ArticlePakistan journal of medical sciences2026
Impact of ChatGPT-assisted personalized learning on teaching acute abdomen to undergraduate medical students: A randomized crossover study.
Article in Pakistan journal of medical sciences, 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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Abstract
Background &Objective: The application of Artificial Intelligence (AI) in medical education has emerged as a promising avenue for personalized learning experiences to the individual needs of medical students. This study investigated the impact of AI-driven personalized learning pathways on the academic performance of medical students in acute abdomen topic, comparing against traditional learning method. Methodology: This study used a randomized controlled crossover trial conducted from February 2024 to July 2024 among fourth year one hundred undergraduate medical students at Islamic International Medical College, Riphah International University, Pakistan. In this study, students enrolled in a general surgery course were randomly assigned to experimental group and control group following a pre-test. The experimental group engaged with AI-driven personalized learning pathways, powered by ChatGPT-4, the control group utilized conventional educational resources. Both groups completed a post-test to assess the effects of their respective learning interventions. Statistical analyses, including descriptive statistics, independent-samples t-tests and paired-samples t-tests were conducted using SPSS. Results: The pre-test scores of the experimental (M = 17.12, SD = 6.99) and control groups (M = 18.64, SD = 6.91) did not differ significantly (p = 0.277). Post-intervention, the experimental group showed a statistically significant improvement (M = 22.8, SD = 5.11) compared to the control group (M = 19.24, SD = 7.11), with a p-value of .005 and a moderate effect size (Cohen's d = 0.58). This suggests that AI-driven personalized learning pathways had a positive and measurable impact on the students' academic performance in the experimental group. Conclusion: AI-driven personalized learning pathways can enhance the academic performance of medical students, particularly in subject of surgery. Future research should explore the long-term effects of personalized AI-powered educational interventions.
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