American linguistic ecology, with its complex array of novel demographic, social, cultural, and linguistic features, LSF likely changed in profound and complex ways.

Linguistic Descent and Its Consequences for Theories of Sign Language Relationships

As we have seen, historical connections among sign languages can be reflected in their contemporary forms; for example, sign languages in the French family share similar vocabulary ( Woodward, 1978 ; Guerra Currie et al., 2002 ), similar structural features ( Abner et al., 2020 ), and similar fingerspelling alphabets ( Power et al., 2020 ). If we accept a historical explanation for many of these similarities, what is the theoretical significance of whether these shared signs and features have been inherited via linguistic descent or via some theoretically nongenetic pathway?

Linguistic descent crucially implicates the native acquisition of language by children. Labov (2007) argues that differences in the ways that children vs. adults acquire language underlie differences between internal language change and change due to contact. Linguistic descent produces gradual changes (“incrementation”) in a language from generation to generation: “the continuity of dialects and languages across time is the result of the ability of children to replicate faithfully the form of the older generation's language, in all of its structural detail” ( Labov, 2007 , p. 346). In contrast, “adults do not learn and reproduce linguistic forms, rules, and constraints with the accuracy and speed that children display” ( Labov, 2007 , p. 349). Thus, if the chain of child language acquisition events is broken, relatively abrupt, chaotic changes may be introduced in the historical development of a language. The diversification of many sign languages has arguably been characterized by abrupt changes of this type. Following diversification, however, the transmission of language in a signing community—for example, of ASL in the American deaf community after the introduction of LSF in the early nineteenth century—could be characterized by linguistic descent.

That the diversification of many sign languages has arguably been characterized by abrupt changes introduces a second set of problems. In traditional historical linguistics, methods for identifying inherited words—that is, cognates—among related languages rely on the type of gradual and regular changes that Labov has argued are characteristic of linguistic descent. If, for example, the diversification of sign languages in the French family has implicated abrupt changes, and not gradual, regular changes, then it may not be possible to use the methods of traditional historical linguistics to identify historically-related signs among languages in a sign language family. Before considering this second set of problems for sign language historical linguistics, I first raise a number of critiques of the theory of genetic language relationships.

Critiques of the Theory of Genetic Language Relationships

To this point, I have attempted to bring into stark relief one aspect of the problem situation confronting sign language historical linguistics. The theoretical dimension of this problem relates to the key roles played by the notions of normal transmission and of linguistic descent in the theory of genetic language relationships. My aim has been to emphasize that these notions should not be uncritically adopted in theorizations of the historical development of sign languages and of their relationships to each other. In this section, I turn the focus onto the theory of genetic language relationships by raising two critiques; see Mufwene (2003 , 2008) and DeGraff (2001) for additional critiques from the field of creole studies.

The first critique arises through a comparison of the theory of genetic language relationships with the putatively parallel theory in evolutionary biology. Although these theories share many similarities, the underlying processes of linguistic and biological evolution nevertheless fundamentally differ ( Atkinson and Gray, 2005 ). Hence it may be misleading to use terminology such as genetic and nongenetic in theories of language relationships. In the theory of genetic language relationships, as we have seen, some pathways of development are considered nongenetic; however, there are no nongenetic pathways of development in evolutionary biology. Every life form has inherited genetic material from at least one antecedent, and hence every species—arguably, the notion that most closely parallels the notion of a language in the current discussion ( Mufwene, 2008 )—has developed via fundamentally genetic pathways. Relatedly, all species are represented on the one evolutionary tree of life; hence all species have genetic relationships ( Maddison et al., 2007 ). Thus, if the theory of genetic language relationships adopts terminology such as genetic from evolutionary biology, why does the theory allow for some languages to lack relationships?

Furthermore, because creoles, mixed languages, and many sign languages are thought to have multiple antecedents, their development, according to the theory of genetic language relationships, has been nongenetic ( Thomason and Kaufman, 1988 ; Ringe et al., 2002 ). That is, linguistic descent implicates asexual reproduction, in a sense; whereas the parallel to sexual reproduction, or perhaps to hybridization, in language formation is considered a nongenetic pathway of development. In contrast to this aspect of the theory of genetic language relationships, both sexual reproduction and hybridization in biology are fundamentally genetic processes. In sum, if intergenerational language transmission and language relationships are theorized in such starkly different ways compared with biological evolution and evolutionary relationships among species, then perhaps terms such as genetic and nongenetic are not appropriate in theories of language relationships.

There is at least one apparent limitation to the theory of genetic language relationships that pertains to this first critique. If some languages have developed along nongenetic pathways, then how does one describe the historical relations of vocabulary and linguistic features that apparently have shared common pathways of historical development? For example, Fischer (1996) has argued that the sign in ASL representing the number three has its origins in nineteenth-century LSF. But, if ASL has not developed from the LSF of the nineteenth century via linguistic descent—or indeed from any other language by that process—how do we describe the historical relation obtaining between the contemporary signs in ASL and LSF for the number three? See Section The identification of cognates for a discussion of this problem as it relates to the term cognate.

In one sense, the theory of genetic language relationships divides languages into two classes: one class of languages has genetic relationships because these languages have developed via linguistic descent; whereas languages in the other class have no genetic relationships due to characteristics of their intergenerational transmission. The traditional methods in historical linguistics for studying language relationships only properly apply to the former group of languages. For instance, scholars applying the Comparative Method presume that the languages being compared are related ( Nichols, 1996 ; Hale, 2015 ). How does one study relationships among languages that have developed, according to the theory, along nongenetic pathways?

The second critique pertains to the notion of normal transmission and the emphasis in that notion on the native acquisition of language by children. Because most deaf children are born into hearing, non-signing families (roughly 90%, Mitchell and Karchmer, 2004 ), these children often experience delays in their exposure to visually-accessible language. Hence the typical situation for language transmission, when considering many signing communities, is not the type of parent-to-child, intergenerational transmission that is assumed to be normal in the notion of normal transmission described above. Costello et al. (2008) note that, in smaller signing communities, such as the community in Basque Country, there may be extremely few deaf signers who could be considered native signers, given the notion of native that is assumed in speech communities. These authors suggest that the number of signers who have acquired their community's language from birth may depend on factors such as the community's marriage patterns and the prevalence of genetic deafness in the community. Because these factors likely vary across language communities, the patterns of typical language transmission in these communities may vary as well.

Cheng et al. (2021) suggest that the terms “native speaker” and “native signer” have sometimes been used by scholars in ways that conflate differing aspects of language acquisition, proficiency, and identity. In light of differences in the demographics of many signing vs. speech communities and, relatedly, in light of differences in the typical pathways of language transmission in these communities, the authors recommend that scholars carefully disentangle the various assumptions that constitute the category of native speaker or native signer. Arguably, a more nuanced theorization of linguistic experience and language transmission would allow historical linguists to more fully capture the natural complexity in how languages change and in how they are related to one another. In sum, we might expect of a theory of language relationships that it engages with the complex patterns of intergenerational language transmission and of language diversification that actually occur in the world.

The Identification of Cognates

At the beginning of Section Relationships among spoken languages and among signed languages, I contrasted the inheritance of * laidijan “lead” from Proto-West-Germanic in contemporary English, Dutch, and German with the borrowing of honcho from Japanese by American English speakers. Because English lead , Dutch leiden , and German leiten have been inherited via linguistic descent from Proto-West-Germanic, the contemporary words are said to be cognates. Trask (2000 , p. 62) defines the term cognate as “one of two or more words or morphemes which are directly descended from a single ancestral form in the single common ancestor of the languages in which the words or morphemes are found, with no borrowing.” Because cognates are inherited via linguistic descent, by comparing them across related languages linguists may discover information about the internal structure of a language family—that is, the sequence of language diversification events in that language family. In contrast, borrowings do not provide the same type of historical information—certainly, not at the point of the borrowing event—because they were not inherited via linguistic descent as constituents of a common ancestral language.

In traditional historical linguistics, the Comparative Method has been the principal methodology used to identify cognates among related languages. Even in more recent quantitative approaches in historical linguistics, the data have typically comprised cognates that had been previously identified using the Comparative Method (e.g., Gray and Atkinson, 2003 ; Kolipakam et al., 2018 ). The Comparative Method depends on the assumption that sound change can be regular ( Rankin, 2003 ; Hale, 2015 ). The methodology seeks to identify regular sound correspondences across semantically similar words; see Campbell (2013) for a comprehensive discussion of the methodology. In the example above, the correspondence in the second consonants across English (-d), Dutch (-d-), and German (-t-) regularly recurs in many other words in those languages (e.g., in English ride , Dutch reijden , and German reiten ). The most parsimonious explanation for this regular correspondence is the genetic hypothesis ( Hockett, 1965 )—that is, that the contemporary words have been inherited from a common ancestral language.

We do not yet know if sign change can be regular in the way that sound change in spoken languages has been argued to be ( Labov, 2020 ). None of the diachronic changes identified among sign languages have yet been shown to occur uniformly, given a defined phonetic context ( Power et al., 2019 ); nor have regularly recurring correspondences of the type described above been identified across sign languages that are thought to be related. In the previous section, I highlighted a potential explanation for this apparent lack of regular correspondences: namely, the diversification of many sign languages in sign language families may not have been characterized by linguistic descent. Hence we would not expect to find regular correspondences across these sign languages because regular correspondences result from the type of gradual change that is characteristic of linguistic descent.

If sign change cannot be regular, or if the historical development of many sign languages has not resulted in regular correspondences across languages that are thought to be related, then it is not possible to use the Comparative Method to identify cognate signs. Because the Comparative Method in traditional historical linguistics is so tightly intertwined with the identification of cognates through regular correspondences, it is unclear how cognates ought to be identified among sign languages that do not exhibit such correspondences—or, indeed, whether signs that are apparently historically-related, given some alternative method to identify such signs, should be considered cognates.

