Student and Staff Perspectives on the Use of Big Data in the Tertiary Education Sector: A Scoping Review and Reflection on the Ethical Issues

Braunack-Mayer, Annette J.; Street, Jackie M.; Tooher, Rebecca; Feng, Xiaolin; Scharling-Gamba, Katrine

doi:10.3102/0034654320960213

Cited by 41Online Learning and AnalyticsData Privacy and CybersecurityEducational and Technological Research

Student and Staff Perspectives on the Use of Big Data in the Tertiary Education Sector: A Scoping Review and Reflection on the Ethical Issues

Braunack-Mayer, Annette J., Street, Jackie M., Tooher, Rebecca, Feng, Xiaolin, Scharling-Gamba, Katrine·2020·Review of Educational Research

DOI 10.3102/0034654320960213

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Abstract

While universities routinely use student data to monitor and predict student performance, there has been limited engagement with student and staff views, social and ethical issues, policy development, and ethical guidance. We reviewed peer-reviewed and grey-literature articles of 2007 to 2018 describing the perspectives of staff and students in tertiary education on the use of student-generated data in data analytics, including learning analytics. We used an ethics framework to categorize the findings. There was considerable variation but generally low awareness and understanding amongst students and staff about the nature and extent of data collection, data analytics, and use of predictive analytics. Staff and students identified potential benefits but also expressed concerns about misinterpretation of data, constant surveillance, poor transparency, inadequate support, and potential to impede active learning. This review supports the contention that consideration of ethical issues has failed to keep pace with the development of predictive analytics in the tertiary sector.

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Previous reviews have criticised LA interventions for lack of methodological quality, such as tending to be small in scale.
“Previous reviews have also criticised LA interventions for lack of methodological quality (e.g., Larrabee Sønderlund et al., 2019), such as tending to be small in scale (e.g., Braunack-Mayer et al., 2020)”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Braunack-Mayer et al., 2020

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Authors: Braunack-Mayer, A. J., Street, J. M., Tooher, R., Feng, X., & Scharling-Gamba, K.
Affiliations: University of Wollongong (AU)
The University of Adelaide (AU)
ORCID: Braunack-Mayer, Annette J.
Street, Jackie M.
Scharling-Gamba, Katrine
Venue: Review of Educational Research
Publisher: American Educational Research Association (AERA)
Published: 2020-09-23
Volume: 90
Issue: 6
Pages: 788-823
ISSN: 0034-6543 (ISSN-L)
1935-1046
DOI: 10.3102/0034654320960213
OpenAlex: W3088198127
Cited by: 41
References: 84
Citations by year: 2026: 7 · 2025: 9 · 2024: 7 · 2023: 9 · 2022: 5 · 2021: 4
FWCI: 4.11
Type: journal article
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Review of Educational Research (publishedVersion)
Research Online (University of Wollongong) (submittedVersion)
Funders: University of Wollongong (Faculty Seed Grant)
University of Adelaide (IRF0006003759)
Topics: Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Social Sciences › Law › Data Privacy and Cybersecurity
Physical Sciences › Computer Science › Information Systems › Educational and Technological Research
Keywords: big data in education, learning analytics, predictive analytics, student data, ethical considerations, student perceptions, staff perspectives, surveillance in higher education, data transparency, higher education, active learning

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Student and Staff Perspectives on the Use of Big Data in the Tertiary Education Sector: A Scoping Review and Reflection on the Ethical Issues

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