Ethics & Privacy

Privacy, please!

Picture from Tristan Niot, https://www.flickr.com/photos/nitot/3488350975/

Learning analytics is a new field, and as with any other new technology there is work to be done to apply existing ethical and privacy approaches to the new ethical quandaries which are generated. Many of the people involved are unused to wrestling with kinds of questions of ethics or privacy that are associated with the field, and are unaware of how to set about answering them.

The LACE project therefore started 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 won the LAK16 best paper award and can be found and cited here:
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.
A pre-print version is available at Dspace server of the Open University of the Netherlands click [here].
Here are the slides we used to introduce the DELICATE checklist at LAK16: