Abstract
We explore eXplainable AI (XAI) to enhance user experience and understand the value of explanations in AI-driven pedagogical decisions within an Intelligent Pedagogical Agent (IPA). Our real-time and personalized explanations cater to students’ attitudes to promote learning. In our empirical study, we evaluate the effectiveness of personalized explanations by comparing three versions of the IPA: (1) personalized explanations and suggestions, (2) suggestions but no explanations, and (3) no suggestions. Our results show the IPA with personalized explanations significantly improves students’ learning outcomes compared to the other versions.
Type
Publication
In 2023 ACM International Conference on Intelligent Virtual Agents
John Wesley Hostetter
Computer Science Ph.D. Student
My research interests include fuzzy logic, artificial intelligence, and machine learning.