The effectiveness of microlearning on student engagement and learning outcomes in educational statistics courses - Jainuri, Muhammad (Jurnal Pengembangan Pembelajaran Matematika (JPPM), 2025)
The Educational Statistics course is often seen as challenging for students, leading to low engagement and learning outcomes. This study aims to analyze the effectiveness of microlearning implementation to optimize student engagement and learning outcomes in the Education Statistics course, identify changes in the dimension of student engagement through the implementation of microlearning, analyze the relationship between student engagement and learning outcomes, and develop an effective microlearning implementation model in the Education Statistics course. Using a quasi-experimental design with a pretest-posttest control group, the study involved 66 students divided into an experimental group (n = 32) who received microlearning-based learning and a control group (n = 34) using traditional methods. Data were collected using the Student Engagement Questionnaire (SEQ), pretest-posttest statistical learning outcomes, digital activity log analysis, and semi-structured interviews. The results showed a significant increase in the engagement rate of the experimental group compared to the control (t = 4.87, p < 0.001) with a large effect size (Cohen's d = 0.79). MANOVA's analysis showed a significant increase in four dimensions of engagement: behavioral (F = 18.34, p < 0.001), cognitive (F = 21.56, p < 0.001), emotional (F = 15.89, p < 0.001), and social engagement (F = 12.45, p < 0.001). The implementation of microlearning resulted in significant improvements in learning outcomes (t = 5.23, p < 0.001) and statistical knowledge retention (F = 19.76, p < 0.001). Thematic analysis of qualitative data identified five factors that support the effectiveness of microlearning: (1) flexibility of content access, (2) visualization of complex concepts, (3) immediacy of feedback, (4) personalization of learning, and (5) integrated collaboration. This study recommends a tiered microlearning implementation model for educational statistics courses that can be adapted for various higher education contexts.