AI-Generated Practice for Textbooks: An Exploratory Analysis From the Classroom


Artificial intelligence has made it possible to generate high quality formative practice questions for use in higher education digital textbooks. Adding these automatically generated questions as a study feature for textbooks in an e-reader platform made it possible to democratize the learn-by-doing approach known to increase learning. Faculty in three different courses at a major public university in the United States assigned the automatically generated practice as a completion homework assignment with the textbook reading. In this paper, we investigate four automatically generated question types as well as an AG multi-question scaffolded tutorial using data from these three courses to better understand two research questions: how did these questions perform for students, and how did students choose to use them during their course? Additionally, survey data was collected to identify how students generally perceived the AG practice. Artificial intelligence can lead to unprecedented advances for teaching and learning technologies, but it is necessary to investigate how these tools perform for students in real-world contexts. The analyses from these classroom examples provide insights into how artificial intelligence can further benefit students in their everyday learning contexts.

Author Information
Rachel Van Campenhout, VitalSource, United States
Michelle Clark, VitalSource, United States
Benny G. Johnson, VitalSource, United States

Paper Information
Conference: IICE2024
Stream: Design

This paper is part of the IICE2024 Conference Proceedings (View)
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To cite this article:
Campenhout R., Clark M., & Johnson B. (2024) AI-Generated Practice for Textbooks: An Exploratory Analysis From the Classroom ISSN: 2189-1036 – The IAFOR International Conference on Education – Hawaii 2024 Official Conference Proceedings
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Posted by James Alexander Gordon