Kazakistan ve Özbekistan'da Yapay Zeka Aracılı Gayri Resmi Dijital İngilizce Öğrenimi Motivasyon ve Dayanıklılık ile İlişkili

Özet (abstract)

The rapid development of generative artificial intelligence (AI) has reshaped informal digital learning, yet most research has focused on well-resourced contexts and often treats AI-mediated learning as a standalone phenomenon. This leaves a limited understanding of how learners in underrepresented regions adopt AI-supported practices and how such practices are connected to established forms of informal learning. Addressing this gap requires examining both the developmental relationship between IDLE and AI-IDLE and the psychological factors that shape learners’ participation. This study investigates how L2 motivational selves and learner resilience are associated with learners’ participation in IDLE and AI-mediated informal learning across two Central Asian contexts. Drawing on proactive language learning theory, the study employed a cross-sectional survey design with 997 university students from Kazakhstan and Uzbekistan. A structural equation modelling (SEM) approach was used to examine the relationships among ideal and ought-to L2 selves, learner resilience, IDLE, and AI-IDLE, alongside a multigroup analysis to test cross-context variation. The findings showed that L2 motivational selves significantly predict resilience and IDLE, while resilience supports AI-mediated learning primarily through indirect pathways. IDLE emerged as the strongest predictor of AI-IDLE, suggesting a close connection between established informal digital learning practices and learners’ use of AI-supported tools. Although the overall model was broadly stable, several relationships varied across contexts, highlighting the role of sociocultural and institutional conditions in shaping AI-mediated informal learning in Central Asian contexts.

Yazarların özeti; kaynağından alınmıştır. Learning and Motivation, 2026 · DOI ↗