DELICATE checklist 4 privacy released at LAK16

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Wolfgang and Hendrik presenting the DELICATE checklist for privacy and ethics in LA

After a lighting keynote from Mireille Hildebrandt on legal aspects of data analytics, it was a full house during our presentation of the DELICATE checklist at #LAK16. People where sitting on the floor or standing around and the 50 Checklists we printed have been sold out in 2 min. Who did not get a checklist, just download it and print it yourself [here].

The DELICATE checklist has been developed over 18 months intensive studies of EU law and various expert workshops on Ethics and Privacy for Learning Analytics (EP4LA). From those workshops we wrote a LACE Review about this pressing topic and developed the DELICATE Checklist for the LACE community in order to have a better discussion ground for kick starting Learning Analytics and Educational Data Mining activities in an educational association.

The DELICATE checklist contains eight action points that should be considered by managers and decision makers planning the implementation of Learning Analytics / Educational Data Mining solutions either for their own institution or with an external provider.

We hope that the DELICATE checklist will be a helpful instrument for any educational institution to demystify the ethics and privacy discussions around Learning Analytics. As we have tried to show in this article, there are 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 eight points are:
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 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, pp. 89-98
Edinburgh, UK. DOI: http://dx.doi.org/10.1145/2883851.2883893
Here are the slides we used to introduce the DELICATE checklist at LAK16:

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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.

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  1. Pingback: Reflecting on LAK16

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