UK SoLAR Flare: 19 November 2012

UK solar flareTogether with Simon Buckingham Shum (OU), Doug Clow (OU)  and Sheila MacNeill, I co-chaired today’s UK SoLAR Flare, the first UK gathering dedicated to Learning Analytics.

Under the auspices of Society for Learning Analytics Research and sponsored by The Open University & JISC Centre for Educational Technology and Interoperability Standards, this fully subscribed inaugural UK Flare invited 50 participants to learn what is going in the country, and forge valuable new connections.

At the event, Sheila MacNeill from JISC-CETIS  launched their new series of reports on the state of the art in Learning Analytics – and where the future may go.

For podcasts of the sessions see:

Introduction from Simon Buckingham Shum  (17 mins)

Short introductions to individuals’ research
0-2 mins Simon Buckingham Shum (The Open University)  Network learning analytics, disposition analytics;
5-8 mins Nicola Avery (Medicine and Healthcare Products Regulatory Agency) Text analysis of feedback
8-13 mins Doug Clow (The Open University) Data wrangling
13-18 mins Adam Cooper (JISC CETIS) Exponential random graph models and network analysis
19-22 mins John Doove (SURF) Diverse learning analytics projects in the Netherlands funded by SUR
23-26 mins Cath Ellis (University of Huddersfield) Evaluation of the benefits of electronic assessment management (including emotion and motivation)
26-33 mins Rebecca Ferguson (The Open University) Social learning analytics
33-37 mins Dai Griffiths (University of Bolton) Tracking how models of learning are changing
37-42 mins Martin Hawksey (JISC CETIS) MOOC analytics
42-47 mins Jean Mutton (University of Derby) Identifying student engagement and students at risk
47-50 mins Jonathan San Diego (King’s College, London) Analytics and learning design
51-55 mins Mark Stubbs (Manchester Metropolitan University) Student satisfaction data collection tools
56-61 mins Annika Wolff (The Open University) Predictive modelling and retention
61-65 mins Chris Ballard (Tribal Labs) Predictive models to visualise student success

Feedback on group discussions
0-3 mins retention and success
3-6 mins dashboards
6-9 mins issues with retention and success analytics
9-15 mins learning analytics and pedagogy
16-22 mins data sources

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