A dashboard model for automatic analytical insight generation in education based on big data visualization
Received: 2026-05-12
Published: 2026-06-06
Abstract
This article investigates the role of big data visualization methods and tools in improving data-driven decision-making in education. In digital learning environments, large amounts of heterogeneous data are generated from electronic journals, learning management systems, tests, attendance records, assignments, video lectures, and learner activity logs. If these data remain only in raw tables, their practical value decreases. Therefore, the article proposes a conceptual model consisting of data cleaning, grouping, KPI formation, interactive dashboard visualization, and automatic insight generation. The model integrates Power BI, Tableau, Python, SQL, and cloud-based data storage with educational analytics. The research substantiates that visual analytics can help identify learning dynamics, at-risk students, problematic topics across subjects, and practical recommendations for improving teaching strategies.
Keywords
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