Fostering generative AI-supported self-regulated learning (GenAI-SRL) in informal digital language learning through literacy and interactions: A two-stage PLS-SEM-ANN approach

Abstract Generative artificial intelligence (GenAI) enables foreign language learners to extend their learning beyond formal instruction and develop their autonomy. However, research has not adequately examined how learners regulate their learning with GenAI or how their GenAI literacy and multiple types of interactions influence their self-regulated learning (SRL) in GenAI-supported informal digital language learning settings. We address this gap by analyzing data from 343 Chinese university foreign language learners through partial least squares structural equation modeling (PLS-SEM) and artificial neural networks (ANN). PLS-SEM showed that awareness and evaluation significantly predicted GenAI-supported SRL (GenAI-SRL), whereas usage and ethics did not. Student–student, student–teacher, and student–GenAI interactions emerged as facilitators of GenAI-SRL. These three interaction types also significantly influenced most GenAI literacy dimensions, with three of them predicting awareness, usage, and evaluation, while only student–student and student–GenAI interactions significantly predicted ethics. Mediation analysis demonstrated that awareness and evaluation partially mediated the effects of student–student and student–teacher interactions on GenAI-SRL. The mediating pathways through student–GenAI interaction were not significant. ANN models identified student–student interaction as the strongest predictor of GenAI-SRL. These findings inform GenAI literacy development and the design of systems to support GenAI-SRL in informal learning contexts.