Construction and Application Effect Evaluation of a University Educational Management Decision Support System Based on Big Data
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Abstract
To address the pain points in traditional university educational management, such as data silos and delayed feedback, which hinder timely curriculum adaptation in specialized engineering fields such as electromagnetic waves, antennas, and propagation, this paper constructs a University Educational Management Decision Support System (EM-DSS). Adopting interdisciplinary research methods, the study follows the technical route of “theoretical combing →demand investigation →system development → pilot verification →comprehensive evaluation”. It designs a four-layer architecture, integrates stream processing technology, develops core models including academic early warning, and covers four major management scenarios. A 6-month pilot was conducted in two colleges of a provincial university, and the application effect was tested through a three-level evaluation index system. The results show that the system achieved a comprehensive score of 0.78, with decision-making time shortened by 30%, academic early warning accuracy reaching 85%, and equipment utilization rate increased by 25%. This system realizes the transformation of educational management from experience-driven to data-driven, thereby improving the alignment between academic programs, laboratory resources, and technical training demands in engineering disciplines involving electromagnetic theory, antenna design, propagation measurement, and related experimental courses, while providing a replicable technical solution and practical model for the digital governance of universities.
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