Impact of ChatGPT-assisted personalized learning on teaching acute abdomen to undergraduate medical students: A randomized crossover study

作者：Maria Ilyas, Rehan Ahmed Khan, Rahila Yasmeen, Zainab Kamal, Noor Ul Ain · 发表于：Pakistan Journal of Medical Sciences · 年份：2026 · DOI：10.12669/pjms.42.8.14827 · 研究领域：Artificial Intelligence in Healthcare and Education、Online Learning and Analytics、E-Learning and COVID-19

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 c...