Confronting Reality with… Big Data & Learning Analytics
We’ve just run this interactive symposium at the Assoc. Learning Technology Conference (“a confrontation with reality”), which went very well: 50% brief presentations, 50% open discussion on the many issues analytics raise. I was lucky enough to have Sheila McNeill from JISC CETIS reporting on the analytics landscape survey she’s been doing, plus key colleagues from different parts of the OU learning analytics operation – thanks to Naomi, Kevin, Richard and Rebecca!
This served to demonstrate how much we need to connect with each other, with the next opportunity being the UK SoLAR Flare meetup on 19 Nov. at Open U. Milton Keynes (details shortly). Here’s the abstract and opening slides…
Confronting Reality with… Big Data & Learning Analytics
Simon Buckingham Shum, Naomi Jeffrey, Kevin Mayles, Richard Nurse & Rebecca Ferguson
The Open University (KMI, IET, LTS & Library)
Sheila McNeill
JISC CETIS
BACKGROUND
We are experiencing an explosion in the quantity of data available online from archives and live streams. Learning Analytics is concerned with how educational research, and learning platform design, can make more effective use of such data (Long & Siemens, 2011). Improving outcomes through the analysis of data is of interest to researchers, administrators, systems architects, social media developers, educators and learners. Analytics are being held up by some as a way to confront, and tackle, the tough new realities of less money, less attention, and higher accountability for quality of learning.
IDEAS TO BE EXPLORED
Researchers and vendors are building reporting capabilities into tools that provide unprecedented levels of data on learners. This symposium will show what is possible, and what’s coming soon. What objections could possibly be raised to such progress?
However, information infrastructure embodies and shapes worldviews: classification schemes are not only systematic ways to capture and preserve, but also to forget, by virtue of what remains invisible (Bowker & Star, 1999). Learning analytics and recommendation engines are designed with a particular conception of ‘success’, driving the patterns deemed to be evidence of progress, the interventions that are deemed appropriate, the data captured and the rules that fire in software.
This symposium will air some of the critical arguments around the limits of decontextualised data and automated analytics, which often appear reductionist in nature, failing to illuminate higher order learning. There are complex ethical issues around data fusion, and it is not clear to what extent learners are empowered, in contrast to being merely the objects of tracking technology. Educators may also find themselves at the receiving end of a new battery of institutional ‘performance indicators’ that do not reflect what they consider to be authentic learning and teaching.
STRUCTURE OF SESSION
This Symposium will provide the opportunity to hear a series of brief presentations introducing contrasting perspectives, before the debate is opened to all. Speakers from a cross-section of The Open University will describe how we are connecting datasets, analysing student data and prototyping next generation analytics. Complementing this, JISC will present a national capability perspective, with an update on the JISC CETIS ‘landscape analysis’ of the field, which will clarify potential benefits, issues to consider, and help institutions to assess their current capability and possible next steps.
INTENDED OUTCOMES
Participants will catch up with developments in this fast moving field, through exposure to the possibilities of analytics, as well as issues to be alert to.
REFERENCES
Bowker, G. C. and Star, L. S. Sorting Things Out: Classification and Its Consequences. MIT Press, Cambridge, MA, 1999
Long, P., & Siemens, G. (2011). Penetrating the fog: analytics in learning and education. EDUCAUSE Review, 46(5), 31-40
Participant Bios:
Simon Buckingham Shum researches, teaches and consults on learning analytics, social learning media, collective intelligence and dialogue/argument visualization. He was Programme Co-Chair for the 2012 Learning Analytics conference, a co-founder of the new Society for Learning Analytics Research, and is a regular invited speaker on the topic including EDUCAUSE and Ascilite. His particular interests are in what learning analytics may be blind to, analytics for informal/social learning, and whether analytics can help build the learning dispositions and capacities needed to cope with complexity and uncertainty — the only things we can be sure the future holds.
Rebecca Ferguson is a research fellow in the UK Open University’s Institute of Educational Technology, focused on Educational Futures. She work as research lead on the SocialLearn team, developing and researching initiatives to improve pedagogical understanding of learning in online settings, to design analytics to support the assessment of learning in these settings, and to extend the university’s ability to support learning in an open world.
Naomi Jeffery is a statistician at the Open University. She builds models of the factors influencing student success as part of the University’s processes aimed at enhancing curriculum quality and the student learning experience. In addition she produces diverse management information for colleagues throughout the institution. She is particularly interested in bridging the gap between research advances and supporting practice and also in the visualisation of learning analytics.
Sheila MacNeill is currently an Assistant Director with JISC CETIS (one of the JISC Innovations Support Centres). Her work in CETIS centres around developments related to teaching practice e.g. learning design; educational content related specifications; enhancement of VLEs e.g. widgets; digital literacies and learning analytics.
Kevin Mayles is Senior Manager, Learning and Teaching, Open University. Having held a number of roles focused on increasing the use of educational technologies at the Open University for the last year Kevin has lead a strategic learning analytics project aimed at significantly improving the institution’s ability to make use of the data it holds about its students and their engagement with learning systems. This has included making enhancements to the analytics capabilities tied to the university’s VLE, which is based on the Moodle platform.
Richard Nurse is Head of Digital Services Development at the Open University Library. He has been involved with library technology for more than twenty years in both academic and public libraries. Richard was Project Director on the JISC-funded RISE (Recommendations Improve the Search Experience) project that investigated how activity data from user interactions with library resources could be used to drive recommendations. Recently he has been involved with several other JISC-funded projects at the Open University (e.g. TELSTAR, LUCERO, MACON and STELLAR). His current interests include understanding how library activity data can be used both as a management tool to drive service improvement and as a tool to provide users of those services with choices that can improve their study experience.
Oct 15th, 2012 at 4:32 pm
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