Tag Archives: privacy

Type: Evidence | Proposition: D: Ethics | Polarity: | Sector: | Country:

The paper defines privacy as the regulation of how personal digital information is being observed by the self or distributed to other observers. It defines ethics as the systematization of correct and incorrect behaviour in virtual spaces according to all stakeholders.

Principles identified within this paper are:

  • transparency
  • student control over data
  • rights of access
  • accountability and assessment

The authors argue that, by discussing the various aspects within each of these categories, institutions have mechanisms to assess their initiatives and achieve compliance with current laws and regulations as well as with socially derived requirements.

In terms of the Evidence Hub proposition 'Learning analytics are used in an ethical way', the need for a paper such as this to be written implies that appropriate measures are being developed but are not yet in place. As the authors note, 'The ethical and privacy issues derived from these scenarios are not properly addressed.'

Summary provided within the paper:

What is already known about this topic
• Learning analytics offers the possibility of collecting detailed information about how students learn.
• The ethical and privacy issues derived from these scenarios are not properly addressed.
• There is a need to clarify how these issues must be addressed from the early stages of the deployment of a learning analytics scenario.
What this paper adds
• An account of how the main legislations are advancing in the general area of privacy.
• A comparison of how other disciplines such as medicine have dealt with privacy issues when collecting private information.
• The description of a group of practical principles in which to include all the ethical and privacy-related issues present when deploying a learning analytics application.
Implications for practice and/or policy
• Designers may now take into account these principles to guide the implementation of learning analytics platforms.
• Students are now aware of the different categories of issues that must be addressed by applications collecting data while they learn.
• Instructors now have a more detailed account of the issues to address when adopting learning analytics techniques.

Citation: Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 45(3), 438-450. | Url: https://www.researchgate.net/profile/Abelardo_Pardo/publications?pubType=article

Type: Evidence | Proposition: D: Ethics | Polarity: | Sector: | Country:

This paper provides an overview of privacy and considers the potential contribution contemporary privacy theories can make to learning analytics. It is written from the position that having the technical capability to conduct a particular learning analytics task does not automatically mean that the task should be performed. It reflects on how privacy theories can help advance learning analytics and stresses the importance of hearing the student voice in this space.

“Transmission principles regarding the provision of a student’s personal demographic data in the student application, admission, and administration context do not necessarily apply in any other context. If a student agrees to the flow of student equity‐related data to support admission processes, he or she is not necessarily agreeing to the same terms and conditions of information flow in another context, such as secondary use of data for learning analytics activities.”

This paper is considered to be positive evidence for ‘Proposition D: Learning analytics are used in an ethical way’ because it provides evidence that learning analytics researchers are thinking carefully about these issues.

Citation: Heath, Jennifer. (2014). Contemporary privacy theory contributions to learning analytics. Journal of Learning Analytics, 1(1), 140-149. | Url: http://epress.lib.uts.edu.au/journals/index.php/JLA/issue/view/307