Co-Evolution in the Successful Learning of Backgammon Strategy
Machine Learning
SimEd: Simulating Education as a Multi Agent System
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
IEEE Intelligent Systems
Assessing Learning in a Peer-Driven Tutoring System
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
BEEweb: a multi-domain platform for reciprocal peer-driven tutoring systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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Formalizing a student model for an educational system requires an engineering effort that is highly domain-specific. This model-specificity limits the ability to scale a tutoring system across content domains. In this work we offer an alternative, in which the task of student modeling is not performed by the system designers. We achieve this by using a reciprocal tutoring system in which peer-tutors are implicitly tasked with student modeling. Students are motivated, using the Teacher's Dilemma, to use these models to provide appropriately-difficult challenges. We implement this as a basic literacy game in a spelling-bee format, in which players choose words for each other to spell across the internet. We find that students are responsive to the game's motivational structure, and we examine the affect on participants' spelling accuracy, challenge difficulty, and tutoring skill.