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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Theoretically, this study contributes to the emerging literature on data-driven academic resource management and the application of artificial intelligence in higher education operations. Practically, it offers a replicable analytical framework for institutions seeking to forecast servicing code demand and align lecturer allocation strategies with real time dynamics and cost optimization goals.…”
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