A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining

This is a comprehensive survey paper that reviews deep learning techniques applied to educational data mining across four scenarios: knowledge tracing, student behavior detection, performance prediction, and personalized recommendation. It synthesizes existing research rather than presenting a new benchmark or evaluation tool.

Educational Data Mining (EDM) has emerged as a vital field of research, which harnesses the power of computational techniques to analyze educational data. With the increasing complexity and diversity of academic data, Deep Learning techniques have shown significant advantages in addressing the challenges associated with analyzing and modeling this data. Existing studies are scattered across various domains, making it challenging to gain a comprehensive understanding of how Deep Learning techniqu

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