Generative AI feedback use and deep cognitive engagement in university EFL writing: a mixed-methods study of autonomy, self-regulated learning, and AI literacy
Year: 2026
Type: article
Abstract: Generative artificial intelligence (AI) is increasingly used to obtain feedback in English as a foreign language (EFL) writing, but its educational significance depends on how learners interpret and regulate that feedback. Grounded in Self-Determination Theory and self-regulated learning theory, this explanatory sequential mixed-methods study examined an AI-supported motivated self-regulated learning framework using a cross-sectional survey of 486 university EFL students and follow-up interviews with 20 students. Structural equation modeling identified a positive direct association between reported AI feedback use and deep cognitive engagement, together with a positive indirect statistical association through learning autonomy and self-regulated learning. The AI feedback use–autonomy association was stronger at higher modeled levels of AI literacy. Interview accounts described feedback-related control, critical evaluation, and awareness of AI limitations, alongside contrasting experiences of rapid polishing and careful evaluation despite limited familiarity with AI. Integration of the two strands highlighted variation in how learners evaluated and incorporated feedback. These self-report findings do not establish temporal ordering or causal effects. They identify learner agency, strategic regulation, and critical evaluation as relevant considerations for future investigations of AI-supported writing.
Source: Frontiers in Psychology
Authors: Hongyi He, Dan Wu, Boya Zhang, Zhi Chen
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225790339