EXPERIENCES OF EFL INSTRUCTORS AT UNIVERSITY OF TABUK WITH AI-GENERATED FEEDBACK THEY ENCOUNTER ON STUDENT ACADEMIC WRITING

Abstract

The purpose of this study was to explore the experiences of EFL writing instructors at the University of Tabuk’s Language Institute with AI-generated feedback they encounter on student academic writing. Guided by Teacher Cognition (Borg, 2003, 2006, 2015) as the primary theoretical framework, with TPACK (Mishra & Koehler, 2006) and CALL as complementary lenses, the study employed a basic interpretive qualitative design. Semi-structured interviews were conducted with eight EFL instructors representing six nationalities, and data were analyzed using Braun and Clarke’s (2006) six-phase thematic analysis. In vivo coding supplemented by descriptive coding (Saldaña, 2021) generated 153 codes organized into five themes: (a) Encountering AI Through Student Writing, (b) Interpreting and Evaluating AI Feedback, (c) Mediating AI Feedback for Students, (d) Navigating the Tension Between AI’s Potential and the Learning Process, and (e) Evolving Beliefs About AI in Writing Instruction. The central finding was that instructors did not simply adopt or reject AI but navigated continuously between its benefits and the risks it posed to writing instruction. Teachers served as essential mediators between AI output and student learning, translating, simplifying, and filtering feedback based on professional knowledge. Their beliefs evolved from initial skepticism toward cautious acceptance, shaped by classroom experience rather than formal training. The findings carry implications for EFL instructors, teacher preparation programs, institutional policy, and AI tool development, highlighting the need for professional development that strengthens teacher judgment rather than replacing it.