AI Magazine - Special issue on achieving human-level AI through integrated systems and research
Interacting with Computers
Effective feedback content for tutoring complex skills
Human-Computer Interaction
Serious Use of a Serious Game for Language Learning
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
BiLAT: A Game-Based Environment for Practicing Negotiation in a Cultural Context
International Journal of Artificial Intelligence in Education
An analysis of students' gaming behaviors in an intelligent tutoring system: predictors and impacts
User Modeling and User-Adapted Interaction
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The role of explicit feedback in learning has been studied from a variety of perspectives and in many contexts. In this paper, we examine the impact of the specificity of feedback delivered by an intelligent tutoring system in a game-based environment for cultural learning. We compared two versions: one that provided only “bottom-out” hints and feedback versus one that provided only conceptual messages. We measured during-training performance, in-game transfer, and long-term retention. Consistent with our hypotheses, specific feedback utterances produced inferior learning on the in-game transfer task when compared to conceptual utterances. No differences were found on a web-based post-test. We discuss possible explanations for these findings, particularly as they relate to the learning of loosely defined skills and serious games.