Biography
Dr. Abdellatif Belkadi is a Professor of English in the Faculty of Legal and Political Sciences at Hassan First University, Settat, Morocco. He holds a PhD in Linguistics. His research examines the psychological dimensions of language learning, including learner motivation and factors shaping language acquisition. He has participated in international collaborative research, including the IPFC project at Université Grenoble Alpes and the IPCE–IPAC project at Université de Lille. His recent academic interests extend to the relationship between artificial intelligence and human learning.
Conference contributions 1
WHEN AI OVERCORRECTS:
A theoretical examination of learner self-efficacy in academic writing
The growing integration of AI-powered writing tools in higher education has introduced new and underexplored challenges for academic writing development. While these tools are considered as valuable feedback resources capable of enhancing students' writing quality, this presentation argues that their systematic tendency to suggest modifications to already correct and academically appropriate writing constitutes a form of overcorrection with serious pedagogical consequences. Unlike traditional corrective feedback, which targets genuine errors, AI tools such as ChatGPT and Gemini consistently propose alternative vocabulary, restructured sentences, and stylistic changes regardless of whether the original writing meets academic standards. This pattern of unnecessary intervention risks sending students a misleading message — that their language choices are perpetually insufficient. Drawing on Bandura's (1997) self-efficacy theory, Truscott's (1996) critique of written error correction, Hyland's (2002) academic voice framework, and Holec's (1981) learner autonomy theory, this presentation theorizes that persistent AI suggestion creates a false impression of inadequacy in students, which leads them to distrust their own linguistic judgments and undermine their confidence as academic writers. Constant AI intervention further erodes learner autonomy and silences the development of an authentic scholarly voice, carrying direct negative consequences for long-term academic writing performance. This presentation calls for raising critical awareness among teachers and students regarding the overcorrective nature of AI feedback tools, advocating for a balanced and reflective approach that encourages students to trust their own competence rather than developing an uncritical over-reliance on AI-generated suggestions.