During the COVID-19 pandemic, medical schools in low- and middle-income countries (LMICs) have faced numerous challenges in adopting online learning management systems (LMS). To address this, our medical school designed and implemented a tailored LMS for its students. This study aims to evaluate how medical students accept and benefit from the LMS, as well as to explore the factors that influence their engagement with online learning. This study employed a mixed-methods design, combining an online questionnaire with semi-structured interviews conducted virtually among first-year medical students at a Thai medical school. Data from the platform’s monitoring system and the questionnaire were analyzed using descriptive statistics and binary logistic regression. Out of 283 students, 157 responded, resulting in a 55.5% response rate. Most respondents highlighted the benefits of the LMS and reported a high level of satisfaction with their learning experience. Analysis using logistic regression revealed that both the quality of the course content (adjusted odds ratio [AOR] = 2.43; 95% CI: 1.11–5.31) and the perceived usefulness of the platform (AOR = 2.75; 95% CI: 1.02–7.39) were significant predictors of students’ acceptance of online learning. In contrast, no correlation was observed between test performance and the amount of time students spent engaging with the course. Although evidence on the effectiveness of learning management systems (LMS) in medical schools within low- and middle-income countries (LMICs) remains limited, our findings suggest that a customized LMS was well-received by students, perceived as useful, user-friendly, and effective. Acceptance of online learning was influenced by both the perceived usefulness of the platform and the quality of its content. These results indicate that medical schools in LMICs can successfully develop tailored LMS solutions to address the specific needs of their students and faculty. As this study was conducted at a single institution, further research on a larger scale is necessary to confirm the generalizability of these findings.
