Classifying and visualizing students' cognitive engagement in course readings

Eran Yogev, Yakov Gal, David Karger, Marc T. Facciotti, Michele Igo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Reading material has been part of course teaching for centuries, but until recently students' engagement with that reading, and its effect on their learning, has been difficult for teachers to assess. In this article, we explore the idea of examining cognitive engagement---a measure of how deeply a student is thinking about course material, which has been shown to correlate with learning gains---as it varies over different sections of the course reading material. We show that a combination of automatic classification and visualization of cognitive engagement anchored in the text can give teachers---and not only researchers---valuable insight into their students' thinking, suggesting ways to modify their lectures and their course readings to improve learning. We demonstrate this approach with analyzing students' comments in two different courses (Physics and Biology) using the Nota Bene annotation platform.
Original languageEnglish
Title of host publicationProceedings of the Fifth Annual ACM Conference on Learning at Scale
Place of PublicationLondon, United Kingdom
Number of pages10
ISBN (Print)978-1-4503-5886-6
Publication statusPublished - 26 Jun 2018
EventFifth Annual ACM Conference on Learning at Scale - London, United Kingdom
Duration: 26 Jun 201828 Jun 2018


ConferenceFifth Annual ACM Conference on Learning at Scale
Abbreviated titleL@S '18
Country/TerritoryUnited Kingdom
Internet address


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