Supervisory versus ChatGPT’s Feedback in Doctoral Supervision: A Comparative Study at Mohamed I University in Oujda

Résumé

This study explores doctoral students’ comparative perceptions of AI-generated versus human feedback. It examines how doctoral students perceive ChatGPT-generated feedback compared to traditional supervisory feedback. Specifically, it evaluates feedback quality standards like clarity, relevance, accuracy, consistency, contextuality and comprehensiveness. It also investigates how these two different sources of feedback influence students’ satisfaction with their research practices and progress. Data were gathered through WhatsApp application by interviewing fifteen doctoral students who belong to the English departments of Mohamed I University in Oujda. The findings indicate that ChatGPT’s feedback is favoured for its clarity and immediacy while supervisory feedback is characterized by its relevance, contextuality, accuracy, and consistency. Supervisory feedback is perceived to be more engaging and contextually appropriate. ChatGPT’s feedback offers advantages in immediate accessibility and clarity but lacks the engagement and the nuanced contextual awareness of human supervision. The findings highlight the need for a balanced approach that integrates AI-driven feedback critically and ethically with traditional supervisory engagement.