New Publication: "Incorporating students' probabilistic expectations into a peer-driven tutoring game"

Bader-Natal, A. Incorporating students' probabilistic expectations into a peer-driven tutoring game. Brandeis CS Tech Report CS-08-269, 2008.
Abstract Draft PDF

Games provide a promising mechanism for intelligent tutoring systems in that they offer means to influence motivation and structure interactions. We have designed and released several game-based tutoring systems in which students learn to identify the best game strategies to adopt, and, in doing so, create for each other increasingly productive learning environments. Here, we first detail the core game underlying our deployed systems, designed to leverage human intelligence in tutoring systems through the tutor's identification of "appropriate" challenges for their tutee. While this game works well for task domains in which problem difficulty is known, it cannot be applied to domains if nothing is known about a problem beyond its correct solution. We introduce a second, more robust, game here capable of addressing this larger set of task domains. By incorporating player-generated probability estimates (in place of a difficulty metric), we show that a game can be designed to simultaneously elicit best-effort responses from tutees, honest statements of probability estimates from tutees, and appropriate challenges from tutors. We derive a set of constraints on the parameterized version of this game necessary for rational players to converge on this "Teacher's Dilemma" learning environment. Beyond providing a foundation for future tutoring systems, this work offers a new mechanism with which to simultaneously leverage and enhance the knowledge of peer learners.