Related Experiment Video
Updated: Aug 31, 2026
E-Patient Counseling Trial (E-PACO): Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
Impact of ChatGPT-assisted personalized learning on teaching acute abdomen to undergraduate medical students: A
Maria Ilyas1, Rehan Ahmed Khan2, Rahila Yasmeen3
1Maria Ilyas, MHPE Senior Lecturer Pharmacology, Watim Medical and Dental College Rawat, Rawalpindi, Pakistan.
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.