One further feature of all known sign languages that complicates the identification of cognates is the apparently greater prevalence of iconic and indexical representations in the lexicons of signed vs. spoken languages ( Perniss et al., 2010 ). As a matter of course, historical linguists of spoken languages avoid iconic, or onomatopoetic, vocabulary in their historical comparisons because phonological similarities, and even apparent correspondences, among such vocabulary may not reflect shared history ( Campbell, 2013 ; but see Joseph, 1987 ). The avoidance of iconic vocabulary in historical comparisons of spoken languages developed from the work of early theorists, such as Meillet (1925/1967 , p. 14), who stressed that our ability to make historical inferences based on language depends on the conventional, but not “natural,” connection between form and meaning: “If the meaning to be expressed by language were linked by a natural connection, loose or strict, to the sounds which indicate it, that is, if by its own value, apart from tradition, the linguistic sign evoked an idea in any way… all linguistic history would be impossible.” As we have seen, however, sign scholars such as Woodward have developed methods that apparently identify historical signal in comparisons of sign language vocabulary—despite the high prevalence of iconic representations. Nevertheless, in agreement with Meillet, the historical signal that the methods of sign language historical linguistics apparently identify is, in a sense, fuzzy. That is, when comparing a set of putatively cognate signs across sign languages, no currently-available methodology rigorously differentiates signs that are similar due to iconicity from those that have been inherited from a common ancestral language.

In the next section, I describe how, absent regular correspondences, sign scholars have adapted their theories and methods to confront the problem of identifying historically-related signs.

Theoretical Adaptation of the Cognate

The inability to identify regular correspondences using the Comparative Method has, in my view, significantly shaped the field of sign language historical linguistics. Sign scholars have developed alternative theories and inferential frameworks for understanding the historical relations of sign vocabulary and, relatedly, the historical relationships of the languages themselves. These alternative approaches fundamentally differ from the Comparative Method because they do not rigorously identify vocabulary that has been inherited from a common ancestor or differentiate that vocabulary from borrowings. Here I briefly highlight two approaches in which the notion of cognacy has been expanded to encompass both inherited vocabulary and borrowings. In the next section, I describe two classes of methods that sign scholars have developed as alternatives to the Comparative Method.

The first approach was developed by James Woodward, who has argued for an adaptation of lexicostatistical methods that allows sign scholars to classify sign languages into families without identifying specifically inherited vocabulary.

“A particular advantage to lexicostatistics that is not shared by the comparative method is that lexicostatistics does not assume that languages in the same language family necessarily came from one common ancestor—merely that something has influenced these languages so that they have become similar to each other. This something could be a common ancestor, or it could be extensive borrowing, hybridization, and/or creolization” ( Woodward, 2011 , p. 41).

In Woodward's approach, the sign language family differs from the spoken language family because it is based on influence rather than inheritance. Influence is conceived as a broad category encompassing both inherited and borrowed features. In addition, lexicostatistics is seen by Woodward to be tightly intertwined with the aims of sign language historical linguistics in general, taking the place of the Comparative Method in traditional historical linguistics.

A second alternative approach is found in Supalla and Clark's (2015) notion of “sign language archaeology” (see also Shaw and Delaporte, 2014 ). Their archaeological, or perhaps philological, approach deals mainly with historical texts, videos, and descriptions of sign meanings and their origins. As with Woodward's approach, these authors take an expansive view of cognacy: “[t]o determine a cognate relationship, researchers make an informed decision with the help of either folk etymology or additional scientific excavation for evidence of historical relatedness between the current LSF form and the modern ASL form” ( Supalla and Clark 2015 , p. 90). The archaeological approach to identifying cognates does not seek to differentiate vocabulary in ASL that has been inherited via linguistic descent from vocabulary that has entered the language via other processes.

Supalla and Clark (2015 , p. 190) also point out that folk etymologies about the origins of signs—and hence their potential cognacy relations to other signs—“arise when there is a gap in knowledge about the true history of a word”; typically, these etymologies “are not substantiated by history or fact.” Over time, according to these authors, folk etymologies may come to constitute shared cultural knowledge that is “transmitted across generations as part of sign language culture.” Thus, folk etymologies may simultaneously represent important cultural knowledge that nevertheless may not provide an accurate description of the historical development of a sign.

In Section Early progress in sign language historical linguistics, I highlighted several of the important contributions that sign scholars, including the scholars discussed above, have made to our understanding of the histories of many sign languages and of language change in the gestural-visual modality. Many of these contributions have been due to these scholars' innovative approaches in the face of the theoretical and methodological problems that I have described here. However, these innovations have also created new issues. The theoretical adaptation of the term cognate has avoided the methodological problem raised above because, in this adapted view of the cognate, inherited signs are not differentiated from borrowings. However, while sign scholars have often used the term cognate to describe historically-related signs (but see Guerra Currie et al., 2002 ), it is important to recognize that this notion in sign language historical linguistics differs from the notion of the cognate in traditional historical linguistics. Consequently, sign language relationships that are based on this expanded notion of the cognate theoretically differ from relationships among spoken languages, which are strictly based on inheritance.

Methodological Adaptations for Identifying Historically-Related Signs

Sign scholars have developed two main approaches for making inferences about the historical relations of signs. In contrast to the aims of the Comparative Method, these approaches have been concerned with identifying historically-related vocabulary—potentially including both inherited and borrowed signs. The first approach adjusts the parameters of the Comparative Method such that correspondences are not required to regularly recur; this approach also incorporates an implicit model of how signs may historically change. The second approach uses measures of phonetic similarity to make inferences about the historical relations of signs; this approach does not include a model of historical change. The strength of the first approach is that it incorporates a theory of diachronic sign change in the historical inference procedure. The second approach includes a clearer inferential procedure, which, to some extent, mitigates the potential for systematic bias present in the first approach.

Woodward's Approach to Identifying Cognates Without Regular Correspondences

In perhaps the earliest work applying methods from historical linguistics to study the histories of sign languages, Woodward (1978) adapted lexicostatistical and glottochronological methods in a lexical comparison of ASL and LSF. He used Swadesh's 200-word list of basic vocabulary as the basis for comparing the two languages; he also used Gudschinsky's (1956) methodology for making cognate inferences.

The appeal of Gudschinsky's methodology may have come from its use of the notion of probable cognacy , which in effect loosened the requirement of the Comparative Method that correspondences regularly recur. For example, her “criterion c” allows sounds that differ across potential cognates to be analyzed as “agreeing” (i.e., corresponding) if the sounds' environments might plausibly have conditioned their difference—even if, crucially, the correspondence does not regularly recur in other words ( Gudschinsky, 1956 , p. 184). The methodology is less rigorous compared to a procedure that requires correspondences to regularly recur in other vocabulary, given the same conditions. Like Starostin's (2013) “preliminary lexicostatistics,” Gudschinsky's methodology could function as an initial heuristic by which potentially informative correspondences can be identified in comparative data. However, as a stand-alone procedure for inferring cognates, the methodology opens the door to a multitude of ad hoc explanations about conditioning environments; that is, it is not possible to independently test a hypothesis about a conditioning environment if it is relevant for only one set of sounds.

In adapting Gudschinsky's methodology to the historical study of sign languages, Woodward retained the notion of probable cognacy and its omission of the requirement for correspondences to regularly recur.

“Linguists working on lexicostatistics of sign languages should classify two forms as cognates using the same standards employed by linguists working on spoken languages, that is, only if the application of plausible rules can derive form A from form B, form B from form A, or both form A and form B from some other form that once existed or continues to exist in related languages. Such phonological rules can be rules of assimilation, dissimilation, deletion, epenthesis, coalescence, metathesis, maximal differentiation, centralization, and/or some other phonological process in sign languages recognized by modern linguistics” ( Woodward, 2011 , p. 41).

In traditional historical linguistics, the process outlined in Woodward's first two scenarios above—that is, the derivation of one contemporary sign from another contemporary sign—would be better described as borrowing from a related language because, by definition, cognate forms cannot be derived from sister languages. Rather, cognate forms in sister languages are derived from a form in a common ancestral language via linguistic descent, which is the situation described in Woodward's third scenario above.

If the cognate inference procedure allows for ad hoc accounts of conditioning environments, such as those allowed in Woodward's cognate inference procedure, there may be greater potential for the introduction of systematic bias—particularly when comparing sign languages that we believe to be related on extra-linguistic grounds. For example, because we know that Laurent Clerc was a signer of LSF, we may be more likely to formulate ad hoc explanations for differences across contemporary signs in ASL and LSF.

Despite the issue outlined above, one advantage to Woodward's approach is that it incorporates a model of historical sign change in the cognate inference procedure. As our understanding of language change among sign languages improves, our model of historical sign change could allow us to more accurately reconstruct the potential pathways along which signs may have historically developed.

Inferences Based on Measures of Phonetic Similarity

The second main approach to making inferences about the historical relations of signs bases these inferences on measures of phonetic similarity. In a lexical comparison of American, Australian, British, and New Zealand Sign Languages, McKee and Kennedy (2000) introduced an algorithmic methodology for inferring cognates. In their approach, the sign parameters of handshape, movement, location, and orientation were pairwise compared, with three mutually exclusive possible results: “identical,” in which all four parameters match; “related,” in which at least one of the parameters matches and at least one differs; and “different,” in which all of the parameters differ. Sign pairs in the identical and related categories were inferred to be cognates. Inferences about the historical relationships among the four languages in the study were based on the distribution of sign pairs across the three categories—identical, related, and different.

