Carolyn Forsyth is a research scientist in the Learning and Assessment Foundations and Innovations in the Research & Development division at ETS. She earned a Ph.D. in cognitive psychology with cognitive science graduate certification from the University of Memphis in 2014. Her research at ETS has focused on innovating and improving technology-enhanced assessment and learning environments primarily via theoretically grounded data mining techniques including computational linguistic approaches. She explores and develops computerized environments for learning and assessment that include conversation-based assessment, game-based assessment, and simulation-based assessment. Findings from theoretically grounded data mining explorations within these environments are used to improve existing systems, inform the larger scientific community about relevant findings for learning and assessment, and create new learning and assessment environments. Her work in these areas have yielded over four dozen peer-reviewed publications and presentations.
She has served as a guest editor for a special edition of the Journal of Educational Data Mining on articles resulting from a multi-institution-hosted competition using National Assessment of Educational Progress data and is a consistent program committee member for the International Conference on Artificial Intelligence and Education and the International Conference on Educational Data Mining. She recently concluded a grant funded by the National Science Foundation, where she served as a coprincipal investigator and has another multi-institutional external grant pending.