Deep Learning for Educational Data Science

• URL: http://arxiv.org/abs/2404.19675v1
• Date: Fri, 12 Apr 2024 19:17:14 GMT
• Title: Deep Learning for Educational Data Science
• Authors: Juan D. Pinto, Luc Paquette,
• Abstract summary: 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. This chapter provides a brief introduction to deep learning, describes some of its advantages and limitations, presents a survey of its many uses in education, and discusses how it may further come to shape the field of educational data science.
• Score: 0.6138671548064356
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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 identify when a student is frustrated or aimlessly trying to solve problems unproductively -- and much more. This chapter provides a brief introduction to deep learning, describes some of its advantages and limitations, presents a survey of its many uses in education, and discusses how it may further come to shape the field of educational data science.

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