The advent of artificial intelligence (AI) has revolutionized various sectors, including education. Generative AI, a subset of AI, has shown significant potential in developing intelligent tutoring systems (ITS) designed to enhance learning experiences through personalized tutoring and scaffolding. ITS systems can adapt to individual learner needs, offering customized feedback and support that traditional educational methods lack. Early studies have demonstrated the potential of AI to enhance learning outcomes, improve engagement, and provide scalable educational solutions (Grassini, 2023).
In this session, we will report the results of a mixed methods pilot study that explores using Khan Academy's Khanmigo, a generative AI-powered tutor, to teach complex scientific concepts. Specifically, it focuses on lunar phases, a fundamental concept in astronomy and science education. By functioning as an intelligent tutor and providing scaffolded learning experiences during the study, Khanmigo can offer tailored educational support that adapts to the unique needs of each learner. We measured the impact of Khanmigo on learner engagement, comprehension, cognitive load, and overall educational experience.
Besides presenting the results of the pilot study, the session will be organized as a dialogue and idea-sharing session between the presenters and the audience. Different uses of generative AI for learning will be discussed.
Lastly, this study contributes to the growing body of knowledge on AI in education, offering valuable perspectives on the potential and challenges of using generative AI as an intelligent tutor. The findings will inform future developments in educational technology, guiding the design of more effective and personalized learning tools.
