Impact of excel-based learning analytics reports feedback on examination performance in obstetrics and gynecology: experience from a resource-limited setting

Competency-specific feedback is essential in competency-based medical education to guide self-regulated learning. In resource-limited settings, feedback is often limited to the total number of correct answers. This study aims to evaluate the impact of midterm excel-based learning analytics report (ExLAR)-based feedback during the Obstetrics and Gynecology (OB-GYN) module 1. A quasi-experimental study was conducted at the University of Medicine and Pharmacy at Ho Chi Minh City (October 2023–October 2024) with 356 fourth-year students. The intervention group (n=178) received ExLAR-based feedback after the midterm theory examination (MTE), while the control group (n=178) received only the total correct answers. Outcomes included improvement in final theory examination (FTE) performance, adherence to study plans, and students’ perceived usefulness of ExLAR. Data was analyzed using t-tests, Chi-square trend test, multivariable logistic regression, ordinal logistic regression, and variance inflation factor (VIF). Proportional odds assessed via the Brant test. At baseline MTE, mean correct answers were 37.40±0.56 in the intervention group and 35.53±0.53 in the control group (p<0.001). The intervention group showed significant improvement in FTE performance (2.2±0.4 vs 0.32±0.38, p<0.001). Intervention participation independently predicted improvement in FTE performance after adjusting for batch, baseline MTE, age, and gender. Study plan adherence tended to improve in FTE performance, but not significantly (p=0.414). Most students found ExLAR helpful, but only perceived usefulness for competency-specific performance was significantly associated with improvement in FTE performance (p=0.048). In our resource-limited setting, ExLAR was a practical tool for competency-based feedback that improved learning outcomes.