A HYBRID MACHINE LEARNING FRAMEWORK FOR INTELLIGENT DECISION SUPPORT IN EDUCATION
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The increasing use of digital platforms in higher education has led to the continuous generation of large volumes of student-related academic data. Effectively utilizing this data has become essential for improving academic performance monitoring, student retention, and institutional planning. Intelligent Decision Support Systems (IDSS) provide a systematic approach for analyzing educational data and supporting informed academic decision-making. However, many existing decision support systems rely on traditional analytical techniques or single machine learning models, which often struggle to manage the complexity, diversity, and uncertainty inherent in real-world educational datasets.
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S.P.Maske, (2026). A Hybrid Machine Learning Framework for Intelligent Decision Support in Education. International Journal of Science, Strategic Management and Technology, 02(03). https://doi.org/10.55041/ijsmt.v2i3.278
S.P.Maske, . "A Hybrid Machine Learning Framework for Intelligent Decision Support in Education." International Journal of Science, Strategic Management and Technology, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i3.278.
S.P.Maske, . "A Hybrid Machine Learning Framework for Intelligent Decision Support in Education." International Journal of Science, Strategic Management and Technology 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i3.278.
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