Abstract
Objectives This study aimed to analyze medical students’ experiences with problem-based learning (PBL) in a non-face-to-face environment using text mining. Methods A total of 157 students’ open-ended responses regarding their experiences with problem-based learning in a non-face-to-face environment were collected and analyzed using term frequency and latent Dirichlet allocation (LDA)-based topic modeling. Results The result of the term-frequency analysis showed that keywords, such as discussion, learning, opinion, thought, process, and tutor, were prominent ones. The LDA-based topic modeling generated nine topics: physical comfort, technical discomfort, challenges of a lack of knowledge, improvement of problem-solving ability, psychological comfort, technical advantages, differences in students’ participation, experiences with tutors, and parallel schedule problems. Conclusions The results of this study can provide suggestions to enhance the quality of students’ experiences with PBL in a non-face-to-face environment.
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