ArticleBMC medical education2026
Implementation and evaluation of customized artificial intelligence personal tutor (chat GPT physiology companion) for medical students in the reproduction module.
Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Artificial Intelligence (AI) has emerged as a transformative tool in education, offering personalized learning, adaptive assessments, and real-time feedback. This study investigates the impact of a customized AI-powered tutoring system—GPT Reproductive Physiology Companion—on student satisfaction and academic performance among third-year medical students enrolled in the Reproduction module. The study was conducted at the Faculty of Medicine, Dar Al Uloom University, Riyadh. The study employed a quasi-experimental mixed-methods design. Forty-seven pre-clinical students with no prior exposure to AI-assisted instruction participated during the 2024–2025 academic year. The intervention involved four structured stages: tool development, implementation, intervention, and data collection. Evaluation metrics included academic performance and student feedback. Results indicated high AI usage, with over half the students interacting with the tool multiple times weekly. Students found the GPT responses well-aligned with course content and beneficial for enhancing conceptual understanding, formative assessment, and critical thinking. Those using the tool more frequently reported higher satisfaction. Despite the positive perceptions, academic performance did not significantly differ from outcomes in other traditionally taught modules like Neuroscience and GIT. Nonetheless, no adverse effect was observed, supporting AI integration as a safe supplemental resource.ConclusionWhile the AI tool did not significantly enhance summative exam scores, it fostered positive learning experiences, supporting self-directed study and curriculum alignment. These findings highlight AI’s potential in content-intensive subjects and advocate for its thoughtful integration into medical education, with future enhancements focused on assessment alignment, expanded content, and ethical oversight.
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