Generative artificial intelligence and academic well-being mediated by basic psychological needs in a self-determination theory framework

Abstract This study explored how generative artificial intelligence (GenAI) can impact academic well-being using Self-Determination Theory (SDT) and the mediating mechanism of basic psychological needs (BPN). This study analyses the hypothesized relations based on the data collected from the undergraduat​es students learning Mandarin Chinese using AI. The results show that GenAI acts as a facilitator of academic well-being, both directly and indirectly. In particular, GenAI has a strong impact on predicting satisfaction of students’ basic psychological needs and directly influencing academic well-being. Furthermore, BPN positively influences well-being outcomes. The mediation analysis results​ revealed that basic psychological needs partially mediate the relationships between GenAI and academic well-being, which aligns with a dual-pathway process. The modelhad a moderate​ explanatory power which highlights the importance of the relationships observed in the model. The findings of this study situate GenAI as more than just a technological solutionas it offers a psychological asset that empowers students to foster a sense of autonomy, competence, and relatedness, which further improve students’ academic well-being. This study extends SDT to the field of AI-aided learning, positioning GenAI as a situational predictor of psychological need fulfillment, and moves the research debate from technology adoption to learner well-being. The results provide practical guidance for creating human-centered learning spaces that can benefit from the use of GenAI to enhance student achievement and flourishing.