Toward XAI for Intelligent Tutoring Systems: A Case Study

Our research is a step toward understanding when explanations of AIdriven hints and feedback are useful in Intelligent Tutoring Systems (ITS). We added an explanation functionality for the adaptive hints provided by the Adaptive CSP (ACSP) applet, an inte lligent interactive simulation that helps students learn an algorithm for constraint satisfaction problems. We present the design of the explanation functionality and the results of an exploratory study to evaluate how students use it, including an analysis of how students' experience with the explanation functionality is affected by several personality traits and abilities . Our results show a significant impact of a measure of curiosity and the Agreeableness personality trait and provide insight toward des igning personalized Explainable AI (XAI) for ITS .