Prioritizing Ethical Use of Learning Data

It’s been a minute since I presented to a large group, albeit online, but I relished the opportunity presented to me by the Learning Guild in inviting to me to speak to the latest xAPI Cohort on ethics and learning analytics. I’m a person who likes to be pretty grounded in any advice I’d share, so I first took notes about the things I actually believe, let alone practice, regarding ethics. That gave me a sort of compass to navigate the literature, and I was very fortunate to find a lot on ethics and learning analytics; a fairly mature corpus. Most of this corpus centered on primary, secondary and higher education use cases for learning analytics, and there’s much to draw from there.

Recording from Week 8 of the xAPI Cohort, 20 October 2022.

Given the context of adult learners in workforce development, in this presentation I

  1. Modeled a lifecycle of an xAPI Statement (json data) to understand the potential long-term impacts of once piece of data on real people;
  2. Curated relevant ethical challenges related to using learning data from a corpus of research literature specifically about the ethics of learning analytics; and
  3. Imparted the need to continuously train the capacity for empathy to strengthen inquiry skills and prioritize ethical use.

As I shared elsewhere, I was delighted to highlight great work done by Rebecca FergusonStephen Downes and others on ways we might prioritize the ethical use of learning data. Thanks so much for sharing your work openly. I hope I was able to at least tie a few difficult concepts across learning science, technical architecture and ethics together in a useful, “I could actually do this” way.

I’d be open to feedback on how to tie these things together better. It’s been a minute.

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