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Investigating the dimensions of students’ privacy concern in the collection, use, and sharing of data for learning analytics

Korir, Maina; Slade, Sharon; Holmes, Wayne; Héliot, Yingfei; Rienties, Bart; (2023) Investigating the dimensions of students’ privacy concern in the collection, use, and sharing of data for learning analytics. Computers in Human Behavior Reports , 9 , Article 100262. 10.1016/j.chbr.2022.100262. Green open access

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Abstract

The datafication of learning has created vast amounts of digital data which may contribute to enhancing teaching and learning. While researchers have successfully used learning analytics, for instance, to improve student retention and learning design, the topic of privacy in learning analytics from students' perspectives requires further investigation. Specifically, there are mixed results in the literature as to whether students are concerned about privacy in learning analytics. Understanding students' privacy concern, or lack of privacy concern, can contribute to successful implementation of learning analytics applications in higher education institutions. This paper reports on a study carried out to understand whether students are concerned about the collection, use, and sharing of their data for learning analytics, and what contributes to their perspectives. Students in a laboratory session (n = 111) were shown vignettes describing data use in a university and an e-commerce company. The aim was to determine students' concern about their data being collected, used, and shared with third parties, and whether their concern differed between the two contexts. Students' general privacy concerns and behaviours were also examined and compared to their privacy concern specific to learning analytics. We found that students in the study were more comfortable with the collection, use, and sharing of their data in the university context than in the e-commerce context. Furthermore, these students were more concerned about their data being shared with third parties in the e-commerce context than in the university context. Thus, the study findings contribute to deepening our understanding about what raises students’ privacy concern in the collection, use and sharing of their data for learning analytics. We discuss the implications of these findings for research on and the practice of ethical learning analytics.

Type: Article
Title: Investigating the dimensions of students’ privacy concern in the collection, use, and sharing of data for learning analytics
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.chbr.2022.100262
Publisher version: https://doi.org/10.1016/j.chbr.2022.100262
Language: English
Additional information: Copyright © 2022. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Privacy concern, Contextual integrity, Learning analytics
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media
URI: https://discovery.ucl.ac.uk/id/eprint/10162083
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