Unlocking student potential: How AI-driven personalized feedback shapes goal achievement, self-efficacy, and learning engagement through a self-determination lens

This study explores how AI-driven personalized feedback influences goal achievement, self- efficacy, and learning engagement in Chinese college students through a self-determination theory lens. The participants, 1079 Chinese college students (56.2 % female, 43.8 % male; mean age = 21.4), including undergraduates, graduates, and PhD students, came from various academic disciplines. The study examines how personalized AI feedback impacts students’ motivation and academic performance. Data were collected via a questionnaire and analyzed using SPSS (version 27) and AMOS (version 24), employing descriptive statistics, correlation, regression analysis, and structural equation modeling (SEM) to investigate relationships among variables. The results reveal significant positive relationships between AI-driven personalized feedback and students’ goal achievement, academic self-efficacy, and learning engagement. AI feedback enhances students’ clarity of goals, boosts their confidence, and increases their involvement in learning by providing adaptive, personalized support. It fosters a sense of mastery and control, improving both goal achievement and self-efficacy, which subsequently enhances engagement. The study finds that AI-driven feedback is a strong predictor of these outcomes, with more personalized feedback leading to higher levels of motivation, engagement, and confidence. This research underscores the importance of AI-driven personalized feedback in supporting students’ academic success and intrinsic motivation.