You are here:

User Consent in MOOCs – Micro, Meso, and Macro Perspectives
ARTICLE English

, ,

IRRODL Volume 19, Number 5, ISSN 1492-3831 Publisher: Athabasca University Press

Abstract

While many strategies for protecting personal privacy rely on regulatory frameworks, consent, and anonymizing data, they are not always effective. Terms and Conditions often lag behind advances in technology, software, and user behaviours, and consent to use data for a range of unclear purposes may be provided unwittingly. As the commercial market for (student) data expands, so does the number of brokers who move, share and sell data across continents and legislative environments. This paper reviews four Massive Open Online Course (MOOC) providers from different geopolitical and regulatory contexts. It explores how consent to collect and use data is described to potential users, and how that consent applies at micro, meso, and macro levels.This paper proposes a need for greater transparency around the implications of users granting consent at the point of registration. Further, it highlights that though MOOC providers have a responsibility to make clear the potential uses and sharing of user data, users themselves should also be more aware and consider how meaningful student agency can be achieved.

Citation

Khalil, M., Prinsloo, P. & Slade, S. (2018). User Consent in MOOCs – Micro, Meso, and Macro Perspectives. The International Review of Research in Open and Distributed Learning, 19(5),. Athabasca University Press. Retrieved December 19, 2018 from .

View References & Citations Map

References

  1. Ball, K., Haggerty, K.D., & Lyon, D. (2012). Routledge handbook of surveillance studies. Abingdon, UK: Routledge.
  2. Bellman, S., Johnson, E.J., & Lohse, G.L. (2001). Onsite: to opt in or opt-out?: It depends on the question. Communications of the ACM, 44(2), 25-27. Retrieved from http://dl.acm.org/citation.cfm?id=359241
  3. Bennett, C.J. (2018). The European general data protection regulation: An instrument for the globalization of privacy standards? Information Polity, (Preprint), 1-8. Retrieved from https://pdfs.semanticscholar.org/3813/041fc44467933d64c54c3e39a467c2be63c3.pdf
  4. Bos, W., & Tarnai, C. (1999). Content analysis in empirical social research. International Journal of Educational Research, 31(8), 659-671. Http://doi.org/10.1016/S0883-0355(99)00032-4
  5. Buckingham Shum, S. (2012). Learning analytics. UNESCO Institute for Information Technologies in Education. Retrieved from http://iite.unesco.org/files/policy_briefs/pdf/en/learning_analytics.pdf
  6. Cormack, A.N. (2016). Downstream consent: A better legal framework for Big Data. Journal of
  7. Crawford, K., & Schultz, J. (2013). Big data and due process: Towards a framework to redress predictive privacy harms. Boston College Law Review, 55(1). Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784
  8. Drachsler, H., & Kalz, M. (2016). The MOOC and learning analytics innovation cycle (MOLAC): A
  9. Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107-115.
  10. Fairfield, J.A.T. (2017). Owned: Property, privacy, and the new digital serfdom. Cambridge, United Kingdom: Cambridge University Press.
  11. Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6) 304–317. Retrieved from http://oro.open.ac.uk/36374/1/IJTEL40501_Ferguson%20Jan%202013.pdf
  12. Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71.
  13. Hern, A. (2018, April 19). Facebook moves 1.5bn users out of reach of new European privacy law [Blog post]. The Guardian. Retrieved from https://www.theguardian.com/technology/2018/apr/19/facebook-moves-15bn-users-out-ofreach-of-new-european-privacy-law
  14. Krasnova, H., Veltri, N.F., & Günther, O. (2012). Self-disclosure and privacy calculus on social networking sites: The role of culture. Business& Information Systems Engineering, 4(3), 127135.
  15. Meyer, R. (2018, March 20). The Cambridge Analytica scandal, in three paragraphs [Blog post]. The Atlantic. Retrieved from https://www.theatlantic.com/technology/archive/2018/03/thecambridge-analytica-scandal-in-three-paragraphs/556046/
  16. Miltgen, C.L., & Smith, H.J. (2015). Exploring information privacy regulation, risks, trust, and behaviour. Information& Management, 52(6), 741–759.
  17. Prinsloo, P., & Slade, S. (2015, March). Student privacy self-management: Implications for learning analytics. In Proceedings of the fifth international conference on learning analytics and knowledge (pp. 83-92). ACM. Retrieved from
  18. Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist 57(10), 1509–1528.
  19. Solove, D.J. (2004). The digital person: Technology and privacy in the information age. New York, USA: New York University Press.
  20. Solove, D.J. (2013). Introduction: Privacy self-management and the consent dilemma. Harvard Law Review 126(7), 1880–1904.

These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact info@learntechlib.org.