Because of its algorithmic nature, McKee and Kennedy's (2000) procedure for inferring cognates might potentially be viewed as more objective than Woodward's. Their approach also excludes one possibility for the introduction of systematic bias in historical comparisons of sign languages because their algorithm does not allow for ad hoc accounts of conditioning environments when parameter values differ (see the discussion of Woodward's approach in the previous section). However, McKee and Kennedy's approach places strict constraints on language change that may not have strong empirical or theoretical grounding. All four parameter values in a sign can change, including handshape ( Battison et al., 1975 ), number of hands and movement ( Frishberg, 1975 ), orientation ( Wilcox and Wilcox, 1995 ), and location ( Lucas et al., 2001 ; Schembri et al., 2009 ). But, for sign pairs to be inferred as cognates in McKee and Kennedy's approach, signs must have only minimally changed over time or they must have changed in exactly the same ways because all parameter values in a pairwise comparison must match for signs to be considered “identical,” and at least one parameter value must match for signs to be categorized as “related.”

As with Woodward's approach, McKee and Kennedy's methodology does not attempt to differentiate inherited vocabulary from borrowed vocabulary. Instead, it solely bases historical inferences on measures of phonetic similarity. That similarity could be due to inheritance, if two sign languages have inherited similar forms from a common ancestral language and those forms have not yet substantially changed. However, that similarity could also be due to borrowing or chance similarity. The inability of this methodology to differentiate vocabulary based on the differing processes by which that vocabulary has entered a language is a weakness that is inherent in any approach that bases historical inferences on phonetic similarity.

Recent Approaches to Historical Inferences

Relatively few sign language historical linguists in the twenty-first century have taken qualitative approaches in their historical comparisons. Supalla and Clark (2015 ; see Section Theoretical adaptation of the cognate) and Shaw and Delaporte's (2014) studies of the histories of signs in ASL are two notable exceptions to this observation. Many more historical comparative studies of sign languages have taken quantitative approaches, following Woodward and McKee and Kennedy (e.g., Parkhurst and Parkhurst, 2003 ; Sasaki, 2007 ). In sign language historical linguistics, this focus on quantitative approaches may ultimately stem from discussions within the field about the appropriateness of lexicostatistics for studying the histories of sign languages ( Woodward, 2011 ). However, in historical linguistics more broadly there also has been a surge in the use of quantitative approaches over the past two decades. In that time, historical linguists have come to recognize how computational phylogenetic approaches and methods that developed in the fields of biology and systematics may help them to investigate questions about the historical evolution of languages and language families ( Gray and Atkinson, 2003 ; Atkinson and Gray, 2005 ; Bouckaert et al., 2012 ; Kolipakam et al., 2018 ). Here I briefly highlight three recent studies that have used quantitative and computational phylogenetic approaches to compare signs and other linguistic features.

In a recent large-scale comparison of 23 sign languages, Yu et al. (2018) annotated signs based on Brentari's (1998) model of the sign and then computationally pairwise compared these annotations. Their comparison produced a distance matrix, which was used as the input for a hierarchical cluster analysis. Many of the clusters produced by their approach were expected based on our understanding of the extra-linguistic history of connections among signing communities. For example, LSF and L í ngua Brasileira de Sinais are closely grouped, as are svenskt teckenspråk and L í ngua gestual portuguesa . However, other clusters were unexpected: ASL was more closely grouped with Polski Język Migowy, Eesti viipekeel, and Latviešu zı̄mju valoda (Polish, Estonian, and Latvian Sign Languages) than with LSF; and Türk i°şaret Dili (Turkish Sign Language) was closely grouped with Íslenskt táknmál and Lingua dei Segni Italiana (Icelandic and Italian Sign Languages). Despite these unexpected results, Yu et al.'s study represented an innovative approach to studying the histories of sign languages; it is also one of the few available large-scale comparisons of sign languages. In a follow-up study, Abner et al. (2020) used a similar computational approach to study the distribution of phonological features across the languages in their sample and to make inferences about the historical development of sign language families based on the distribution of those features.

Power et al. (2020) designed a database of 76 manual alphabets, including those of contemporary sign languages and of historical manual alphabets dating to the sixteenth century. They compared handshapes in these manual alphabets by making qualitative judgements about the similarity of their forms. The manual alphabets were then pairwise compared and a series of computational phylogenetic network methods were applied to understand the complex patterns of similarity among these manual alphabets. Because the sample of manual alphabets included 36 historical examples, the authors were able to compare subsets of manual alphabets at various historical periods and to make inferences about their evolution over time. By assuming that the historical connections among manual alphabets paralleled historical connections among sign languages more broadly, the authors used their results to understand the world-wide dispersal of European sign languages.

In sum, recent work in sign language historical linguistics has followed broader trends in historical linguistics by applying computational and phylogenetic methods. Whereas previous quantitative comparisons mainly focused on sign vocabulary, the recent approaches highlighted here have studied other aspects of sign languages—such as their phonological features and manual alphabets—to better understand the histories of these languages. Thus, these recent approaches can also be viewed as alternative approaches to the Comparative Method. Like the previous approaches discussed in the preceding two sections, more recent approaches do not rigorously differentiate between inherited and borrowed signs or linguistic features.

Etymological Relations

I have argued that one of the main problems that has shaped the theories and methods of sign language historical linguistics has been the inability to identify regular correspondences among apparently cognate signs. In this section, I briefly recapitulate that argument before discussing the notion of the etymological relation.

As I discussed in Section Relationships among spoken languages and among signed languages, the process of linguistic descent—that is, the native acquisition of language by children over multiple, successive generations—has been argued to be a driver of the type of incremental change that can result in regular correspondences ( Labov, 2007 ). Because many sign languages that are thought to be related have not diversified via linguistic descent, we might not expect to find regular correspondences among the apparently cognate signs of these languages. If we cannot identify regular correspondences, we cannot use the Comparative Method to identify cognates or to rigorously differentiate inherited vocabulary from vocabulary that has entered a language due to other processes, such as borrowing. Given this problem situation, the term cognate is not, in my view, an appropriate characterization of the historical relations of many signs—perhaps even of similar signs in the languages of many sign language families. What is an appropriate characterization of the historical relations of these signs?

In his comparison of theoretical terminology in historical linguistics and evolutionary biology, List (2016) showed that some of this terminology does not map in similar ways onto abstract historical relations. For example, a fundamental notion in biological evolution is homology (attributed to Owen, 1843 ). According to List (2016 , p. 120), “[h]omology is a very general historical relation between evolving objects. It does not specify the process from which the relation originated.” Homology is a superordinate concept describing “a relationship of common descent” ( Koonin, 2005 , p. 311), with three subtypes “based on the processes underlying the homology”—namely processes of speciation, gene duplication, and horizontal transmission ( List, 2016 , p. 120).

Homology is distinct from similarities arising through analogy—that is, the evolution of functionally-similar traits that have no specifically historical relation. One example of a process giving rise to analogy was the independent parallel evolution of wings in bats and birds, which did not arise from common historical pathways of descent; rather, wings independently evolved in birds and bats for functional reasons ( Morrison et al., 2015 ). There are clear parallels in traditional historical linguistics to the distinction between homology and analogy. Greenberg's (1957) four causes of similarity differentiate between two causes that are thought to be historical—namely inheritance and borrowing—and two others that are considered nonhistorical—chance and sound symbolism. According to List (2016) , however, there is no broadly accepted theoretical notion in historical linguistics that corresponds to the notion of homology. Theories in historical linguistics are certainly concerned with processes of language diversification via linguistic descent; they are also concerned with borrowing. But, historical linguists do not commonly make reference to an overarching term to describe both inherited and borrowed features.

In parallel to the concept of homology, List (2016) proposed the term etymological relation to encompass the historical relations of cognacy and borrowing (see also “sign language etymology,” Supalla and Clark, 2015 ). List's invocation of etymology seems appropriate as a parallel to homology because the concept has a long history in linguistics with precisely this meaning. Mailhammer (2015 , p. 424) defined an etymology as “a historical account of the origin and the subsequent historical development of a linguistic item.” He distinguished between “internal” and “external,” or “contact,” etymologies. An internal etymology is one that describes the history of an inherited linguistic feature, whereas a contact etymology implicates borrowing events, or horizontal transmission. Mailhammer (2015 , p. 432–433) pointed out that “the etymology of a linguistic item can comprise one or more cases of horizontal transmission” and that “a contact etymology necessarily combines internal and external etymologies, vertical and horizontal transmission.” Thus, in parallel to homologous biological traits, the linguist may speak of etymologically-related words, the histories of which connect at a shared common etymon.

List's notion of the etymological relation accurately captures the type of historical relation that the less precise notion of influence is intended to invoke in the theory of sign language relationships described in Section Theoretical adaptation of the cognate. Characterizing the historical relations of many signs as etymological directly acknowledges the methodological problems facing sign language historical linguistics—in particular the current inability to identify cognates using the Comparative Method. In contrast to previous theories about sign language relationships, the notion of etymology maintains important theoretical distinctions between vertical and horizontal pathways of descent in the histories of signs and linguistic features. A contact etymology, per Mailhammer, is flexible enough to incorporate instances of both vertical and horizontal transmission in the history of a sign, without committing historical linguists of sign languages to any conclusions about the genetic language relationships of the sign languages being compared.

The two subfields of historical linguistics—namely, those focusing on spoken and signed languages—have rarely engaged one another, despite the relevance of both subfields to an overarching theory of language change. Why have they so rarely engaged with each other? As we have seen, the field of sign language historical linguistics since the 1970s has adopted many of the theories and methods that developed in traditional historical linguistics, including notions such as the language family and cognacy, as well as methods such as lexicostatistics. More recently, too, sign scholars have applied computational and phylogenetic methods in their historical comparisons of sign languages, thereby following broader trends in the approaches used in historical linguistics. Thus, in one sense, sign language historical linguists have indeed engaged with the theories and methods of spoken language historical linguistics.

