Toward Scenario Adaptation for Learning

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.

• Type: Conference
• Year: 2009
• Where: AIED
• Authors: James Niehaus, Mark Riedl
• Keywords: AIED 2009, Artificial Intelligence, Learners Hands-on Experience, Scenario, Scenario Adaptor