Computational aspects of the intelligent tutoring system metatutor
We present in this paper the architecture of MetaTutor, an intelligent tutoring system that teaches students meta-cognitive strategies while learning about complex science topics. A more in-depth presentation of the micro-dialogue component in MetaTutor is provided. This component handles the meta-cognitive strategy of subgoal generation. This strategy involves subgoal assessment and feedback generation. We present a taxonomy-driven method for subgoal assessment and feedback. The method yields very good to excellent human-computer agreement scores for subgoal assessment (average kappa=0.77). Copyright © 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23
Rus, V., Lintean, M., & Azevedo, R. (2010). Computational aspects of the intelligent tutoring system metatutor. Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23, 522-527. Retrieved from https://digitalcommons.memphis.edu/facpubs/2641