Graphical Representations and Causal Models in Intelligent Interactive LearningEnvironments

摘要

This research project investigates how an interactive learning environment cansupport students learning and acquisition of mental models when acquiring a target cognitive skill. In this project, we have constructed GIL, an intelligent tutoring system for LISP programming, and have used GIL to conduct pedagogical experiments on skill acquisition. Progress in the current year includes extensions to GIL's graphical representation and model tracing capabilities. The experiments run this year include a study of how GIL's graphical representations facilitate learning for complex programming skills and how GIL enables students to engage in a more natural resoning than the traditional text-based representation of the programming language.