I’ve had the time of my life(stream) – Week 9 summary

There are twin themes to the lifestream this week: the first, a desire to engage critically with the content of the block, emerges through plenty of references to critical texts and articles. Learning analytics, and the omnipresent ethical debate which surrounds it, is a key component. For example, I included Anderson’s brilliant Wired article (mentioned in the lecture we heard this week), a short reading list on learning analytics and ethics, and a JISC report, which I found to be quite uncritical: I included some of the notes I made while reading it, and my responses.

There’s a keen sense, then, of ‘what I’m reading‘. The phrase, chosen as a blog title over two months ago when I set up IFTTT to work with Evernote, encapsulates the second of the twin themes: an emerging issue of temporality. This, I think, is present in several ways. With regard to learning analytics and Big Data, temporality incorporates ideas of the currency of the collection of data: methods of data collection and analysis will improve, but this will not necessarily account for the patchiness of past data, upon which decisions will continue to be made. This, for me, problematises our historiographical understanding of how Big Data might help us to become more self-aware, especially with regard to the “timeless quest” to which Cukier refers in this Ted talk. But temporality is present too in a personal sense: in my reasons for missing the tweetstorm, which was locked into a specific point in time, but also in a keenly felt fixing of attention to forthcoming assignments.

The themes converge with a slightly more substantive blog post on Big Data, learning analytics and posthumanism which, I think, may be a fruitful topic to consider further in the digital essay.

One Reply to “I’ve had the time of my life(stream) – Week 9 summary”

  1. Lots of really great critical stuff here Helen, and some super reading lists. Ethics is a really important topic here, and it seems to cross over into the related areas of data, and its collection and storage. Although associated in very important ways, it might be worth thinking through the ways that ethics relate to (educational) algorithms specifically – what is it about the prediction or ‘personalisation’ that is ethically questionable, as opposed to privacy or surveillance (equally important perhaps, but also distinct).

    Good to pick up on the JISC reports here in the UK – I’m looking at those as well at the moment, so interesting to read your thoughts. It seems difficult to get past simplistic notions of tool use doesn’t it? I’ve added a few more comments there too.

    Sorry to hear you couldn’t make the tweetorial – good avenue for a critique of the tweetarchivist presentation then! Imagine if we were using those visualisations to assess student sin week 8….

    I’ll also comment on your post ‘Big Data, learning analytics, and posthumanism’ shortly…

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