Possible topic: What’s the matter with data-enhanced learning?

Quite suddenly tonight, an idea for a possible assignment topic struck my head. Choosing the final topic has been simmering in my head the past week but only only now did it bubble up — so I thought I’d write this idea down, as a first attempt at least for thinking about the final assignment for the course.

The title will be: What’s the matter with data-enhanced learning? The title is a rift of Sian’s critique of TEL. The plan is to apply the three main critiques Sian raised in her article to some of the claims made about learning analytics.

The paper will try to argue how the process of data-gathering needs to be questioned; values behind the application of learning analytics, clarified; and assumptions about learning, uncovered.

I am uncertain about two things: Are the terms learning analytics and data-enhanced learning synonymous? Is the use of term data-enhanced learning justifiable for the title, though perhaps not in the body of the paper.

For references, I will rely mainly on Sian’s article for the framework of the critique of TEL. For the other part, I will cite the main claims made about learning analytics as mentioned by Ben Williamson in his presentation.

For the multimodal part, I will try to draw a sketch note that outlines the main arguments, similar to the one I had created earlier. I have seen several videos of animated data visualisations but I do not have the skills to pull of something similar. Although I will try to minimise the amount of text in the sketch note, having the flexibility of the sketch note format comes in handy. The need to minimise the amount of text in the drawing suggests that the tone may need to be somewhat punchy, or manifesto-like. Time may not be enough to pull something like that for the assignment but I am writing it down here anyway to keep it in the radar of my brain. The sketch note cannot stand alone and still relies on text to flesh out the argument. I’m unsure whether I will combine the images and text into a web page or PDF document.

A song called Android’s lament, which I tweeted in the early weeks of the course, seems appropriate for the topic. It’s opening lyric is “I will not be pushed, filed, stamped, debriefed or numbered”, which sounds like a rally against the de-personalization that happens as a by product of the processes around big data. I do not know yet how to incorporate it into the multimodal format, but the tone of its argument reminds me of Haraway’s strong and clear voice, and of her imaginative approach.

These are just preliminary ideas, some of which may not make it as part of my final assignment. However, I am interested in finding out which ideas I keep or discard in the end, and why: Creating a multimodal artefact is its own learning.

5 comments

  1. mprowse says:

    Ed, Great outline and concept for the final assignment (theres a breadth here but a distinct focus too). I particularly like your note that ‘creating a multimodal artefact is its own learning’, inspirational and highly relevant for my own final assignment (work in progress) idea.

  2. sbayne says:

    I do like the sound of this Ed. I think it’s perfectly reasonable to take a wider view of ‘data’ in education than learning analytics alone. For example, you might want to take a look at some work on data and the governance of education (this paper by Borer and Lawn is open access and gives some sense of the history of this).

    This may be a little broader than you’d like to try for what is after all quite a short piece of work. If so, I think just focusing on ‘What’s the matter with learning analytics’ would be more than respectable! Your sketch notes are great, so I can see that working really well in terms of form.

    • Ed Guzman says:

      Thanks Sian. I haven’t started on a lit review yet, so I’ll try to see if my focus changes. Thanks for sending the link to the journal article. The process of institutionalising use of data in education is quite revealing, especially because the questions being raised about analytics now seem to clearly echo the issues that were already there at the start.

      Incidentally, the authors are from the Uni of Geneva, which is only a few minutes walk from my place. What a strange coincidence!

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