The Interplay of Personal Learning Experience, Social Emotional Learning and Autonomy in Promoting Well-Being in AI-Assisted Language Learning: A Self-Determination Theory Approach
EUROPEAN JOURNAL OF EDUCATION, cilt.60, sa.4, ss.1-12, 2025 (SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 60 Sayı: 4
- Basım Tarihi: 2025
- Doi Numarası: 10.1111/ejed.70354
- Dergi Adı: EUROPEAN JOURNAL OF EDUCATION
- Derginin Tarandığı İndeksler: Scopus, Social Sciences Citation Index (SSCI), IBZ Online, Education Abstracts, Educational research abstracts (ERA), ERIC (Education Resources Information Center), MLA - Modern Language Association Database, Public Affairs Index
- Sayfa Sayıları: ss.1-12
- İstanbul Medipol Üniversitesi Adresli: Evet
Özet
Artificial intelligence has become an important force in higher education, especially in language learning. Existing researchhas mainly focussed on its influence on academic performance, with limited attention to psychological outcomes, so this studyaimed to examine the effects of personal learning experience, social emotional learning and student autonomy on student well-being within the framework of Self-Determination Theory. The study adopted a quantitative design and developed a path modelto test five hypotheses. A structured questionnaire was distributed to 508 Chinese university students. Data were collectedthrough self-report surveys and analysed using SPSS 27.0 and AMOS 26.0. The results show that personal learning experiencepositively influences both autonomy and well-being, while social emotional learning significantly predicts autonomy and well-being. Student autonomy not only directly enhances well-being but also mediates the effects of personal learning experience andsocial emotional learning on well-being. These findings confirm the central claims of self-determination theory in AI-assistedlearning and demonstrate that technology can support both academic achievement and psychological flourishing. The studyenriched theoretical understanding by integrating direct and mediating effects into one model and provides practical insights forthe design of AI-based tools that foster autonomy, emotional growth and student well-being