Exploring How to Adaptively Apply Tutorial Dialogue Tactics

Abstract

Prior research aimed at identifying linguistic features of tutoring that predict learning found interactions between student characteristics (e.g., incoming knowledge level, gender, and affect) and learning. This paper addresses the question: What do these interactions suggest for developing adaptive natural-language tutoring systems? We summarize two studies which investigated interactions between gender and learning in a tutoring system for conceptual physics. We argue that student characteristics such as gender are insufficient to guide the development of adaptive tutorial dialogue systems. A more fruitful approach is to consider the underlying factors and cognitive mechanisms that potentially mediate the relationship between student characteristics and learning from particular tutoring tactics.