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

Korir, Maina (2022) Investigating the dimensions of students' privacy concern in the collection, use and sharing of data for learning analytics. Computers in Human Behavior Reports, 9. ISSN 2451-9588

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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.

Item Type: Article
Uncontrolled Keywords: privacy concern, contextual integrity, learning analytics
Subjects: L Education > LC Special aspects of education
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Health & Science > Department of Science & Technology
Depositing User: Maina Korir
Date Deposited: 24 Jan 2023 16:00
Last Modified: 24 Jan 2023 16:00
URI: https://oars.uos.ac.uk/id/eprint/2919

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