Modeling shared states for adaptive instruction

Abstract

This paper discusses methods in which adaptive instructional techniques, strategies and tactics (collectively referred to henceforth as adaptive instruction) might be applied in a multi-learner or team training domain where accurate shared models of cognition and affect are critical to optimizing team performance, and individual learning, retention, and transfer. Application of these models in the Generalized Intelligent Framework for Tutoring (GIFT) is also discussed.