Improving self-directed learning ability of medical students using the blended teaching method: a quasi-experimental study.

BACKGROUND: Self-directed learning (SDL) is one of the most important abilities for medical students in terms of their future clinical medical practice. During the blended teaching process, teachers can design a variety of learning activities to cultivate students' SDL abilities. This study aimed to assess the differences between the SDL abilities of medical students using blended and traditional didactic teaching. METHODS: This study included 239 medical students from eight administrative classes. The students were divided into two groups: (1) the experimental group (EG), which included 119 students from four administrative classes, and (2) the control group (CG), which included 120 students from the remaining four classes. From February to July 2022, blended teaching methods were applied to the EG group, and SDL abilities were assessed in comparison to the CG group receiving traditional didactic teaching methods. RESULTS: At the end of the semester, significant differences (p < 0.05) were observed between EG and CG in all six SDL ability factors. Furthermore, when k-means cluster analysis was used to analyze the learning behavior of students in the EG after classifying them as comprehensive, interactive, and passive types, significant differences were observed in all six Self-directed learning factors of students with the comprehensive type, whereas significant differences were observed in four factors (setting learning goals and plans, self-monitoring and regulation, information processing, and communication and cooperation) of students with the interactive type. For students with passive type, only one factor of SDL (information processing) showed significant improvement. There were on differences between comprehensive, interactive, and passive types of CG. CONCLUSION: The blended teaching approach is better than the conventional didactic teaching for cultivating clinical medical students' SDL abilities.