Analysis of the Effectiveness of Learning Analytics-Based Formative Evaluation in Improving Secondary School Students’ Learning Engagement
DOI:
https://doi.org/10.58222/jpd.v4i2.76Keywords:
Formative Evaluation, Learning Analytics, Learning Engagement, Adaptive Feedback, Educational Technology, Middle School, Digital LearningAbstract
Student learning engagement is a key predictor of academic success, yet conventional formative evaluation often fails to provide timely and personalized feedback to encourage optimal engagement. This study analyzes the effectiveness of learning analytics-based formative evaluation in improving middle school students' learning engagement. The research method uses a quasi-experimental approach with a pretest-posttest control group design involving 240 eighth-grade students from four middle schools in Bengkulu City. The experimental group (120 students) received learning analytics-based formative evaluation using a digital platform integrating real-time analytics, adaptive feedback, and learning progress visualization, while the control group (120 students) received conventional formative evaluation. Data were collected through learning engagement questionnaires, learning activity observations, digital platform log analysis, and learning achievement tests over a 16-week period. Research findings show that the experimental group experienced significantly higher increases in learning engagement scores compared to the control group: cognitive engagement increased by 43.7 percent versus 18.3 percent, emotional engagement by 38.4 percent versus 15.7 percent, and behavioral engagement by 41.2 percent versus 19.4 percent. Learning analytics data analysis shows that students in the experimental group accessed learning materials 3.4 times more frequently, spent 2.8 times longer studying, and completed assignments with a completion rate of 89.7 percent compared to 67.3 percent in the control group. Learning outcomes for experimental group students increased by an average of 24.6 points compared to 12.3 points in the control group. Key effectiveness factors include: immediate and specific feedback, motivating progress visualization, data-based learning path personalization, and student involvement in metacognitive reflection. This research contributes to developing a technology-based formative evaluation model that can enhance student engagement and learning outcomes in the digital era.
Keywords: Formative Evaluation, Learning Analytics, Learning Engagement, Adaptive Feedback, Educational Technology, Middle School, Digital Learning
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