Deep Learning for Educational Data Science

This is a survey chapter that reviews how deep learning has been applied across educational data science, covering use cases like knowledge tracing, automated assessment, affect detection, and student behavior prediction in K-12, higher education, and online learning contexts. It provides an overview of deep learning architectures (CNNs, RNNs, etc.) and their applications in education rather than presenting a specific benchmark or evaluation.

With the ever-growing presence of deep artificial neural networks in every facet of modern life, a growing body of researchers in educational data science -- a field consisting of various interrelated research communities -- have turned their attention to leveraging these powerful algorithms within the domain of education. Use cases range from advanced knowledge tracing models that can leverage open-ended student essays or snippets of code to automatic affect and behavior detectors that can iden

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