TEACHER, AI, AND HYBRID FEEDBACK IN EFL WRITING: AN INTEGRATED THEORETICAL MODEL OF LEARNER PREFERENCES
DOI:
https://doi.org/10.46991/AFA/2026.22.1.110Keywords:
EFL writing feedback, AI in education, Hybrid Feedback Models, Feedback Literacy, Technology Acceptance Model (TAM)Abstract
This research examines the preferences of EFL university students in Algeria, regarding teacher, AI-generated, and hybrid feedback in academic writing. Based on a unified theoretical framework that integrates Sociocultural Theory (SCT), Feedback Literacy, and the Technology Acceptance Model (TAM), this study examines the influence of cognitive, affective, and technological factors on learners’ engagement with various feedback sources. Data were gathered from 226 EFL students using a validated self-report questionnaire and subsequently analyzed by exploratory factor analysis (EFA) and structural equation modeling (SEM). The results show that teacher feedback is the best predictor of how students like to get feedback overall. AI-generated feedback, on the other hand, is more of a supplement: students acknowledge its usefulness for grammatical accuracy and iterative revision, but its perceived usefulness alone does not significantly predict their preferences. Instead, behavioral engagement with AI tools proves to be a significant determinant, suggesting that interaction with AI, rather than cognitive evaluation, drives its acceptance. Mediation analysis further demonstrates that high-quality teacher feedback indirectly enhances feedback preference by fostering greater engagement with AI tools, supporting a synergistic relationship between human and automated feedback. The study contributes to the growing body of literature by offering an integrative, SEM-based comparison of teacher, AI, and hybrid feedback in an underexplored Algerian EFL context. The results underscore the pedagogical value of hybrid feedback models, where AI serves as a supportive tool rather than a replacement for teacher input. Implications for designing balanced, technology-enhanced writing instruction that integrates both human expertise and AI affordances are drawn.
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