Week 9: learning analytics and calculating academics

This week we will continue to develop our thinking around algorithmic cultures within education by watching a video lecture (Ben Williamson on the digital university), reading a paper (George Siemens on learning analytics) and debating the ideas raised within a course tweetorial.

What is a tweetorial and how does it work?

We will dedicate two days of this week (Thursday 12th March and Friday 13th March) to some intensive tweeting around the ideas raised in weeks 8 and 9 of the course. Nearer the time, we will post questions here and on Twitter for you to respond to using the course hashtag #mscedc. A rough analysis of our tweets using Tweetarchivist will be available below.

To take part in the tweetorial you will need a Twitter account, and we would recommend you use Tweetdeck to view your tweets: see the Twitter section of the MSc programme Technologies Handbook for how to set these up.

Week 9 readings

This week’s readings (one of which is a video lecture) will complement those we looked at last week, and will help us formulate some of our ideas for the tweetstorm this week.

Lecture
Ben Williamson (2014) Calculating Academics: theorising the algorithmic organization of the digital university

In this 40 minute lecture, Ben Williamson from the University of Stirling explores some of the ways in which algorithms are informing contemporary ways of understanding the university. Ben’s talk – given at the University of Edinburgh late last year – gives us a good perspective on the broader contexts of ‘learning analytics’ and big data in education, and perhaps help us understand why we need to develop a critical understanding of algorithmic culture in order to respond to the growth of new fields of research such as learning analytics.

Reading
Siemens, G. (2013) Learning Analytics: the emergence of a discipline. American Behavioral Scientist, 57(10): 1380-1400
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In this paper, George Siemens tracks the emergence of learning analytics as a ‘discipline’, providing a useful overview of the field’s techniques, functions and expectations of itself.