A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining

Relevance: 6/10 29 cited 2023 paper

This paper surveys deep learning techniques applied to educational data mining, covering knowledge tracing, student behavior detection, performance prediction, and personalized recommendation systems. It reviews existing deep learning methods and datasets used in educational contexts but does not present new benchmarks or evaluate cognitive offloading concerns.

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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knowledge tracing student modelcomputer-science