Analysis of Self-Regulated Learning and Learning Style Preference of First-Year Medical Students for E-Learning Optimization

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First-year medical students adapt to hybrid education, combining online and offline learning in the new standard era. The various features of e-learning need to accommodate students' skills in self-regulated learning and their preferences, such as learning style preference. Therefore, this research aims to analyze first-year medical students' self-regulated learning skills and learning style preferences in online learning to identify e-learning optimization needs that can facilitate their adaptation to medical education. A descriptive quantitative and qualitative narrative method was conducted through document analysis. The Online Self-Regulated Learning Questions (OSRLQs) were used to obtain quantitative descriptive data on students' self-regulated learning skills, and the learning style preference questionnaire was used to obtain data on first-year medical students. The results showed that first-year medical students require optimization in four domains of the self-regulated learning skills in online learning, including task strategies, time management, help-seeking, and self-evaluation. The analysis yielded 19 categories with three main learning style preferences: a combination of visual and auditory and a combination of visual, auditory, and kinesthetic. This analysis recommends optimizing several e-learning features to improve first-year medical students' self-regulated learning skills and learning style preferences.