However, I have argued that theoretical notions like the genetic language relationship, the language family based on genetic relationships, and cognacy do not straightforwardly map onto the processes of historical development that have characterized the diversification of many sign languages. In addition, the innovative methods that sign language historical linguists have developed as alternatives to the Comparative Method have both fostered progress in our understanding of the histories of sign languages and, perhaps, hindered cross-disciplinary engagement because these methods fundamentally differ from those used in traditional historical linguistics. Greater clarity about the strengths and weaknesses of our methods as well as their aims may foster greater collaboration in the future.

Much progress has been made in sign language historical linguistics since Stokoe, but, as I have argued here, fundamental theoretical and methodological problems remain. In my view, one of the main thrusts in future research in this area should be a concerted effort to identify regular correspondences among apparently related sign languages and across historical stages of the same sign language. To date, there have been few systematic attempts to do so ( Power et al., 2019 , 2021 ). Relatedly, there have been few systematic studies of diachronic change between different stages in the historical development of sign languages. For example, more than 40 years have passed since Frishberg's (1975) groundbreaking study of diachronic change in ASL, and few scholars have attempted to refine or to add to Frishberg's insights (see Shaw and Delaporte, 2014 ; Supalla and Clark, 2015 ). Another promising area for future research is the use of simulation studies to model the effects of differing processes of language transmission on language change ( Gong et al., 2010 ; Gong and Shuai, 2016 ; Mudd et al., 2020 ) and to understand how iconicity may shape language change ( Greenhill et al., 2009 ; Currie et al., 2010 ).

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Support has come from the National Science Foundation grant BCS-1941560 Regularity and Genetic Relatedness in Sign Languages.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

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Acknowledgments

This article has benefited greatly from many stimulating conversations with David Quinto-Pozos, Danny Law, and Richard P. Meier. Any errors are the author's alone.

1. ^ Guerra Currie et al. (2002 , p. 225) hypothesized that cultural ties between Spanish-speaking Mexico and Spain might “manifest themselves” in linguistic similarities among LSM and Lengua de Signos Española .

2. ^ Labov (2007) uses the term “transmission” in a restricted sense to mean the intergenerational transmission of language and its acquisition by children; see Section Linguistic descent and its consequences for theories of sign language relationships. Here I use the term in its more general sense.

3. ^ With hindsight, the modifier “normal” may have been ill-considered; see Thomason (2002 , p. 102), who admits that the opposite notion of abnormality of transmission is “arguably pejorative.” More to the point, to my knowledge, there have been no careful empirical studies on the basis of which historical linguists might determine which are the normal, or perhaps the most common, pathways of transmission within the world's language communities.

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Keywords: historical linguistics, language change, sign language, language relationships, language families

Citation: Power JM (2022) Historical Linguistics of Sign Languages: Progress and Problems. Front. Psychol. 13:818753. doi: 10.3389/fpsyg.2022.818753

Received: 19 November 2021; Accepted: 27 January 2022; Published: 09 March 2022.

Reviewed by:

Copyright © 2022 Power. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Justin M. Power, justin.power@utexas.edu

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Sign Language Research, Uses and Practices

Crossing views on theoretical and applied sign language linguistics.

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The Cognitive Neuroscience of Sign Language: Engaging Undergraduate Students’ Critical Thinking Skills Using the Primary Literature

This article presents a modular activity on the neurobiology of sign language that engages undergraduate students in reading and analyzing the primary functional magnetic resonance imaging (fMRI) literature. Drawing on a seed empirical article and subsequently published critique and rebuttal, students are introduced to a scientific debate concerning the functional significance of right-hemisphere recruitment observed in some fMRI studies of sign language processing. The activity requires minimal background knowledge and is not designed to provide students with a specific conclusion regarding the debate. Instead, the activity and set of articles allow students to consider key issues in experimental design and analysis of the primary literature, including critical thinking regarding the cognitive subtractions used in blocked-design fMRI studies, as well as possible confounds in comparing results across different experimental tasks. By presenting articles representing different perspectives, each cogently argued by leading scientists, the readings and activity also model the type of debate and dialogue critical to science, but often invisible to undergraduate science students. Student self-report data indicate that undergraduates find the readings interesting and that the activity enhances their ability to read and interpret primary fMRI articles, including evaluating research design and considering alternate explanations of study results. As a stand-alone activity completed primarily in one 60-minute class block, the activity can be easily incorporated into existing courses, providing students with an introduction both to the analysis of empirical fMRI articles and to the role of debate and critique in the field of neuroscience.

Undergraduate science courses often face a tension between the coverage of scientific content versus scientific process skills ( American Association for the Advancement of Science, 2009 ; Coil et al., 2010 ; Osborne, 2010 ). Whereas content learning relates primarily to the key findings, theories, and models in a scientific discipline, process skills encompass the range of skills needed to do science, including but not limited to interpreting data, designing experiments, and engaging in evidence-based argumentation and critique ( Coil et al., 2010 ; Osborne, 2010 ; Association of American Medical Colleges, 2012 ). Although content and skill learning are invariably intertwined, there is a recognized need to incorporate stronger training of process skills into science education ( American Association for the Advancement of Science, 2009 ; Coil et al., 2010 ; Osborne, 2010 ).

One way to develop students’ scientific process skills is to incorporate focused activities and discussion based on empirical, primary articles (e.g., Muench, 2000 ; Hoskins et al., 2007 ; Hoskins, 2008 ; Hoskins et al., 2011 ; Willard and Brasier, 2014 ). For students, engaging the primary literature can be markedly different from reading sets of “facts” in a textbook. Reading in the primary literature typically requires a number of process skills, such as interpreting data and graphs, critiquing experimental design, and proposing alternative interpretations or future studies. Reading the primary literature can be particularly beneficial when it allows students to engage a controversy or paradigm shift in the field, modeling the thought process and dialogue inherent to science (e.g., Hoskins, 2008 ). Indeed, a recent survey indicated that, among undergraduate neuroscience faculty, the most important core competency for undergraduate neuroscience programs is critical and integrative thinking (ahead of basic neuroscience knowledge), with the ability to read and analyze a primary research paper the most essential element of critical and integrative thinking ( Kerchner et al., 2012 ).

An emerging literature provides general suggestions for faculty members wishing to incorporate the primary literature into undergraduate science courses (e.g., Janick-Buckner, 1997 ; Muench, 2000 ; Hoskins et al., 2007 ; Hoskins, 2008 ; Hoskins et al., 2011 ). Articles, for example, should be carefully selected so they are appropriate not only to course content, but also to students’ existing content knowledge, which may be limited. In some cases, sets of articles can be selected that either represent a series of sequential experiments from within the same laboratory group, or different perspectives on a scientific controversy. Scaffolding is also suggested, where focused activities or questions allow students to practice specific scientific process skills such as interpreting the data, graphs, and figures from a research paper or proposing possible follow-up experiments. Similarly, specific questions or activities can be included that require students to demonstrate an understanding of the experimental methods and how different patterns of results would relate to specific hypotheses.

In addition to these general suggestions, more specific guidance has been provided for a small subset of neuroscience-related courses. For example, sets of readings or specific course structures have been identified for advanced courses in cellular biology ( Janick-Buckner, 1997 ) and developmental neurobiology ( Hoskins et al., 2007 ; Hoskins, 2008 ; Hoskins et al., 2011 ; note these activities have also been used in general biology courses). Another recent paper has described how primary readings regarding two key controversies were used in a freshmen seminar introducing students to neuroscience ( Willard and Brasier, 2014 ). These examples provide a valuable resource for faculty teaching similar courses and wishing to incorporate the primary literature, as article selection and/or scaffolding activities are included as part of the documentation. However, similar resources are not available for the range of courses in the neuroscience curriculum, leaving the challenge of article selection and scaffolding activities to individual instructors. As well, many of the specific examples published to date involve complete redesign of courses to focus exclusively on reading in the primary literature (e.g., Janick-Buckner, 1997 ; Willard and Brasier, 2014 ). As such, there remain few concrete examples of modular activities using the primary literature that can be incorporated into existing neuroscience courses. However, modular activities may be particularly valuable to faculty, who report that some of the largest challenges to teaching scientific process skills are the time-consuming nature of teaching those skills and the need for students to have adequate content knowledge to make engaging in process skills possible ( Coil et al., 2010 ).

The goal of the present paper is to describe a stand-alone, primary literature-based activity that can be easily incorporated into existing cognitive neuroscience courses. The activity focuses on the neurobiology of sign language processing. This topic is less commonly covered in cognitive neuroscience textbooks (e.g., see Gazzaniga et al., 2009 ; Ward, 2010 ) but provides a natural complement to typical course units on spoken language processing. Traditional coverage of the neurobiology of spoken language often emphasizes the prominent role of the left-hemisphere in language processing, as well as distinctions among subsystems within language, such as production versus comprehension or syntax versus semantics. However, within the literature on sign language processing, one area of debate concerns the extent and functional significance of right-hemisphere recruitment observed in some fMRI studies of sign language processing. Importantly, there is not an agreed upon answer to this question (e.g., for different perspectives and data on this issue, see Newman et al., 2002 ; MacSweeney et al., 2002 ; Emmorey et al., 2005 ; Capek et al., 2009 ; MacSweeney et al., 2009 ; Malaia and Wilbur, 2010 ). Thus, the activity described below is not designed to provide students with a specific conclusion regarding the debate. Instead, the set of articles provide a rich opportunity for students to consider key issues in experimental design and interpretation of the primary literature using functional magnetic resonance imaging (fMRI), one of the neuroimaging methods commonly encountered in the primary literature in cognitive neuroscience.

