Generative artificial intelligence and academic well-being mediated by basic psychological needs in a self-determination theory framework
Year: 2026
Type: article
Study design: Observational Study
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 undergraduates 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.
Source: Discover Artificial Intelligence
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,590
OpenAlex ID: W7225332394