Classifying and visualizing students' cognitive engagement in course readings

Eran Yogev; Kobi Gal; David Karger; Marc T. Facciotti; Michele Igo

doi:10.1145/3231644.3231648

Classifying and visualizing students' cognitive engagement in course readings

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

22 Scopus citations

Abstract

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 language	English
Title of host publication	Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450358866
DOIs	https://doi.org/10.1145/3231644.3231648
State	Published - 26 Jun 2018
Event	5th Annual ACM Conference on Learning at Scale, L at S 2018 - London, United Kingdom Duration: 26 Jun 2018 → 28 Jun 2018

Publication series

Name	Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018

Conference

Conference	5th Annual ACM Conference on Learning at Scale, L at S 2018
Country/Territory	United Kingdom
City	London
Period	26/06/18 → 28/06/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education

ASJC Scopus subject areas

Computer Networks and Communications
Education
Software
Computer Science Applications

Access to Document

10.1145/3231644.3231648

Cite this

Yogev, E., Gal, K., Karger, D., Facciotti, M. T., & Igo, M. (2018). Classifying and visualizing students' cognitive engagement in course readings. In Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018 Article 52 (Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3231644.3231648

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title = "Classifying and visualizing students' cognitive engagement in course readings",

abstract = "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.",

author = "Eran Yogev and Kobi Gal and David Karger and Facciotti, \{Marc T.\} and Michele Igo",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery. All rights reserved.; 5th Annual ACM Conference on Learning at Scale, L at S 2018 ; Conference date: 26-06-2018 Through 28-06-2018",

year = "2018",

month = jun,

day = "26",

doi = "10.1145/3231644.3231648",

language = "English",

series = "Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018",

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Yogev, E, Gal, K, Karger, D, Facciotti, MT & Igo, M 2018, Classifying and visualizing students' cognitive engagement in course readings. in Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018., 52, Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018, Association for Computing Machinery, Inc, 5th Annual ACM Conference on Learning at Scale, L at S 2018, London, United Kingdom, 26/06/18. https://doi.org/10.1145/3231644.3231648

Classifying and visualizing students' cognitive engagement in course readings. / Yogev, Eran; Gal, Kobi; Karger, David et al.
Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018. Association for Computing Machinery, Inc, 2018. 52 (Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Facciotti, Marc T.

AU - Igo, Michele

PY - 2018/6/26

Y1 - 2018/6/26

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AB - 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.

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M3 - Conference contribution

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T3 - Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018

BT - Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018

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Yogev E, Gal K, Karger D, Facciotti MT, Igo M. Classifying and visualizing students' cognitive engagement in course readings. In Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018. Association for Computing Machinery, Inc. 2018. 52. (Proceedings of the 5th Annual ACM Conference on Learning at Scale, L at S 2018). doi: 10.1145/3231644.3231648

Classifying and visualizing students' cognitive engagement in course readings

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

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