Specifically, the readings and activity described here engage students in critical thinking regarding the cognitive subtractions used in blocked-design fMRI studies, as well as possible confounds in comparing results across different experimental tasks. As such, instructors implementing the activity should be familiar with fMRI methodology, including boxcar diagrams and the logic of cognitive subtractions, particularly with regard to the selection of baseline tasks and the challenges of isolating a cognitive process of interest. The readings and activity also allow students to consider general experimental design issues related to heterogeneity of participant characteristics, and the need for multiple experiments to rule out alternative explanations. By presenting articles representing different perspectives, each cogently argued by leading scientists and published in peer-reviewed venues, the readings and activity also model the type of debate and dialogue critical to science, but often invisible to undergraduate science students.

MATERIALS AND METHODS

The activity uses a set of three articles: a seed empirical primary research study ( Neville et al., 1998 ), followed by a subsequent critique of the study ( Hickok et al., 1998 ) and rebuttal from the original authors ( Corina et al., 1998 ). This set of articles thus allows students to engage in a debate in the field, including critical analysis and discussion of study design and proposal of possible follow-up studies. The articles also explicitly expose students to the conflict and controversy inherent to scientific findings. Below, an overview of each article is provided, before describing the classroom activity.

The first article, “Cerebral organization for language in deaf and hearing subjects: Biological constraints and effects of experience” ( Neville et al., 1998 ), is a brief, eight-page empirical fMRI study that examines whether processing of sign language by native, fluent signers recruits a similar, left-lateralized network of brain areas typically associated with spoken language processing. The study includes two separate fMRI tasks designed to isolate English and ASL processing, respectively. The English language task includes alternating blocks of trials in which participants view either declarative sentences presented one word at a time or consonant strings presented one string at a time. The subtraction of neural activity elicited during the consonant strings condition from the declarative sentences condition is used to isolate processing associated with English. The ASL task includes alternating blocks of trials in which participants view a video of a signer producing either sentences in ASL or non-sign gestures that are physically similar to ASL signs. The subtraction of neural activity elicited during the non-sign gesture condition from the ASL sentences condition is used to isolate processing associated with ASL. Critical to both the English and ASL subtractions is the assumption that, to the extent that an individual is naïve either to written English or to ASL, the subtraction should yield no distinct neural activity, as the subtractions are designed to remove activity associated with general visual processing, etc common to both conditions. However, any unique activity that remains following subtraction will isolate processing specific to the linguistic nature of either the English or ASL stimuli.

The seed article includes three different participant groups: (1) hearing, monolingual native English speakers unfamiliar with a sign language, (2) congenitally deaf native signers of ASL, who also learned English late, and (3) hearing, bilingual native English speakers, born to deaf parents, who also learned ASL as a native language. All three groups complete both the English and ASL fMRI task. The primary finding indicates that a similar set of left-hemisphere regions associated with language processing (e.g., Broca’s and Wernicke’s area, and other left-hemisphere regions) are recruited both when native English speakers process English or when native signers process ASL, suggesting that these regions are “amodal” for language, and recruited even for visual-gestural signed language. However, a second key finding indicates that native signers, whether deaf or hearing, additionally recruit an extensive network of right hemisphere regions during sign language processing. The authors interpret this second finding to indicate that sign language has unique characteristics that place functional demands on the right hemisphere, possibly attributable to the use of spatial syntax in sign language (i.e., the placement of signs in visual space to communicate syntactic relations).

The second article, “What’s right about the neural organization of sign language? A perspective on recent neuroimaging results” ( Hickok et al., 1998 ), is a four-page critique of the seed article. The critique takes issue with the unique right hemisphere recruitment observed during ASL processing. Specifically, the critique raises concerns about the subtraction used to isolate English language processing. The authors argue that English processing should not be isolated using visually presented words, but rather with audio-visual talking heads. The authors argue that the use of printed English presents a critical confound in the comparison of “ASL” and “English,” with any unique activity in response to ASL possibly attributable to ‘extra-grammatical’ information, such as prosody, facial expressions, and nonlinguistic visual features which are also present in audio-visual spoken language but absent in printed English. The authors argue that a more appropriate method of isolating English language processing would be to use audio-visual talking heads, which would be more similar to real-life language processing and likely to engage right-hemisphere regions. To further support their argument that the right hemisphere is not functionally significant to sign language processing, the authors present data showing that left-hemisphere lesions in signers are more likely to lead to sign language aphasia than right hemisphere lesions. The authors argue that the lesion data further support their contention that the right hemisphere activity reported in the original article may not be critical for sign language processing per se, but rather an artifact of processing extra-linguistic features available in the signing stimuli, but absent from printed English. The article thus claims that the similarities in left-hemisphere recruitment is the most interesting finding in the paper, and that there is not compelling evidence that the right-hemisphere recruitment for ASL is unique to signed languages or critical for ASL processing.

The third and final article, “Response from Corina, Neville, and Bavelier” ( Corina et al., 1998 ), written by the authors of the seed article, provides a rebuttal to the criticisms raised. The rebuttal acknowledges that spoken language processing may indeed recruit right-hemisphere regions more than printed English processing, but the authors argue that the right hemisphere recruitment for spoken English is never as spatially extensive or statistically robust as apparent with ASL. The rebuttal also defends the use of written English in the study, arguing that it was not a control condition per se, but rather provided a within-modality comparison between English and ASL. Had the authors used audio-visual talking heads, there would have been a different set of confounds created by the auditory stimulation present in the English condition but absent in the ASL condition. The authors further argue that activity in the ASL subtraction cannot be explained by facial expressions and non-linguistic gesture, as the non-sign subtraction included similar features and such activity would therefore be removed in the cognitive subtraction. Finally, the authors note that discrepancies between fMRI and lesion studies may reflect the aspects of language assessed in each type of study. The authors argue that tests of language processing used in lesion studies generally emphasize production, and thus may miss important deficits in comprehension, particularly for spatial syntax, whereas the fMRI tasks are based solely on language comprehension. Additionally, lesion studies generally include individuals with different etiologies of deafness and experience with signed languages, including age of acquisition of sign language. Heterogeneity in the participant population included in lesion studies may make it more difficult to identify the neural regions important to signed language when learned natively and fluently.

The main activity required approximately 60 minutes of class time, with an additional 10–15 minutes used in the class period prior to and following the discussion for class preparation and final debrief.

In the class period prior to the discussion, the instructor led a short pre-discussion of sign language. Based on their knowledge of sign language and/or short video clips of ASL played from youtube ( https://www.youtube.com/ ), students identified similarities and differences between signed and spoken language. This pre-discussion was used to introduce the question of whether the neural systems recruited during signed language would be similar to or different from those identified as “classical language areas” (e.g., Broca’s and Wernicke’s area of the left hemisphere). Students were then divided into three groups, with each group assigned to one of the different participant populations studied in the seed article (e.g., hearing monolingual English speakers). Students completed a pre-discussion handout as homework, answering the questions with respect to their group’s assigned participant population. The handout included four questions, focused on ensuring students understood the basic logic, methods, and findings from the study:

• What are the basic characteristics of your participant group (number, age, hearing status, language status, and proficiency)? What was the purpose of including this group in the study?
• Draw a boxcar diagram representing the fMRI experimental design used to isolate (a) “English” and (b) “ASL.” What was participants’ task?
• What brain regions were recruited in this participant group for (a) “English” and (b) “ASL”? [it’s ok just to give the big picture findings – you don’t have to list everything! ]
• What is the relevance or significance of these activations (i.e., what is most important about the pattern of results in the question above with respect to big picture questions about the signing brain)?

Students were also asked to read the critique of the article in preparation for class discussion. (Note: The activity could be modified to divide the discussion across two smaller activities in subsequent class periods, in which case the critique of the article would be discussed in a later class period. This modification would allow students to come up with their own critiques of the seed article before reading the critique by Hickok and colleagues.)

In the next class period, approximately 60 minutes were devoted to the article discussion. Students were divided back into their three groups, with one group for each of the three participant groups represented in the study. Approximately 10 minutes were provided for students to recap the basic methods and fMRI contrasts used and resolve any discrepancies across group member answers. As students discussed the article, the instructor drew a large 2 × 3 grid on the whiteboard, with rows representing Task (“English” vs. “ASL”) and columns representing Participant Group (“Hearing-NonSigner” vs. “Hearing-Signer” vs. “Deaf-Signer”). In each cell, schematic outlines of the left and right hemisphere were drawn. The instructor asked each group to fill in simple focal points of brain activity representing the key areas responding to each subtraction for their respective participant group. This encouraged students to abstract away from the extreme detail of the article to highlight, visually, the key findings of the paper. It also involved extraction and recoding of information from Figure 1 and Figure 2 of the seed article. An example of what a completed grid might look like is provided in Appendix I . As shown in the example final grid, this extraction makes visually clear that robust left-hemisphere recruitment is observed whenever a group processes their native language. In contrast, right hemisphere recruitment is observed during ASL processing in native signers of ASL (whether deaf or hearing) as well as in deaf signers processing written English.

A whole-class discussion followed, in which the class was asked to consider the full pattern of data on the board. Each group briefly presented the main results for their participant group. The class was then asked to identify the key findings from the paper. The instructor ensured that students identified the unique recruitment of right-hemisphere regions for native ASL signers processing ASL, as well as the common recruitment of left-hemisphere regions whenever a group processed their native language (English or ASL). Some students also observed the smaller right-hemisphere activity in the “English” contrast by the deaf native signers. This provided opportunity for brief discussion of the effects of late and imperfect learning of English by deaf signers, who do not have access to a spoken language. If raised, the instructor could include mention of the robust literature showing that deaf signers often have lower English reading ability ( Conrad, 1979 ; Marschark and Harris, 1995 ; Dyer et al., 2003 ), with other literatures showing that increased reading ability is associated with a shift toward increasing left-lateralization during reading ( Turkeltaub et al., 2003 ; Yamada et al., 2011 ). The instructor ended this portion of the discussion by focusing students on the right-hemisphere activity observed during sign language processing which was the key finding that became very controversial in the field, leading to an academic debate with a published critique of the article.

