Having taken the learning analytics course last year, at the start of this week I was back in familiar territory, reading Siemens on LA and EDM and watching Ben Williamson’s lecture on the digital university. In the second half of the week, we engaged in a two-day ‘tweetorial’ and I found myself communicating with Ben directly about LA.
The tweetorial was very much a tweetathon and I was fascinated to follow Anne’s link to some emergent analytics around our engagement and communications over the two days. Nigel’s cheesy diversion had an impact on the data which was generated via Twitter.
It will be fascinating to see what further analysis offers up, but this initial insight provided evidence of the conflicting interpretations as to what algorithms can offer us: order and chaos. The data generated by our discussion were, to an extent, captured and ordered by the algorithm, but the results are simultaneously ‘messy’ and require human agency to make sense of the ‘cheese’ in the data.
For me, thinking summatively about what we’ve focused on over the last 9 weeks, I keep circling back to Bayne’s term, ‘entanglement’ (Bayne, 2015).
The sociomaterialist perspective of the ‘the constitutive entanglement of the social and the material’ (Orlikowski, 2007) and, therefore, the technical, is a seam which has run throughout our blocks of study and was highlighted in both the Siemens and Williamson readings. As Siemens highlights, learning cannot be reduced to data:
The tension, the interplay, between the technical – the algorithm – and the human, informed much of our discussion during the tweetorial. Discussions circled back to the subjective agency which informs LA – both in terms of data extraction and interpretation – and to the impact of data on the subjects – both teachers and students. Kitchin and Dodge’s definition of algorithms – cited by Williamson – reminds us that data are not objective:
I’m looking forward to drawing more strands of thought together as we progress into week 10.
Orlikowski, W. J. (2007). Sociomaterial Practices: Exploring Technology at Work. Organization Studies (28)9, pp. 1435-1448.