Evaluating the Use of Learning Analytics in Formative Assessment
DOI:
https://doi.org/10.59944/postaxial.v3i4.540Keywords:
Learning analytics, formative assessment, data-driven instruction, teacher decision-making, student engagementAbstract
This study explores the role of learning analytics in enhancing formative assessment practices within contemporary educational settings. The primary objective is to evaluate how data-driven insights from learning analytics contribute to improving feedback quality, teacher decision-making, and student engagement. Using a mixed-methods approach, the research integrates quantitative data from learning management systems with qualitative interviews from teachers and students. The findings reveal that learning analytics fosters more personalized, continuous, and responsive assessment practices. Teachers benefit from real-time data that enable targeted interventions and adaptive instruction, while students experience increased motivation and self-regulation through visual feedback of their learning progress. Nevertheless, the study highlights key challenges, including teachers’ limited data literacy, institutional readiness, and ethical considerations regarding data privacy. Overall, the integration of learning analytics into formative assessment represents a paradigm shift from static evaluation to a dynamic, learner-centered process. The study concludes that effective implementation requires strong institutional support, professional training, and ethical data governance to ensure sustainable and equitable educational improvement.
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