Next, students returned to their small groups to discuss the Hickok et al. critique and generate possible follow-up experiments. Groups were asked to address the following questions:

• What are the primary claims and arguments in the critique? What challenges are raised to the experimental design or findings in the Neville reading?
• Of the criticisms raised, which do you find most compelling and why?
• Based on the critiques – or additional criticisms you might raise – what follow up study would you like to see conducted? What information would you hope to gain from the follow up study?

Following small group discussion, the entire class convened to discuss these issues. Student discussion focused on different possible comparisons to ASL, including the benefits and drawbacks of using printed English (which includes no auditory component, similar to ASL) versus audio-visual talking heads (which includes facial expression and prosody, similar to ASL). Students were encouraged to clearly describe possible follow up experiments. For example, if students proposed an fMRI study using audio-visual talking heads, they also needed to identify a possible baseline condition for the cognitive subtraction. For the next class period, students were asked to read the rebuttal from the original study authors, paying attention to which responses or new pieces of evidence they found most compelling.

The next class period, approximately 15 minutes were devoted to final discussion of the rebuttal and set of articles as a whole. The instructor led the class in a group discussion of the main points raised in the rebuttal. The instructor also revisited some of the experimental designs proposed by students in the previous class period, asking whether any changes might be warranted. The discussion ended with a consideration of production versus comprehension as different components of language processing. Depending upon student interest, the discussion could also include possible modifications to evaluations for language aphasia, and the importance of participant characteristics in studies of sign language processing. This latter issue can also be applied to future studies discussed in class or read in the literature. This encourages students to attend to possible confounds in a study, or reasons for discrepant findings across studies.

The author has used variations of the activity seven times in mid-level psychology courses in Cognitive Neuroscience (the only pre-requisite for the course is Introductory Psychology), as well as in courses on Language and Literacy Acquisition. The activity described can be used completely stand-alone or, at instructor’s discretion, additional related articles could be assigned or presented in future class periods (e.g., Newman et al., 2002 ; MacSweeney et al., 2002 ; Emmorey et al., 2005 ; Capek et al., 2009 ; MacSweeney et al., 2009 ; Malaia and Wilbur, 2010 ). These studies generally provide some, but not all, of the data students hope to see (e.g., comparisons of neural activity to signed language versus audio-visual talking heads, and effects of age of acquisition on neural systems recruited during sign language processing.)

To assess student perceptions of the activity, a section of students who completed the activity as part of a Cognitive Neuroscience course were invited to complete an optional, supplemental evaluation of the activity at the end of the course. The course enrolled 23 students, 74% of whom were in their junior or senior years. The survey was anonymous and included six questions about the activity (see Table 1 ), using a scale ranging from 1 (strongly disagree) to 5 (strongly agree). All but one student (96%) completed the optional survey.

Text of anonymous supplemental evaluation form provided to students, with mean and standard deviation (SD) for each item provided. Responses were given on a scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), with a neutral midpoint of 3.

Table 1 presents the mean and standard deviation for student responses to each survey item, as well as the percent of students who “agreed” or “strongly agreed” with each item. As indicated, student feedback was positive for all items, with means above 4.0 (“agree”) for all questions. 95% of students “agreed” or “strongly agreed” that the set of articles was interesting (M= 4.27, SD=0.54), with a similarly high 91% of students recommending including the readings in future classes (M= 4.32, SD = 0.63). Several questions were used to identify whether students felt the activity as a whole improved their ability read empirical fMRI articles. These items indicated that students felt the assignment helped them to read and understand the methods and results sections of empirical fMRI studies (M = 4.27, SD = 0.62). Students also indicated that the activity helped them to critically evaluate the design of an fMRI study, including consideration of different control conditions included (M= 4.32, SD = 0.70) and to consider alternate explanations of study results (M = 4.45, SD = 0.66). Students reported that after completing the assignment, they felt better prepared to read empirical articles using the fMRI technique (M= 4.32, SD = 0.72).

The activity described here provides a means for faculty teaching courses in cognitive neuroscience to engage students in reading the primary fMRI literature. Students reported finding the set of articles interesting, and that the activity improved their ability to read and understand empirical fMRI studies. The activity specifically improved students’ self-perceptions of their ability to engage in critical analysis including evaluating the experimental design (e.g., considering different possible control conditions) and considering alternate explanations of study results. As a stand-alone activity primarily completed in one 60 minute class block, the activity can be easily incorporated into existing courses, providing students with a guided introduction both to reading empirical fMRI articles and to the role of debate and critique in the field of neuroscience.

The activity addresses a key concept in cognitive neuroscience courses: the design and interpretation of fMRI studies. By highlighting the key role of cognitive subtractions, the assignment specifically engages students in thinking critically about what cognitive processes are isolated in a given subtraction. The activity provides a structured introduction to reading and analyzing fMRI studies, which can be valuable in preparing students to read independently in the cognitive neuroscience literature as part of term papers or other course projects. More generally, the activity can expand coverage in units on the neurobiology of language processing to include discussion of manual-gestural languages, which are often omitted or covered only very briefly in cognitive neuroscience textbooks (e.g., see Gazzaniga et al., 2009 ; Ward, 2010 ).

Three features of the set of articles used in the activity are particularly noteworthy. First, the articles address a topic that requires minimal background knowledge on the part of students. While students may have more extensive background on the neurobiology of language, the only critical background is an appreciation for the dominant role of the left hemisphere for spoken language processing. Even brief discussions of Broca’s and Wernicke’s aphasia can establish the role of the left hemisphere, as well as foreshadow possible distinctions between comprehension and production. Second, the articles themselves are very short and readable. This can be a challenge in cognitive neuroscience, where technical language or fine theoretical distinctions can render the primary literature less accessible to students early in their training. This set of articles addresses a larger-scale question (the contribution of an entire hemisphere to language processing), and all of the authors write clearly and concisely. Finally, the articles present competing views that specifically address experimental design issues and interpretation. In cognitive neuroscience, one challenge for students is the critical analysis of the cognitive subtraction used and identifying what specific cognitive processes the subtraction can isolate. Thus, the articles reflect a consideration of key components identified as important for the selection of empirical readings in science-based courses ( Muench, 2000 ).

This activity can be situated in the larger context of efforts to engage undergraduate science students in reading the primary literature. For example, the activity shares elements of the C.R.E.A.T.E. method pioneered by Sally Hoskins and used in undergraduate developmental neurobiology and introductory biology courses ( Hoskins et al., 2007 ; Hoskins, 2008 ; Hoskins et al., 2011 ). Under the C.R.E.A.T.E. method, students c onsider the concepts and issues from the paper introduction, r ead the article with annotation of figures and transformation of data into different formats (graphs or charts), e lucidate hypotheses (relate each figure to a hypothesis), a nalyze and interpret the data (relying on analysis and annotation of figures and tables from the text), and finally t hink of the next experiment that might be conducted. The present activity, though not formally within the C.R.E.A.T.E. framework, emphasizes analysis and interpretation of data, including linking findings from the figures to different conclusions. The present activity also engages students in thinking about the next experiment, with scaffolding that prepares students for considering the pros and cons of different cognitive subtractions, which is particularly critical to cognitive neuroscience experimental design. Other efforts at engaging undergraduate students in reading the primary literature emphasize introducing students to debates within the field, where students can read different perspectives on a scientific controversy ( Janick-Buckner, 1997 ; Willard and Brasier, 2014 ). Thus, both this activity and others that are focused on the reading of empirical articles emphasize the iterative process of science and role of not only of current experiments, but future experiments, to advance our understanding.

By reading different perspectives on a scientific controversy, the activity also provides students the opportunity to experience argumentation and debate as a key part of the scientific enterprise. The importance of argument and debate in science is widely acknowledged, as is its relative under-emphasis in science courses ( Osborne, 2010 ). Noting the importance of critique and debate in science, a recent review article argued “Critique is not, therefore, some peripheral feature of science, but rather it is core to its practice, and without argument and evaluation, the construction of reliable knowledge would be impossible” ( Osborne, 2010 p. 464). The present activity engages students in considering “how we know” what neural systems are recruited by sign language processing, with implications for conclusions about the similarities and differences between signed and spoken language processing. Rather than presenting students with “facts” about sign language processing, the activity emphasizes analysis of the methodology and the validity of particular contrasts and comparisons. The activity also explicitly models for students how scientists both critique one another and must respond to criticism and questions. Rather than identifying the “correct” answer, students are encouraged to consider the role of future research in helping to adjudicate different possibilities as well as appreciate the nuances of relative contributions of particular brain regions, moving beyond an all-or-nothing binary classification of neural regions as involved or uninvolved in a particular cognitive process. Encouraging this type of skeptical, critical evaluation of neuroscience findings may be particularly important given the evidence that the mere presence of neuroimaging information or figures with brain scans can influence the evaluation of associated scientific reasoning (e.g., see McCabe and Castel, 2008 ; Weisberg et al., 2008 ). Rather than turning off critical thinking when encountering neuroscience evidence or images, students need to be empowered to engage critical thinking and evaluation skills in these contexts.

The activity described here can be imported directly as a stand-alone activity in existing cognitive neuroscience courses. The activity can also be used as a framework for selecting articles to incorporate primary readings into undergraduate neuroscience classes. Indeed, future research should identify other current controversies and relevant, readable empirical articles for inclusion in existing neuroscience courses. A recent textbook for cognitive neuroscience highlights several debates in cognitive neuroscience ( Slotnick, 2012 ) and could be used by instructors wishing to incorporate key controversies in the field as a more central focus in the course (the sign language right-hemisphere debate is not included in this book). Future research should also include direct assessments of student gains using aligned questions to assess not only student self-perceptions, but also student performance following inclusion of the activity. Direct assessments will be important for assessing the degree to which student performance achieves key learning objectives for neuroscience programs, including critical thinking and the ability to read and analyze empirical articles ( Coil et al., 2010 ; Kerchner et al., 2012 ).

