Applying Reinforcement Learning to Take Pedagogical Decisions in Intelligent Tutoring Systems

[Proceedings of] 4th International Conference on New Educational Environments, Lugano, Switzerland, May 8-1, 2002In this paper we propose the use of a Reinforcement Learning model that avoids the problems derived from construction of different pedagogic strategies for each student in intlligent tutoring systems. This model consists on defining the pedagogical module of any ITS (domain independent) as an action policy learned by trial and error (as human tutors do). This paper exposes the foundation of a theoretical model, proposing a representation of the domain module in intelligent tutoring systems. Currently, it is being implemented in a specific domain application, the database design learning.Publicad