Impact Analysis of the Use of Artificial Intelligence with Self-Regulated Learning Theory on Student Academic Performance in Indonesia

This study examines the influence of artificial intelligence (AI) on the academic achievement of students in Indonesia, using the self-regulated learning ) theory as a framework. We conducted a study using an online questionnaire that was completed by 242 students. Our analysis focused on the impact of metacognition, motivation, and behavior on academic outcomes. The findings indicate that metacognition accounts for 27.6<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> of the variation in academic performance, motivation accounts for 44.3%, and behavior contributes to 29.8%. Together, these factors explain a total of 90.7<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> of the achievement. The results emphasize the importance of educators and parents overseeing the use of AI, ensuring that it improves learning without promoting dependency. The article offers practical suggestions for stakeholders to efficiently utilize artificial intelligence in educational settings, with the goal of enhancing student motivation and academic achievement.