Measuring Students’ Engagement with Digital Interactive Textbooks by Analyzing Clickstream Data

Authors

  • Breanne Crockett University of Toledo

DOI:

https://doi.org/10.1609/aaai.v36i11.21702

Keywords:

Data Mining, Machine Learning, Statistical Learning

Abstract

This paper provides an overview of my contributions to a project to measure and predict student’s mental workload when using digital interactive textbooks. The current work focuses on analysis of clickstream data from the textbook in search of viewing patterns among students. It was found that students typically fit one of three viewing patterns. These patterns can be used in further research to inform creation of new interactive texts for improved student success.

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Published

2022-06-28

How to Cite

Crockett, B. (2022). Measuring Students’ Engagement with Digital Interactive Textbooks by Analyzing Clickstream Data. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13132-13133. https://doi.org/10.1609/aaai.v36i11.21702