Learning Analytics: Dream, Nightmare, or Fairydust?
From today’s keynote at Ascilite 2011, here’s the podcast plus the slides. I am grateful to Gary, Renee and everyone else at Ascilite for their understanding and flexibility, since after months of planning this trip, unfortunately I could not be there in person after my father passed away last weekend.
For detailed descriptions of work presented here, see other posts tagged learning analytics and the references below.
Pervasive digital technology is weaving a fabric around our lives which makes it increasingly hard not to leave digital traces. We are experiencing an unprecedented explosion in the quantity and quality of data available not only to us, but about us. While some people find this blanket suffocating and threatening, for others, it marks an exciting new turn in our cultural evolution. The question for us is: what are the implications for learning?
One answer is it’s time to upgrade our computing kit. The learning platform and business intelligence vendors are rolling out analytics dashboards aggregating data into summary views, and will be a source of innovation as they seek to respond to customer needs — but what will institutions be asking for? It is conceivable that government education departments might see potential for league tables based on them.
Another answer is that, at last, we will have an evidence base previous generations of educators and academics could only dream of: real-time data streaming in from our students, even more from data shared by countless others who are happy to reveal their social networks, geo-location, and recommended books. Previously siloed scholarly datasets are now released into the wild, where they can be harvested and mined in a vibrant ecosystem of connected ideas, learners and educators.
Then there are those of a more cautious nature. So what if we have shedloads of data? Now we can drown faster. Learning, enquiry, argumentation, sensemaking, scholarship, insight — these skills are of an entirely different order, the highest forms of meaning-making, uniquely human. And what have analytics to say about the less tangible 21st Century skills that we need to nurture if the next generation is to manage the unprecedented complexity and uncertainty that they will inherit from us? Surely data analytics have nothing to say about intrinsic disposition to learn, emotional resilience in the face of adversity, the ability to moderate a discussion, resolve conflict, or ask critical questions? Finally, who is in control of analytics: are they tools to study learners, or tools to place in their hands, to create reflective, more agile individuals and collectives?
Analytics may in time come to be used to judge you — as a learner, an educator, or your institution. The challenge for us is to debate what it means for this new breed of performance indicators to have pedagogical and ethical integrity. What can and should we do, and what are the limits? Do they advance what we consider to be important in learning, teaching, and what it means to be a higher education institution in the 21st Century?
Are you thinking Dream, Nightmare, or Fairydust?
Simon Buckingham Shum’s work on sensemaking, collective intelligence and knowledge cartography inform his thinking about the role of technology in shaping the future of learning in higher education, and at school level. His background is in Psychology (B.Sc., York), Ergonomics (M.Sc., UCL) and Graphical Argumentation for Design Rationale (Ph.D., York). He is Senior Lecturer in Knowledge Media and Associate Director (Technology), at the Open University’s Knowledge Media Institute. Within the OU he served on the Steering Group for OpenLearn, and as Director of SocialLearn. He served on the Steering Group who organized the 1st International Conference on Learning Analytics & Knowledge (LAK11), and is LAK12 Program Co-Chair.
Buckingham Shum, S. and Deakin Crick, R. (2012). Learning Dispositions and Transferable Competencies: Pedagogy, Modelling and Learning Analytics. Proc. 2nd International Conference on Learning Analytics & Knowledge. (29 Apr-2 May, 2012, Vancouver, BC). ACM Press: New York. Eprint: http://oro.open.ac.uk/32823
Ferguson, R. and Buckingham Shum, S. (2012). Social Learning Analytics: Five Approaches. Proc. 2nd International Conference on Learning Analytics & Knowledge, (29 Apr-2 May, Vancouver, BC). ACM Press: New York. Eprint: http://oro.open.ac.uk/32910
De Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L. (2011). Discourse-Centric Learning Analytics. Proc. 1st International Conference on Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff. ACM Press: New York. Eprint: http://oro.open.ac.uk/25829
Ferguson, R. and Buckingham Shum, S. (2011). Learning Analytics to Identify Exploratory Dialogue within Synchronous Text Chat. Proc. 1st International Conference on Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff. ACM Press: New York. Eprint: http://oro.open.ac.uk/28955