By incorporating primary articles and active debate and discussion into science courses, undergraduate students can experience the dialogue of science and develop key science process skills. The activity and set of articles described here provide one means for faculty wishing to incorporate primary readings into cognitive neuroscience courses to do as a modular component of existing courses.

Appendix I. 

Example completed grid described in primary article. The data transformation can be used to reinforce the robust left-hemisphere recruitment observed whenever a group processes their native language. In contrast, right hemisphere recruitment is observed in native signers of ASL (whether deaf or hearing) as well as in deaf signers processing written English. The absence of any activity for ASL in the Hearing-Nonsigner group can further support discussions of cognitive subtractions, with the absence of activity not indicating an absence of brain activity, but rather an absence of differential brain activity between the (unfamiliar) ASL signs and the (equally unfamiliar) non-sign baseline task.

Note: See Appendix I on page A73.

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Sign Language Research Paper

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Until recently, most of the scientific understanding of the human capacity for language has come from the study of spoken languages. It has been assumed that the organizational properties of language are connected inseparably with the sounds of speech, and the fact that language is normally spoken and heard determines the basic principles of grammar, as well as the organization of the brain for language. There is good evidence that structures involved in breathing and chewing have evolved into a versatile and efficient system for the production of sounds in humans. Studies of brain organization indicate that the left cerebral hemisphere is specialized for processing linguistic information in the auditory–vocal mode and that the major language-mediating areas of the brain are connected intimately with the auditory–vocal channel. It has even been argued that hearing and the development of speech are necessary precursors to this cerebral specialization for language. Thus, the link between biology and linguistic behavior has been identified with the particular sensory modality in which language has developed.

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Although the path of human evolution has been in conjunction with the thousands of spoken languages the world over, recent research into signed languages has revealed the existence of primary linguistic systems that have developed naturally independent of spoken languages in a visual–manual mode. American Sign Language (ASL), for example, a sign language passed down from one generation to the next of deaf people, has all the complexity of spoken languages, and is as capable of expressing science, poetry, wit, historical change, and infinite nuances of meaning as are spoken languages. Importantly, ASL and other signed languages are not derived from the spoken language of the surrounding community: rather, they are autonomous languages with their own grammatical form and meaning. Although it was thought originally that signed languages were universal pantomime, or broken forms of spoken language on the hands, or loose collections of vague gestures, now scientists around the world have found that there are signed languages that spring up wherever there are communities and generations of deaf people (Klima and Bellugi 1988).

One can now specify the ways in which the formal properties of languages are shaped by their modalities of expression, sifting properties peculiar to a particular language mode from more general properties common to all languages. ASL, for example, exhibits formal structuring at the same levels as spoken languages (the internal structure of lexical units and the grammatical scaffolding underlying sentences) as well as the same kinds of organizational principles as spoken languages. Yet the form this grammatical structuring assumes in a visual–manual language is apparently deeply influenced by the modality in which the language is cast (Bellugi 1980).

The existence of signed languages allows us to enquire about the determinants of language organization from a different perspective. What would language be like if its transmission were not based on the vocal tract and the ear? How is language organized when it is based instead on the hands moving in space and the eyes? Do these transmission channel differences result in any deeper differences? It is now clear that there are many different signed languages arising independently of one another and of spoken languages. At the core, spoken and signed languages are essentially the same in terms of organizational principles and rule systems. Nevertheless, on the surface, signed and spoken languages differ markedly. ASL and other signed languages display complex linguistic structure, but unlike spoken languages, convey much of their structure by manipulating spatial relations, making use of spatial contrasts at all linguistic levels (Bellugi et al. 1989).

1. The Structure Of Sign Language

As already noted, the most striking surface difference between signed and spoken languages is the reliance on spatial contrasts, most evident in the grammar of the language. At the lexical level, signs can be separated from one another minimally by manual parameters (handshape, movement, location). The signs for summer, ugly, and dry are just the same in terms of handshape and movement, and differ only in the spatial location of the signs (forehead, nose, or chin). Instead of relying on linear order for grammatical morphology, as in English (act, acting, acted, acts), ASL grammatical processes nest sign stems in spatial patterns of considerable complexity (see Fig. 1), marking grammatical functions such as number, aspect, and person spatially. Grammatically complex forms can be nested spatially, one inside the other, with different orderings producing different hierarchically organized meanings.

Similarly, the syntactic structure specifying relations of signs to one another in sentences of ASL is also essentially organized spatially. Nominal signs may be associated with abstract points in a plane of signing space, and it is the direction of movement of verb signs between such endpoints that marks grammatical relations. Whereas in English, the sentences ‘the cat bites the dog’ and ‘the dog bites the cat’ are differentiated by the order of the words, in ASL these differences are signaled by the movement of the verb between points associated with the signs for cat and dog in a plane of signing space. Pronominal signs directed toward such previously established points or loci clearly function to refer back to nominals, even with many signs intervening (see Fig. 2). This spatial organization underlying syntax is a unique property of visual-gestural systems (Bellugi et al. 1989).

2. The Acquisition Of Sign Language By Deaf Children Of Deaf Parents

Findings revealing the special grammatical structuring of a language in a visual mode lead to questions about the acquisition of sign language, its effect on nonlanguage visuospatial cognition, and its representation in the brain. Despite the dramatic surface differences between spoken and signed languages—simultaneity and nesting sign stems in complex co-occurring spatial patterns—the acquisition of sign language by deaf children of deaf parents shows a remarkable similarity to that of hearing children learning a spoken language. Grammatical processes in ASL are acquired at the same rate and by the same processing by deaf children as are grammatical processes by hearing children learning English, as if there were a biological timetable underlying language acquisition.

First words and first signs appear at around 12 months; combining two words or two signs in children, whether deaf or hearing, occurs by about 18–20 months, and the rapid expansion signaling the development of grammar (morphology and syntax) develops in both spoken and signed languages by about 3–3 1/2 years. Just as hearing children show their mastery and discovery of grammatical regularities by producing over regularizations (‘I goed there,’ ‘wehelded the rabbit’), deaf children learning sign language show evidence of learning the spatial morphology signaling plural forms and aspectual forms by producing over regularizations in spatial patterns (see Fig. 3).

3. Neural Systems Subserving Visuospatial Languages

The differences between signed and spoken languages provide an especially powerful tool for understanding the neural systems subserving language. Consider the following: In hearing speaking individuals, language processing is mediated generally by the left cerebral hemisphere, whereas visuospatial processing is mediated by the right cerebral hemisphere. But what about a language that is communicated using spatial contrasts rather than temporal contrasts? On the one hand, the fact that sign language has the same kind of complex linguistic structure as spoken languages and the same expressivity might lead one to expect left hemisphere mediation. On the other hand, the spatial medium so central to the linguistic structure of sign language clearly suggests right hemisphere or bilateral mediation. In fact, the answer to this question is dependent on the answer to another, deeper, question concerning the basis of the left hemisphere specialization for language.

Specifically, is the left hemisphere specialized for language processing per se (i.e., is there a brain basis for language as an independent entity)? Or is the left hemisphere’s dominance generalized to process any type of information that is presented in terms of temporal contrasts? If the left hemisphere is indeed specialized for processing language itself, sign language processing should be mediated by the left hemisphere, as is spoken language. If, however, the left hemisphere is specialized for processing fast temporal contrasts in general, one would expect sign language processing to be mediated by the right hemisphere. The study of sign languages in deaf signers permits us to pit the nature of the signal (auditory-temporal vs. visual-spatial) against the type of information (linguistic vs. nonlinguistic) that is encoded in that signal as a means of examining the neurobiological basis of language (Poizner et al. 1990).

One program of studies examines deaf lifelong signers with focal lesions to the left or the right cerebral hemisphere. Major areas, each focusing on a special property of the visual-gestural modality as it bears on the investigation of brain organization for language, are investigated. There are intensive studies of large groups of deaf signers with left or right hemisphere focal lesions in one program (Salk); all are highly skilled ASL signers, and all used sign as a primary form of communication throughout their lives. Individuals were examined with an extensive battery of experimental probes, including formal testing of ASL at all structural levels; spatial cognitive probes sensitive to right-hemisphere damage in hearing people; and new methods of brain imaging, including structural and functional magnetic resonance imaging (MRI, fMRI), event-related potentials (ERP), and positron emission tomography (PET). This large pool of well-studied and thoroughly characterized subjects, together with new methods of brain imaging and sensitive tests of signed as well as spoken language allows for a new perspective on the determinants of brain organization for language (Hickok and Bellugi 2000, Hickok et al. 1996).

3.1 Left Hemisphere Lesions And Sign Language Grammar

The first major finding is that so far only deaf signers with damage to the left hemisphere show sign language aphasias. Marked impairment in sign language after left hemisphere lesions was found in the majority of the left hemisphere damaged (LHD) signers, but not in any of the right hemisphere damaged (RHD) signers, whose language profiles were much like matched controls. Figure 4 presents a comparison of LHD, RHD, and normal control profiles of sign characteristics from The Salk Sign Diagnostic Aphasia Examination—a measure of sign aphasia. The RHD signers showed no impairment at all in any aspect of ASL grammar; their signing was rich, complex, and without deficit, even in the spatial organization underlying sentences of ASL. By contrast, signers with LHD showed markedly contrasting profiles: one was agrammatic after her stroke, producing only nouns and a few verbs with none of the grammatical apparatus of ASL, another made frequent paraphasias at the sign internal level, and several showed many grammatical paraphasias, including neologisms, particularly in morphology.

