Way back when, I did some thinking about the differences between approaches to ethics in the Arts and the Social Sciences. To generalise, the Social Sciences treat the Internet as space, whereas the Arts treat the Internet as text. As I noted at the time: if you view the Internet as a virtual space populated by human actors, then you need a human subject approach to ethics, with informed consent a big issue. If, on the other hand, you see the Internet as an accumulation of texts, then your concern is with data protection, copyright and intellectual property rights. One practical example of this is that giving the real name of a data source is typically unethical behaviour in the Social Sciences, while failing to give the real name of a data source is typically unethical behaviour in the Arts.
So ethical behaviour is not a given – it is context dependent.
Extending this to learning analytics, a one-size-fits-all approach to ethics won’t necessarily work. Ethical research behaviour depends on what we are doing, on what we are trying to do and on what those involved in the research believe we are trying to do. The ethics discussion at #lasi13 suggested many of us are trying to different things – so maybe our approach to ethics will need to vary according to context.
Much of the discussion about the ethics of learning analytics this morning was framed in terms of learning as an economic transaction. The student contributes time, effort and money to an educational institution and, if this transaction is successfully completed, the student should emerge with a proxy for learning in the form of a certificate.
This view of learning is associated with a view of data as a commodity to be owned and exchanged. In order for this transaction to be successfully completed, some exchange of data (attendance figures, grades, etc) is essential, and each party to the contract has rights and responsibilities in relation to the data.
So that implies a contractual perspective on ethics. My own work is in a different context – in informal or barely formal learning settings. Learning through social media, open educational resources, MOOCs, virtual worlds… The transaction is not overtly economic, the outcomes are more varied, the data have a different role. There is less sense of an obligation on either side. I suspect this means that the ethical concerns and priorities will be different, and that negotiating them will take us in different directions.
So one ethical code for learning analytics may prove impossible, we may need to shift from one to another according to context.