The unbearable lightness of consent: Mapping MOOC providers’ response to consent

Khalil, Mohammad; Prinsloo, Paul and Slade, Sharon (2018). The unbearable lightness of consent: Mapping MOOC providers’ response to consent. In: L@S '18: Proceedings of the Fifth Annual ACM Conference on Learning at Scale, ACM, New York, article no. 61.

DOI: https://doi.org/10.1145/3231644.3231659

Abstract

While many strategies for protecting personal privacy have relied on regulatory frameworks, consent and anonymizing data, such approaches are not always effective. Frameworks and Terms and Conditions often lag user behaviour and advances in technology and software; consent can be provisional and fragile; and the anonymization of data may impede personalized learning. This paper reports on a dialogical multi-case study methodology of four Massive Open Online Course (MOOC) providers from different geopolitical and regulatory contexts. It explores how the providers (1) define ‘personal data’ and whether they acknowledge a category of ‘special’ or ‘sensitive’ data; (2) address the issue and scope of student consent (and define that scope); and (3) use student data in order to inform pedagogy and/or adapt the learning experience to personalise the context or to increase student retention and success rates.

This study found that large amounts of personal data continue to be collected for purposes seemingly unrelated to the delivery and support of courses. The capacity for users to withdraw or withhold consent for the collection of certain categories of data such as sensitive personal data remains severely constrained. This paper proposes that user consent at the time of registration should be reconsidered, and that there is a particular need for consent when sensitive personal data are used to personalize learning, or for purposes outside the original intention of obtaining consent.

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About

  • Item ORO ID
  • 55577
  • Item Type
  • Conference or Workshop Item
  • ISBN
  • 1-4503-5886-1, 978-1-4503-5886-6
  • Extra Information
  • presented at L@S 2018 (Fifth (2018) ACM Conference on Learning @ Scale), June 26–28, 2018, London, UK.
  • Keywords
  • consent; sensitive data; Massive Open Online Courses (MOOCs); learning analytics; privacy policy; terms and conditions
  • Academic Unit or School
  • Faculty of Business and Law (FBL) > Business
    Faculty of Business and Law (FBL)
  • Copyright Holders
  • © 2018 Association for Computing Machinery
  • SWORD Depositor
  • Jisc Publications-Router
  • Depositing User
  • Jisc Publications-Router
CORE (COnnecting REpositories)

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