An AI-interpretable multidimensional intelligence-driven framework for student performance prediction using local LLM-based narrative reasoning
Predicting student performance has become a vital objective in educational data mining, however existing models remain limited by limited feature sets, opaque decision processes, and the absence of real-time, context-aware interpretative intelligence. This study presents a novel hybrid Artificial Intelligence (AI) arch...