Scaffolding Student Learning with Interactive Adaptive Technologies: Challenges and Directions
Kasia Muldner received her Ph.D. from the Department of Computer Science at the University of British Columbia, where she designed and evaluated a computational tutor that supported students during analogical problem solving. She is currently a post-doctoral researcher in the Department of Computing, Informatics, and Decision Systems Engineering at Arizona State University. Her work falls into the intersection of Human-Computer-Interaction and Artificial Intelligence, dealing with the design and evaluation of interactive educational technologies that aim to help students learn effectively though personalized support. She is particularly interested in technologies that support high level student states related to meta-cognition, affect, and creativity. Her work was recently recognized through the annual James Chen User Modeling and User Adapted Interaction (UMUAI) award given to the best journal paper in this venue.