Student privacy in learning analytics: An information ethics perspective

Description:

Higher education institutions have started using big data analytics tools. By gathering information about students as they navigate information systems, learning analytics employs techniques to understand student behaviors and to improve instructional, curricular, and support resources and learning environments. However, learning analytics presents important moral and policy issues surrounding student privacy. We argue that there are five crucial questions about student privacy that we must address in order to ensure that whatever the laudable goals and gains of learning analytics, they are commensurate with respecting students’ privacy and associated rights, including (but not limited to) autonomy interests. We address information access concerns, the intrusive nature of information-gathering practices, whether or not learning analytics is justified given the potential distribution of consequences and benefits, and issues related to student autonomy. Finally, we question whether learning analytics advances the aims of higher education or runs counter to those goals.

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Cited in the scholarly literature:

Mittelstadt, B. (2016). Automation, algorithms, and politics: Auditing for transparency in content personalization systems. International Journal of Communication10(2016), 4991–5002. Retrieved from http://ijoc.org/index.php/ijoc/article/view/6267

Mittelstadt, B., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (forthcoming). The ethics of algorithms: Mapping the debate. Big Data & Society. Retrieved from http://philpapers.org/rec/MITTEO-12

Prinsloo, P., & Slade, S. (2016). Student vulnerability, agency, and learning analytics: An exploration. Journal of Learning Analytics, 3(1), 159–182. Retrieved from https://epress.lib.uts.edu.au/journals/index.php/JLA/article/view/4447

Roberts, L. D., Chang, V., & Gibson, D. (2017). Ethical considerations in adopting a university-and system-wide approach to data and learning analytics. In B. K. Daniel (ed.), Big data and learning analytics in higher education (pp. 89-108). Switzerland: Springer International Publishing. Accessible at http://link.springer.com/chapter/10.1007/978-3-319-06520-5_7

Cited in syllabi/course sites:

Daniel Hickey (Indiana University): Introduction to Educational Data Sciences. https://iu.instructure.com/courses/1457882/pages/5-introduction-to-learning-analytics

Cited elsewhere:

UW-Madison Delta Roundtable. https://delta.wisc.edu/Data_Analytics_Resources.pdf

Google Scholar Citations: 3

Access the Publication: The Information Society

APA Citation:

Rubel, A. & Jones, K. M. L. (2016). Student privacy in learning analytics: An information ethics perspective. The Information Society, 32(2), 143–159. doi: 10.1080/01972243.2016.1130502

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