Enhancing Algerian Students’ Academic Writing Skills through Artificial Intelligence: A Paradigm Shift in EFL Pedagogy

The development of advanced academic writing skills remains a considerable challenge for students of English as a Foreign Language (EFL) in Algeria. Traditional pedagogical approaches frequently fail to deliver the individualized and iterative feedback required for sustained improvement. This study employs mixed-methods approach to examine how Artificial Intelligence (AI) can serve as a transformative tool in overcoming these challenges. A convergent mixed-methods design is used, combining quantitative analysis of students’ written productions with qualitative insights gathered through interviews and classroom observations. It identifies the recurrent writing difficulties encountered by Algerian EFL learners—such as grammatical inaccuracies, limited lexical range, syntactic inconsistencies, and difficulties in adhering to academic discourse conventions. It Further investigates the role of AI-powered technologies, including Automated Writing Evaluation (AWE) systems, intelligent tutoring platforms, and Large Language Models (LLMs) such as GPT-۴, in providing immediate and personalized feedback, supporting the drafting and revision process, and promoting learner autonomy. Findings indicate that AI-assisted feedback improves linguistic accuracy, strengthens revision practices, and increases students’ confidence as academic writers. While acknowledging potential drawbacks, including overreliance on technology and the risk of plagiarism, the paper advocates for an integrative pedagogical model in which AI functions as a complementary tool rather than a substitute for human instruction. It concludes that the strategic and ethical integration of AI in Algerian higher education can democratize access to high-quality writing support and foster a more effective, student-centered learning environment.

کلیدواژه ها:

Artificial Intelligence ، Academic Writing ، EFL Algerian Students ، Automated Feedback ، Educational Technology ، Mixed-methods Research