Effect of explainable artificial intelligence adaptive tutor on High School students’ motivation and learning outcomes - Marpaung, Fifit L; Sari, Ni Made Ameylia; Reno, Reno; Sulistiani, Heni (Proceeding of International Conference on Islamic Education (ICIED), 2025)
The development of artificial intelligence (AI) in education has created new opportunities for the development of more customized learning environments. However, students' confidence and involvement tend to decline when traditional AI-powered educational systems lack transparency. This study examines how an adaptive tutoring system based on Explainable Artificial Intelligence (XAI) affects high school students' academic performance and motivation. Two learner groups were included in the quasi-experimental framework; one group used a conventional adaptive tutor, while the other group used a XAI-integrated adaptive tutor that was able to fully explain each instructional recommendation. Academic performance evaluations, motivation questionnaires, and system interaction logs were used to collect data. According to the results, students who used the XAI-enhanced instructor had much greater motivation and better learning outcomes than students in the control group. Students' self-control and confidence in their ability to learn were strengthened by the clear feedback systems, which enabled them to understand the reasoning behind instructional assistance. Overall, the study emphasizes how crucial explainability is to fostering learner trust, long-term engagement, and significant knowledge acquisition in AI-supported educational systems.