EDUCAUSE just completed two afternoons of online presentations and discussions in their Learning Analytics Online Spring Focus Session.
In my talk [Abstract+Resources/AdobeConnect replay] I continued to explore the potential dream/nightmare theme that I’ve been running for the last few months [Ascilite2011; Networked Learning Hotseat 2012], but updated to explore in more detail some of the legitimate concerns around the definition and implementation of analytics. These revolve around the fundamental limits of computational modelling which have pedagogical, political and social justice ramifications. The slides include follow-up citations, but you might want to get the annotated slides [pdf] to see my additional commentary notes.
I open with the story of a student whose progress is not only invisible in the visual analytics, but which is in fact depicted as retrograde. “Joe” is not real of course, but is a composite of the kinds of students we have in the school where I work, and his story will be painfully familiar to all school Heads working with the bitter reality of many students’ lives, and national analytics claiming to reflect the school’s performance.
Thanks to Malcolm Brown, Veronica Diaz and the ELI team who pulled together a very high calibre forum (and helped me check I could give the webinar from a farm holiday cottage in Teeside!).
A quick interactive exercise I do is invite webinar participants to type in the qualities that in their experience make great learners:
In 10 secs, we crowdsource a list which presents a challenging set of qualities and dispositions that we all want to foster in our learners. How does our mentoring and teaching scaffold such qualities, and how might Dispositional Learning Analytics give us clues to their presence?
The next slide introduces the work of Ruth Deakin Crick at University of Bristol Graduate School of Education, with whom I’m now working, as we try to figure out how her approach to modelling learning dispositions as a multidimensional construct can be embedded into social learning platforms. The mapping between what the webinar participants entered, and the seven Learning Power dimensions of the visual analytic, is striking…
See LearningEmergence.net for more on this, and the upcoming LAK12 paper:
Buckingham Shum, S. and Deakin Crick, R. (2012). Learning Dispositions and Transferable Competencies: Pedagogy, Modelling and Learning Analytics. Proc. 2nd Int. Conf. Learning Analytics & Knowledge. (29 Apr-2 May, 2012, Vancouver, BC). ACM Press: New York. Eprint: http://oro.open.ac.uk/32823
Next stop, Vancouver for the SOLD OUT Learning Analytics & Knowledge conference…