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Implementing next generation privacy and ethics research in education technology

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dc.contributor.authorMarshall, R.
dc.contributor.authorPardo, A.
dc.contributor.authorSmith, D.
dc.contributor.authorWatson, T.
dc.date.issued2022
dc.description.abstractFor the developers of next‐generation education technology (EdTech), the use of Learning Analytics (LA) is a key competitive advantage as the use of some form of LA in EdTech is fast becoming ubiquitous. At its core LA involves the use of Artificial Intelligence and Analytics on the data generated by technology‐mediated learning to gain insights into how students learn, especially for large cohorts, which was unthinkable only a few decades ago. This LA growth‐spurt coincides with a growing global “Ethical AI” movement focussed on resolving questions of personal agency, freedoms, and privacy in relation to AI and Analytics. At this time, there is a significant lack of actionable information and supporting technologies, which would enable the goals of these two communities to be aligned. This paper describes a collaborative research project that seeks to overcome the technical and procedural challenges of running a data‐driven collaborative research project within an agreed set of privacy and ethics boundaries. The result is a reference architecture for ethical research collaboration and a framework, or roadmap, for privacy‐preserving analytics which will contribute to the goals of an ethical application of learning analytics methods.</jats:p></jats:sec><jats:sec><jats:label /><jats:p> <jats:boxed-text content-type="box" position="anchor"><jats:caption><jats:title>Practitioner notes</jats:title></jats:caption><jats:p>What is already known about this topic <jats:list list-type="bullet"> <jats:list-item><jats:p>Privacy Enhancing Technologies, including a range of provable privacy risk reduction techniques (differential privacy) are effective tools for managing data privacy, though currently only pragmatically available to well‐funded early adopters.</jats:p></jats:list-item> <jats:list-item><jats:p>Learning Analytics is a relatively young but evolving field of research, which is beginning to deliver tangible insights and value to the Education and EdTech industries.</jats:p></jats:list-item> <jats:list-item><jats:p>A small number of procedural frameworks have been developed in the past two decades to consider data privacy and other ethical aspects of Learning Analytics.</jats:p></jats:list-item> </jats:list></jats:p><jats:p>What this paper adds <jats:list list-type="bullet"> <jats:list-item><jats:p>This paper describes the mechanisms for integrating Learning Analytics, Data Privacy Technologies and Ethical practices into a unified operational framework for Ethical and Privacy‐Preserving Learning Analytics.</jats:p></jats:list-item> <jats:list-item><jats:p>It introduces a new standardised measurement of privacy risk as a key mechanism for operationalising and automating data privacy controls within the traditional data pipeline;</jats:p></jats:list-item> <jats:list-item><jats:p>It describes a repeatable framework for conducting ethical Learning Analytics.</jats:p></jats:list-item> </jats:list></jats:p><jats:p>Implications for practice and/or policy <jats:list list-type="bullet"> <jats:list-item><jats:p>For the Learning Analytics (LA) and Education Technology communities the approach described here exemplifies a standard of ethical LA practice and data privacy protection which can and should become the norm.</jats:p></jats:list-item> <jats:list-item><jats:p>The privacy risk measurement and risk reduction tools are a blueprint for how data privacy and ethics can be operationalised and automated.</jats:p></jats:list-item> <jats:list-item><jats:p>The incorporation of a standardised privacy risk evaluation metric can help to define clear and measurable terms for inter‐ and intra‐organisational data sharing and usage policies and agreements (Author, Ruth Marshall, is an Expert Contributor on ISO/IEC JTC 1/SC 32/WG 6 "Data usage", due for publication in early 2022).</jats:p></jats:list-item> </jats:list></jats:p></jats:boxed-text> </jats:p></jats:sec>
dc.identifier.citationBritish Journal of Educational Technology, 2022; 53(4):737-755
dc.identifier.doi10.1111/bjet.13224
dc.identifier.issn0007-1013
dc.identifier.issn1467-8535
dc.identifier.orcidPardo, A. [0000-0002-6857-0582]
dc.identifier.urihttps://hdl.handle.net/11541.2/28954
dc.language.isoen
dc.publisherWILEY
dc.relation.fundingAustralian Government Cooperative Research Centres Projects (CRC‐P) program
dc.rightsCopyright 2022 British Educational Research Association Access Condition Notes: Accepted manuscript available after 1 January 2024
dc.source.urihttps://doi.org/10.1111/bjet.13224
dc.subjectdata ethics
dc.subjectdata privacy
dc.subjectdifferential privacy
dc.subjectlearning analytics
dc.subjectprivacy enhancing technologies
dc.subjectprivacy risk
dc.subjectprivacy risk reduction
dc.titleImplementing next generation privacy and ethics research in education technology
dc.typeJournal article
pubs.publication-statusPublished
ror.fileinfo12245399410001831 13245399400001831 Open Access Postprint
ror.mmsid9916640289501831

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