Ethics & Privacy in Learning Analytics – a DELICATE issue

0
Privacy, please!

Picture from Tristan Niot

The widespread adoption of Learning Analytics (LA) and Educational Data Mining (EDM) has somewhat stagnated recently, and in some prominent cases like the inBloom disaster even been reversed following concerns by governments, stakeholders and civil rights groups.

In this ongoing discussion, fears and realities are often indistinguishably mixed up, leading to an atmosphere of uncertainty among potential beneficiaries of Learning Analytics, as well as hesitations among institutional managers who aim to innovate their institution’s learning support by implementing data and analytics with a view on improving student success.

The LACE project conducted a series of Expert Workshops on Ethics and Privacy for Learning Analytics (#EP4LA) on the topic to get to the heart of the matter, by analysing the most common views and the propositions made by the LA community to solve them.

Within LACE,  an eight-point checklist named DELICATE has been developed that can be applied by teachers, researchers, policy makers and institutional managers to facilitate a trusted implementation of Learning Analytics.

The eight points are [It can be downloaded here LINK]:
1. D-etermination: Decide on the purpose of learning analytics for your institution.
2. E-xplain: Define the scope of data collection and usage.
3. L-egitimate: Explain how you operate within the legal frameworks, refer to the essential legislation.
4. I-nvolve: Talk to stakeholders and give assurances about the data distribution and use.
5. C-onsent: Seek consent through clear consent questions.
6. A-nonymise: De-identify individuals as much as possible
7. T-echnical aspects: Monitor who has access to data, especially in areas with high staff turn-over.
8. E-xternal partners: Make sure externals provide highest data security standards.

The DELICATE checklist will be a helpful instrument for any educational institution to demystify the ethics and privacy discussions around Learning Analytics. The DELICATE Checklist shows ways to design and provide privacy conform Learning Analytics that can benefit all stakeholders and keep control with the users themselves and within the established trusted relationship between them and the institution.
The full article about DELICATE will be published at LAK16 in Edinburgh, for citing the source article please use the following citation:
Drachsler, H. & Greller, W. (2016). Privacy and Analytics – it’s a DELICATE issue. A Checklist to establish trusted Learning Analytics. 6th Learning Analytics and Knowledge Conference 2016, April 25-29, 2016, Edinburgh, UK.

An early pre-print of the article is available on Dspace, but the final version has received various improvements so we strongly recommend to use the official publication from the LAK16 proceedings.

Share.

About Author

Dr. Hendrik Drachsler is Associate Professor for Personalised Learning Technologies at the Welten Institute of the Open University of the Netherlands. His research interests include Learning Analytics, Personalisation technologies, Recommender Systems, Educational data, mobile devices, and their applications in the fields of Technology-Enhanced Learning and Health 2.0. He is chairing the EATEL SIG dataTEL and the national SIG Learning Analytics of the Dutch umbrella organisation SURF. He is elected member of the Society of Learning Analytics Research (SoLAR). In the past he has been principal investigator and scientific coordinator of various national and EU projects (e.g., FP7 laceproject.eu, patient-project.eu, WP2 lead LinkedUp-project.eu). He has regularly chairing international scientific events and is Associate Editor of IEEE's Transactions on Learning Technologies, and the Journal of Learning Analytics.

Leave A Reply