Abstract
The adoption of learning analytics in the Higher Education sector is evolving fast, however, there are many challenges concerning privacy, ethics, security, and transparency. Despite HE Institutions having promised to improve student’s learning experiences through the use of student data, students, to a large extent, are absent and verily in institutions policies and frameworks. This research investigated student perceptions of privacy principles in learning analytics through a rapid review of 12 papers. Results reveal that there is very limited research on students’ perception of privacy and learning analytics, and inadequate insight into students’ awareness of privacy principles in an educational context.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Adejo, O., Connolly, T.: Learning analytics in a shared-network educational environment: ethical issues and countermeasures. Learning 8(4), 156–163 (2017)
Arnold, K.E., Sclater, N.: Student perceptions of their privacy in leaning analytics applications. In: Proceedings of LAK 2017, pp. 66–69 (2017)
Falcão, T.P., Mello, R.F., Rodrigues, R.L., Diniz, J.R.B., Tsai, Y.S., Gašević, D.: Perceptions and expectations about learning analytics from a Brazilian HE institution. In: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, pp. 240–249 (2020)
Ifenthaler, D., Schumacher, C.: Student perceptions of privacy principles for learning analytics. Education Tech. Research Dev. 64(5), 923–938 (2016)
Khalil, M., Ebner, M.: Learning analytics: principles and constraints. In: EdMedia+Innovate Learning. Association for the Advancement of Computing in Education (AACE), pp. 1789–1799 (2015)
Roberts, L.D., Howell, J.A., Seaman, K.: Give me a customizable dashboard: Personalized learning analytics dashboards in HE. Technol. Knowl. Learn. 22(3), 317–333 (2017)
Roberts, L.D., Howell, J.A., Seaman, K., Gibson, D.C.: Student attitudes toward learning analytics in HE: “The fitbit version of the learning world”. Front. Psychol. 7 (2016)
Slade, S., Prinsloo, P., Khalil, M.: Learning analytics at the intersections of student trust, disclosure and benefit. In Proceedings of LAK 2019, pp. 235–244 (2019)
Sun, K., Brooks, C., Mhaidli, A.H., Schaub, F., Watel, S.: Taking student data for granted? A multi-stakeholder privacy analysis of a learning analytics system. In: EDM 2018 Workshop on Policy and Educational Data Mining (2018)
Tsai, Y.S., Whitelock-Wainwright, A., Gašević, D.: The privacy paradox and its implications for learning analytics. In: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, pp. 230–239 (2020)
Vu, P., Adkins, M., Henderson, S.: Aware, but don’t really care: students’ perspective on privacy and data collection in online courses. J. Open Flex. Distance Learn. 23(2), 42–51 (2020)
Khangura, S., Konnyu, K., Cushman, R., Grimshaw, J., Moher, D.: Evidence summaries: the evolution of a rapid review approach. Syst. Rev. 1(1), 10 (2012)
Whitelock-Wainwright, A., et al.: Assessing the validity of a learning analytics expectation instrument: a multinational study. J. Comput. Assist. Learn. 36, 209–240 (2020)
Whitelock-Wainwright, A., Gašević, D., Tejeiro, R., Tsai, Y.S., Bennett, K.: The student expectations of learning analytics questionnaire. J. Comput. Assist. Learn. 35(5), 633–666 (2019)
Khalil, M., Ebner, M.: De-identification in learning analytics. J. Learn. Analytics 3(1), 129–138 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Botnevik, S., Khalil, M., Wasson, B. (2020). Student Awareness and Privacy Perception of Learning Analytics in Higher Education. In: Alario-Hoyos, C., Rodríguez-Triana, M.J., Scheffel, M., Arnedillo-Sánchez, I., Dennerlein, S.M. (eds) Addressing Global Challenges and Quality Education. EC-TEL 2020. Lecture Notes in Computer Science(), vol 12315. Springer, Cham. https://doi.org/10.1007/978-3-030-57717-9_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-57717-9_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57716-2
Online ISBN: 978-3-030-57717-9
eBook Packages: Computer ScienceComputer Science (R0)