AI assisted, mentor-guided narrative review writing task for medical students, a novel educational strategy to enhance research and academic writing

Abstract

The integration of artificial intelligence (AI) tools into medical education presents new opportunities for enhancing students’ research skills and scientific writing. However, concerns remain about the potential for cognitive disengagement and the ethical use of AI when lacking appropriate educational supervision. This study aimed to evaluate a novel educational strategy combining structured AI assistance with mentor guidance to support narrative review writing among third-year medical students. A structured framework was implemented during the endocrine module, involving AI-assisted objective formulation, mentor-guided objective refinement, literature search and summarization, review drafting followed by AI-assisted rephrasing. Students worked in groups, each supervised by a trained mentor. A validated questionnaire assessed student perceptions across four domains: framework and guidelines, AI-generated objectives, skills developed and mentor role, and overall satisfaction. Descriptive statistics were performed and chi-square tests evaluated associations between perceptions and AI tool usage (ChatGPT vs. DeepSeek). Eighty-seven students completed the survey. Perceived improvement in research readiness was observed; confidence in literature searching rose from 29.8% to 69%, while 75.8% reported increased familiarity with PubMed/Google Scholar. Most students (80.5%) expressed satisfaction with the AI mentor hybrid approach, and 82.8% agreed it prepared them for future research. There were no significant differences in perceived outcomes between AI tools used. Mentor involvement was deemed essential by 69% of students, and a minority believed AI alone could replicate the same outcomes. Common challenges included limited access to articles and peer collaboration difficulties, while key learning outcomes included improved summarization and ethical AI use. This study supports the integration of AI tools within a structured, mentor-guided educational framework to enhance critical evaluation and scientific writing in medical education. Human oversight and mentorship drive skill development and minimize the risk of unmoderated AI use in academic settings.

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