AI And Indigenous Language Arts: A Quadruple Helix Model for Nigeria

This study explores the effectiveness of AI-powered personalized feedback on writing quality among English language learners (ELLs) at a Nigerian university, addressing challenges in delivering timely feedback due to large class sizes and limited resources. Fifty undergraduate students were divided into two groups: one received feedback from an AI-enabled assistant integrated into the learning management system, while the other received traditional teacher feedback. Pretest and posttest essays were evaluated using an analytic rubric assessing grammar, vocabulary, coherence, and overall writing quality. Results indicated significant improvements in both groups, with the AI group demonstrating greater gains in grammar and coherence. Qualitative feedback highlighted the AI's timeliness and clarity, though concerns about overcorrection and maintaining student voice were noted. The findings suggest that AI feedback can effectively complement traditional teaching methods by enhancing learner autonomy and revision quality when implemented responsibly. The study concludes with recommendations for pedagogical practices, institutional policy, and the ethical integration of AI in education.