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Science of Learning and Educational Technology (McNamara)

Keywords:  knowledge acquisition; reading comprehension; writing; strategies; self-explanation; writing assessment; intelligent tutoring systems; tutoring; games; computational linguistics; learning analytics

Lab Research Area:

The Science of Learning and Educational Technology (SoLET) Lab, directed by cogntive psychologist Dr. Danielle S. McNamara, is a research laboratory housed in the Institute for Science and Teaching of Learning at ASU.

The SoLET lab focuses on applying research from computer science, education, and psychology in educational environments. The research aims to further the understanding of cognitive processes and to use this theoretical foundation to improve educational methods.

Research Projects

Reading Comprehension. The majority of high school students lack adequate literacy skills, placing them below the proficiency level for their grade, and calling for improvements in reading comprehension training. Dr. McNamara discovered the importance of textual coherence and a reader’s prior knowledge in the reader’s abilities to form coherent mental representations of text. This led to the consideration of the importance inferencing skills have when readers try to comprehend complex text. This research led to the current exploration of self-explanation training as a means of improving reading comprehension. Self-explanation prompts students to connect the information they are reading to their prior knowledge as well as to information previously presented in the text.

Intelligent Tutoring Systems. Dr. McNamara developed two Intelligent Tutoring Systems, iSTART and Writing Pal, for reading comprehension and writing instruction and practice. These educational technologies enable researchers to better understand cognitive processes involved in comprehension, knowledge and skill acquisition, and writing. Research on these technologies has explored methods for improving student engagement via game-based practice, enhancing adaptability functions, and assessing the feasibility and usability of these systems in real world settings such as high school classrooms.

Natural Language Processing. Much of the research in the lab employs computational linguistics—such as Natural Language Processing (NLP) techniques—as a means of analyzing discourse. This research has led to the development and testing of multiple NLP tools that have been used in various research projects involving essay writing, reading comprehension, second language learning, and creativity. These tools have been applied to the intelligent tutoring systems—the Writing Pal and iSTART—in order to assess students’ written responses and provide automated feedback. The lab’s current research also explores how these tools can be applied to other learning environments such as computer supported collaborative learning environments and massive open online courses (MOOCs).  

For more information please see the SoLET Lab website.

Lab Director and Principal Investigator: Danielle S. McNamara, PhD, Professor of Psychology

Dr. McNamara develops educational technologies and conducts research to better understand cognitive processes of comprehension, learning, comprehension strategies, text coherence, and individual differences. She and her team have developed a number of educational technologies (e.g., iSTART, iSTART-ME, Coh-Metrix, and Writing-Pal). She is particularly interested in how the effects of such tools interact with individual differences and can be optimized for individual learners. Curriculum Vitae.


Research Faculty

Jianmin Dai, PhD,  Assistant Research Professor
Dr. Jianmin Dai received his PhD in System Engineering from the Huazhong University of Science and Technology in China in 2006, and served as a Postdoctoral Fellow on the Writing Pal project with Danielle McNamara from 2008-2011. Jianmin's primary interests are in R&D Intelligent Tutoring Systems (ITS) and game-based education technology. His research focus is on the application of Natural Language Processing and Machine Learning in ITS and game-based education system.

Matthew Jacovina, PhD, Assistant Research Professor
Dr. Jacovina studies the cognitive processes that guide comprehension and communication. His work focuses on situations in which success is complicated by mismatches between discourse content and prior knowledge, preferential biases, or time pressure. He is interested in how individual differences influence success in these situations, and how educational technology can leverage these understandings to individualize and improve learning. He is currently working on the optimization of iSTART-2 and Writing Pal, game-based tutoring systems teaching reading and writing strategies.

Amy Johnson, PhD,  Assistant Research Professor
Dr. Johnson received her PhD in Cognitive Psychology from the University of Memphis in 2011, and came to ASU as Assistant Research Scientist. Amy's primary interests concern effective integration of multiple external representations, successful engineering education environments, self-regulated learning with hypermedia, and optimal methods for educational technology. She currently works on design and development of iSTART for adult literacy learners.

ASU Faculty Collaborator(s)

Rod D. Roscoe, PhD,  Assistant Professor, Human Systems Engineering
Dr. Roscoe studies the metacognitive, cognitive, and motivational process of learning, and how these processes can be effectively facilitated via educational technology and games, strategy instruction, and peer support. He has contributed to the research and design of several technologies (e.g., Writing Pal, Coh-Metrix, Betty’s Brain, and iSTART-ME) that address diverse topics of reading, writing, science, self-explanation, self-regulated learning, and causal reasoning. He is particularly interested in how users' expectations, perceptions, and roles can be leveraged to improve engagement with and efficacy of educational technologies.

Post-doctoral Research Fellow(s)

Elizabeth Tighe, PhD
Dr. Tighe received her PhD in cognitive psychology from Florida State University in 2015.  Her primary research focuses on understanding the literacy skills and instructional needs of adults enrolled in Adult Basic and Secondary Education programs.  She is also interested in applying innovative and rigorous research designs and statistical analyses to the field of reading research.  She is currently working on data collection of a large battery of adults' component reading skills and modifying iSTART for use in adult literacy settings.

