KMi and OU a major player in Learning Analytics

Last week saw KMi and OU colleagues out in strength at the 1st International Conference on Learning Analytics & Knowledge, held at the outstanding Banff Centre in the Rocky Mountains outside Calgary. Learning Analytics is highlighted as a very hot topic in the EDUCAUSE/NMC Horizons 2011 report, reflecting the growing amounts of data that can be gathered about a learner’s history and likely intentions, across multiple platforms in their institution and the cloud.

The Horizons 2011 report introduces learning analytics as follows:

“Learning analytics loosely joins a variety of data-gathering tools and analytic techniques to study student engagement, performance, and progress in practice, with the goal of using what is learned to revise curricula, teaching, and assessment in real time. Building on the kinds of information generated by Google Analytics and other similar tools, learning analytics aims to mobilize the power of data-mining tools in the service of learning, and embracing the complexity, diversity, and abundance of information that dynamic learning environments can generate.”

The conference frames it thus:

“The growth of data surpasses the ability of organizations to make sense of it. This concern is particularly pronounced in relation to knowledge, teaching, and learning. Learning institutions and corporations make little use of the data learners “throw off” in the process of accessing learning materials, interacting with educators and peers, and creating new content. In an age where educational institutions are under growing pressure to reduce costs and increase efficiency, analytics promises to be an important lens through which to
view and plan for change at course and institutions levels. Corporations face pressure for increased competitiveness and productivity, a challenge that requires important contributions in organizational capacity building from work place and informal learning. Learning analytics can play a role in highlighting the development of employees through their learning activities.

In enterprise settings, information flow and social interactions can yield novel insights into organizational effectiveness and capacity to address new challenges or adapt rapidly when unanticipated event arise.

Thirdly, as we witness the expansion of learning and knowledge work beyond formal institutional boundaries, myriad platforms in the cloud hosting the activity of individuals will be providing/exchanging analytics.”

Myself and three OU colleagues on the Steering Cttee helped design the conference (Tony Hirst, GrĂ¡inne Conole and Martin Weller), and the conference saw Tony Hirst (Faculty Maths, Computing & Technology) keynoting on linked data mashups and social network analysis, Doug Clow (Inst. Educ. Technology) speaking on iSpot analytics on expertise, KMi’s Anna De Liddo and myself on discourse centric analytics, and KMi’s Rebecca Ferguson and myself on identifying exploratory dialogue in textchat.

I also contributed to the pre-conference workshop of about 50, on theory-based learning analytics, and to the pre-conference MOOC (Massive, Online Open Course) with the closing invited address on the future of learning analytics.

Plans are already underway for next year’s conference, EDUCAUSE are focusing on the topic in their forthcoming ELI webinar series, and there is activity within and between many universities, and the learning platform vendors, to develop the field.

As highlighted on many occasions including my talk (“Notes on the future”), there is a significant ethical dimension to designing meaningful analytics that do not reduce the richness of learning to an over-simplistic quantitative/semantic activity profile, simply because that is all the technology is capable of. Our challenge as researchers is to shape the field such that meaningful, authentic learning and sensemaking are the focus of analytics, moving beyond simple counting of low-level system events.

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