Toward Scenario Adaptation for Learning

Authors:
James Niehaus;Mark Riedl
Affiliations:
School of Interactive Computing, Georgia Institute of Technology, jniehaus@cc.gatech.edu, riedl@cc.gatech.edu;School of Interactive Computing, Georgia Institute of Technology, jniehaus@cc.gatech.edu, riedl@cc.gatech.edu
Venue:
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Year:
2009

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Abstract

This paper presents a methodology for automatically customizing a scenario to suit a learner's abilities, needs, or goals. Training scenarios are often utilized to give learners hands-on experience with real-life problem solving tasks. The customization of scenarios has the potential to improve learning gains within these domains. We present initial steps toward an intelligent technology called a Scenario Adaptor that employs a partial order planning formalism to reason about learning objectives and causality, and we discuss how the Scenario Adaptor may add or delete learning objectives from a scenario.