Another deaf signer showed deficits in the spatially encoded grammatical operations which link signs in sentences, a remarkable failure in the spatially organized syntax of the language. Still another deaf signer with focal lesions to the left hemisphere reveal dissociations not found in spoken language: a dissociation between sign and gesture, with a cleavage between capacities for sign language (severely impaired) and manual pantomime (spared). In contrast, none of the RHD signers showed any within-sentence deficits; they were completely unimpaired in sign sentences and not one showed aphasia for sign language (in contrast to their marked nonlanguage spatial deficits, described below) (Hickok and Bellugi 2000, Hickok et al. 1998).

Moreover, there are dramatic differences in performance between left-and right-hemisphere damaged signers in formal experimental probes of sign competence. For example, a test of the equivalent of rhyming in ASL provides a probe of phonological processing. Two signs ‘rhyme’ if they are similar in all but one phonological parametric value such as hand- shape, location, or movement. To tap this aspect of phonological processing, subjects are presented with an array of pictured objects and asked to pick out the two objects whose signs rhyme (Fig. 5). The ASL signs for key and apple share the same hand-shape and movement, and differ only in location, and thus are like rhymed pairs. LHD signers are significantly impaired relative to RHD signers and controls on this test, another sign of the marked difference in effects of right-and left-hemisphere lesions on signing. On other tests of ASL processing at different structural levels, there are similar distinctions between left- and right-lesioned signers, with the right-lesioned signers much like the controls, but the signers with left hemisphere lesions significantly impaired in language processing. Moreover, studies have found that there can be differential breakdown of linguistic components of sign language (lexicon and grammar) with different left hemisphere lesions.

3.2 Right Hemisphere Lesions And Nonlanguage Spatial Processing

These results from language testing contrast sharply with results on tests of nonlanguage spatial cognition. RHD signers are significantly more impaired on a wide range of spatial cognitive tasks than LHD signers, who show little impairment. Drawings of many of the RHD signers (but not those with LHD) show severe spatial distortions, neglect of the left side of space, and lack of perspective. RHD deaf signers show lack of perspective, left neglect, and spatial disorganization on an array of spatial cognitive nonlanguage tests (block design, drawing, hierarchical processing), compared with LHD deaf signers. Yet, astonishingly, these severe spatial deficits among RHD signers do not affect their competence in a spatially nested language, ASL. The case of a signer with a right parietal lesion leading to severe left neglect is of special interest: Whereas his drawings show characteristic omissions on the left side of space, his signing (including the spatially organized syntax) is impeccable, with signs and spatially organized syntax perfectly maintained.

The finding that sign aphasia follows left hemisphere lesions but not right hemisphere lesions provides a strong case for a modality-independent linguistic basis for the left hemisphere specialization for language. These data suggest that the left hemisphere is predisposed biologically for language, independent of language modality. Thus, hearing and speech are not necessary for the development of hemisphere specialization—sound is not crucial. Furthermore, the finding of a dissociation between competence in a spatial language and competence in nonlinguistic spatial cognition demonstrates that it is the type of information that is encoded in a signal (i.e., linguistic vs. spatial information) rather than the nature of the signal itself (i.e., spatial vs. temporal) that determines the organization of the brain for higher cognitive functions.

4. Language, Modality, And The Brain

Analysis of patterns of breakdown in deaf signers provides new perspectives on the determinants of hemispheric specialization for language. First, the data show that hearing and speech are not necessary for the development of hemispheric specialization: sound is not crucial. Second, it is the left hemisphere that is dominant for sign language. Deaf signers with damage to the left hemisphere show marked sign language deficits but relatively intact capacity for processing nonlanguage visuospatial relations. Signers with damage to the right hemisphere show the reverse pattern. Thus, not only is there left hemisphere specialization for language functioning, there is also complementary specialization for nonlanguage spatial functioning. The fact that grammatical information in sign language is conveyed via spatial manipulation does not alter this complementary specialization.

Furthermore, components of sign language (lexicon and grammar) can be selectively impaired, reflecting differential breakdown of sign language along linguistically relevant lines. These data suggest that the left hemisphere in humans may have an innate predisposition for language, regardless of the modality. Since sign language involves an interplay between visuospatial and linguistic relations, studies of sign language breakdown in deaf signers may, in the long run, bring us closer to the fundamental principles underlying hemispheric specialization.

Bibliography:

• Bellugi U 1980 The structuring of language: Clues from the similarities between signed and spoken language. In: Bellugi U, Studdert-Kennedy M (eds.) Signed and Spoken Language: Biological Constraints on Linguistic Form. Dahlem Konferenzen. Weinheim Deerfield Beach, FL, pp. 115–40
• Bellugi U, Poizner H, Klima E S 1989 Language, modality and the brain. Trends in Neurosciences 10: 380–8
• Emmorey K, Kosslyn S M, Bellugi U 1993 Visual imagery and visual-spatial language: Enhanced imagery abilities in deaf and hearing ASL signers. Cognition 46: 139–81
• Hickok G, Bellugi U 2000 The signs of aphasia. In: Boller F, Grafman J (eds.) Handbook of Neuropsychology, 2nd edn. Elsevier Science Publishers, Amsterdam, The Netherlands
• Hickok G, Bellugi U, Klima E S 1996 The neurobiology of signed language and its implications for the neural organization of language. Nature 381: 699–702
• Hickok G, Bellugi U, Klima E S 1998 The basis of the neural organization for language: Evidence from sign language aphasia. Reviews in the Neurosciences 8: 205–22
• Klima E S, Bellugi U 1988 The Signs of Language. Harvard University Press, Cambridge, MA
• Poizner H, Klima E S, Bellugi U 1990 What the Hands Reveal About the Brain. MIT Press Bradford Books, Cambridge, MA

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August 23, 2024

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Being a 'weekend warrior' could be as good for brain health as exercising throughout the week

by Matthew Ahmadi and Emmanuel Stamatakis, The Conversation

With the responsibilities of adulthood, free time can be a rare commodity. Many of us find ourselves asking, "I barely have time to cook dinner. How can I find time to exercise regularly during the week?"

The health benefits of exercise—which include reduced risk of chronic diseases such as heart disease and dementia —can seem out of reach due to the pressures of work and life.

But a new study published in the journal Nature Aging offers some good news for people who struggle to fit regular exercise into their weekday schedules.

The findings suggest " weekend warriors "—those who get most of their exercise on the weekend —may enjoy the same brain health and mental health benefits as those who exercise regularly throughout the week.

What the study did

The research team, from China, analyzed data from more than 75,000 people from the UK Biobank . This is a large cohort study tracking the health of about half a million people in the United Kingdom. More than 100,000 of them wore wearable activity trackers. The average age of participants in this study was 62.

Participants provided data from wrist-worn wearable devices to track their physical activity patterns over a period of seven days. They were then categorized into three groups:

• inactive: people who were not meeting the recommended 150 minutes of moderate-to-vigorous physical activity per week
• regularly active: those meeting the guidelines with activity spread throughout the week

"weekend warriors": people meeting the guidelines by accumulating more than 50% of their activity across one to two days (this was not necessarily Saturday and Sunday, but any one or two days of the week).

The researchers followed up with participants for a median period of 8.4 years. They used GP records, hospitalization data and death records to track the onset of neurological diseases (dementia, stroke and Parkinson's disease) as well as psychological disorders (including depression and anxiety).

The researchers adjusted for several key lifestyle and health factors that could affect these outcomes. These factors included age, sex, smoking status, alcohol consumption , diet and history of conditions such as diabetes, hypertension (high blood pressure) and cancer.

Weekend warriors reap big rewards

Among the roughly 75,500 participants, about 24,300 were classified as inactive, 21,200 as regularly active and 30,000 as weekend warriors.

The results showed that, compared to inactive adults, weekend warriors had a 26% lower risk of developing dementia, a 21% lower risk of stroke and a 45% lower risk of Parkinson's disease. Their risk was 40% and 37% lower for depression and anxiety respectively compared to the inactive group. All these figures in the weekend warrior group were comparable to outcomes for those who were regularly active.

The protective associations against depression and anxiety were consistent across age groups, both under and over 65. However, the reduced risks for dementia, stroke and Parkinson's disease were particularly pronounced in people over 65. This finding reflects the significant benefits of physical activity for older adults, who are at higher risk of these conditions.

There's more than one way to get the benefits

What if weekends are off-limits for exercise due to work, family duties or other commitments? Fortunately, the researchers explored different patterns of the weekend warrior lifestyle.

They found that as long as people accumulated the majority of moderate-to-vigorous physical activity on any one or two days of the week—even if these weren't consecutive days—they achieved similar health benefits.

In a previous study , also using UK Biobank data, researchers similarly found people who do most of their exercise across one or two days see similar benefits for heart health as those whose physical activity is spread more evenly across the week.

And if traditional gym-based exercise isn't your thing, you're still in luck. The study used activity trackers that monitored all types of activities. So regardless of how you accumulate your moderate-to-vigorous activity, this study suggests you'll reap the health benefits.

This aligns with a growing body of research that shows that whether it's short bursts of daily activities like stair climbing or household chores or going for a walk at the park, or longer sessions of running or gym workouts, the health benefits are there for everyone.

Some caveats to consider

The researchers accounted for various lifestyle and health factors. However, it's still possible other factors could have influenced some of the associations.

Another limitation is that the study couldn't assess how changes in physical activity over time might impact brain health. Previous research has shown that even inactive adults who increase their activity levels can experience immediate health benefits.

Nonetheless, the findings add to a substantial body of evidence supporting the brain health benefits and overall health benefits of moderate-to-vigorous physical activity—on whatever days of the week you can fit it in.

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