Dr. Danielle McNamara is the Director of the Science of Learning and Educational Technology (SoLET) lab at Arizona State University. The overarching theme of her research is to better understand cognitive processes involved in comprehension, writing, knowledge acquisition, and memory, and to apply that understanding to educational practice by developing and testing Natural Language Processing (NLP) tools and educational technologies (e.g., Coh-Metrix, iSTART, Writing Pal). This work integrates various approaches and methodologies including the development of game-based, intelligent tutoring systems (e.g., iSTART, Writing Pal), the development of natural language processing tools (e.g., iSTART, Writing Pal, Coh-Metrix, the Writing Assessment Tool), basic research to better understand cognitive and motivational processes involved in comprehension and writing, and the use of learning analytics across multiple contexts. Two of her projects, The Writing Pal and iSTART, are computer assisted learning programs designed to advance students writing and reading comprehension. Coh-Metrix is a text analysis tool designed to advance our understanding of the nature of text difficulty.

Over the years, she has published over 300 papers and secured over 20 million in funding. Her work has been funded by the Institute of Education Sciences (IES), the National Science Foundation (NSF), the Office of Naval Research (ONR), the McDonnell Foundation, and the Gates Foundation. She has served as Associate Editor for four journals, topiCS, the Cognitive Science Journal, the International Journal of Artificial Intelligence in Education, and the Journal of Educational Psychology. She has also served on the Governing Board for the Cognitive Science Society and as President of the Society for Text and Discourse.
Ph.D., Cognitive Psychology, University of Colorado Boulder,
M.A., Clinical Psychology, Wichita State University, 1989
B.A., Linguistics, University of Kansas, 1982
Areas of Research / Professional Expertise
Cognitive Science; Discourse Processes; Educational Technology; Natural Language Processing; Learning Analytics; Linguistics; Educational Data Mining