#EP4LA #LAK15 privacy driven design of learning analytics applications – exploring the design space of solutions for data sharing and interoperability 


Tore Hoel and Chen

Privacy control of data and trust essential to learning analytics. What are the implications for LA design of setbacks in learning analytics/privacy issues? Who owns the data? LACE suggests we give parents and students control of their own data…? Will this solve the privacy problem? Privacy is recognised but only superficially so, mostly seen as a barrier that should be overcome. Issues defined by Nissenbaum are contextual integrity, informational norm, actors, information types, transmission principles, contexts (tech, business practice, social domain). Where are the boundaries between formal agreed study and what goes on in the private space? Hoel suggest that socio cultural barriers to sharing data more important than legal barriers.

Should we be asking whether any application of learning analytics would pass a public deliberation on the appropriate use of the data? Good question. Societal approval is key…. Eg the InBloom collapse failed due to public perceptions around the trust issues rather than the application per se. Hoel suggests any LA application should have privacy aspects designed in at the start as an integral part of the solution/approach. Bit.ly/lashare

 

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About sharonslade

Dr Sharon Slade is a senior lecturer in the Faculty of Business and Law at the Open University in the UK working to support both tutors and students on Open University distance learning modules and programmes. Her research interests encompass ethical issues in learning analytics and online learning and tuition. Project work includes the development of a student support framework to improve retention and progression and the development of a university wide tool for tracking students and triggering relevant and targeted interventions. She led the development of new policy around the ethical use of learning analytics within the Open University, UK.
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