I am completing Week 10 activities, and writing this synthesis, a week later than scheduled in the course, due a bout of flu and pneumonia which has prevented me from participating in some of the course activities (e.g. the week 10 Google Hangout). I have, however, managed to accomplish two key tasks: First, a completed a critical blog on the analytics from the Week 9 Tweetorial; Second, I have refined the title and focus on my digital essay.
My critical discussion of the analytics from the Tweetorial highlighted the over-representation of males as top-participants. Analytics such as this, I argued, can help facilitate a level of reflexivity in teaching; for example, by highlighting teaching techniques that could, inadvertently, re-enforce gendered divisions in learning. I also argued that such analytics need to be treated with caution. In particular, we need to avoid the temptation – as highlighted in Ben Williamson’s presentation – to view big data as ‘revealing’ the true social facts and patters in education. Instead, I argued, learning analytics are best viewed as part of a broader set of socio-material relationships, through which the learning process is socially constructed. This, I suspect, is not the prevailing approach to the promise of Big Data in higher education!
This led me to consider the focus of my digital essay. I am keen to explore Big Data further, so I emailed a provisional title to Jeremy and Sian (which was looking to explore humanist and anti-humanist frameworks to using Big Data in smart universities). This was to broad a focus for an assignment of 2500 words, so I narrowed the focus to the following
The promises and pitfalls of Big Data in higher education
I then did some searching via Pinterest on visual representations of the promises and pitfalls of Big Data. As you can see from the results, there tends to be more promises associated with Big Data than pitfalls, which will be a useful theme to explore in terms of the emerging ideology of Big Data.