Graduate Student(s)

Laura Allen, Doctoral Student, Cognitive Psychology, Department of Psychology
Laura's research investigates the cognitive individual differences that contribute to proficiency in reading comprehension and writing, as well as the application of cognitive principles to educational practice. The majority of her current research projects focus on the application of natural language processing techniques to better understand cognition, particularly with respect to text-based communication. 

Laboratory Staff

Sanchit Bapat, Computer Programming Assistant
Sanchit is a Computer Science graduate student at Arizona State University. He is currently involved in providing technical support for Writing Pal and iSTART projects. His interests are developing user friendly web applications and making them more secure.


Joseph Curcuru, Research Aid
Joseph is a graduate student at Arizona State University. He is currently involved in recruiting, scheduling, and running Writing Pal and iStart research studies. His interested include research observation, communication, and reading and writing development.


Kevin Kent, Research Specialist
Kevin joined ASU in August of 2015 after completing a master's degree from the Harvard Graduate School of Education with a concentration in Mind, Brain, and Education. He is particularly interested in applying cognitive science to the design of learning environments, with the goal of empowering all students to be master learners. He is also interested in using dynamical analyses to better understand the processes of learning.

 Cecile Perret, Research Technician
Cecile graduated from ASU with a Bachelor’s of Science degree in Psychology in May 2014. She has assisted the SoLET lab in their research as an undergraduate student and continues to do so as an research technician at ASU's Learning Sciences Institute. She is interested in how Intelligent Tutoring Systems can help students develop and apply their critical thinking skills to various tasks.

Gaurav Kumar Srivastav, Computer Programming Assistant
Gaurav joined ASU in fall 2014 as a graduate student in Computer Science. He is currently working as assistant programmer for Writing Pal and iSTART projects. His area of interests are web development, data analytics and data mining.


 Melissa Stone, Research Specialist
Melissa graduated from ASU’s Barrett, the Honors College in May 2014, and is now assisting the SoLET Lab as a research specialist. A former research assistant, she is excited to return to the lab and contribute to the development of its research. Her research interests include the intersection of psychology and education, as well as the clinical application of drama therapy.


If you are interested in joining the SoLET Lab as an Undergraduate Research Assistant, then please visit Psychology's Research Opportunity page for more information. Priority is given to Psychology majors but all science majors are encouraged to apply. 


Select Publications

Below are a sample of recent publications from Dr. McNamara's research and lab. A more complete listing may be found on Dr. McNamara's curriculum vitae or by visiting the external SoLET Lab website.

Allen, L. K., McNamara, D. S., & McCrudden, M. T. (2015). Change your mind: Investigating the effects of self-explanation in the resolution of misconceptions. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. Maglio, Proceedings of the 37th Annual Meeting of the Cognitive Science Society (Cog Sci 2015). Pasadena, CA.

McNamara, D. S., Crossley, S. A., Roscoe, R. D., Allen, L. K., & Dai, J. (2015). Hierarchical classification approach to automated essay scoring. Assessing Writing, 23, 35-59.

McNamara, D. S., Jacovina, M. E., Snow, E. L., & Allen, L. K. (2015). From generating in the lab to tutoring systems in classrooms. American Journal of Psychology, 128(2), 159-172.

Roscoe, R. D., Snow, E. L., Allen, L. K., & McNamara, D. S. (2015). Automated detection of essay revising patterns: application for intelligent feedback in a writing tutor. Technology, Instruction, Cognition, and Learning, 10, 59-79.

Allen, L. K., Snow, E. L., Crossley, S. A., Jackson, G. T., & McNamara, D. S. (2014). Reading comprehension components and their relation to the writing process. L'année psychologique/Topics in Cognitive Psychology, 114, 663-691.

McNamara, D. S., Graesser, A. C., McCarthy, P., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. Cambridge: Cambridge University Press.

Snow, E. L., Jackson, G. T., & McNamara, D. S. (2014). Emergent behaviors in computer-based learning environments: Computational signals of catching up. Computers in Human Behavior, 41, 62-70.

McNamara, D. S. (2013). The epistemic stance between the author and reader: A driving force in the cohesion of text and writing. Discourse Studies, 15, 575-592.

McNamara, D. S., Crossley, S. A., & Roscoe, R. D. (2013). Natural language processing in an intelligent writing strategy tutoring system. Behavior Research Methods, 45, 499-515.

Jackson, G. T., & McNamara, D. S. (2013). Motivation and performance in a game-based intelligent tutoring system. Journal of Educational Psychology, 105, 1036-1049.

Roscoe, R. D., & McNamara, D. S. (2013). Writing Pal: Feasibility of an intelligent writing strategy tutor in the high school classroom. Journal of Educational Psychology, 105, 1010-1025.

2012 and older
Crossley, S. A., & McNamara, D. S. (2012). Predicting second language writing proficiency: The roles of cohesion and linguistic sophistication. Journal of Research in Reading, 53, 115-136.

Graesser, A. C., McNamara, D. S., & Kulikowich, J. M. (2011). Coh-Metrix: Providing multilevel analyses of text characteristics. Educational Researcher, 40, 223-234.

McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1–43.

In the News and More!

Professor Danielle McNamara honored by UC Merced with Distinguished Cognitive Scientist Award of 2015.  Read More (posted 6/16/15).