![Learning analytics is…
• Learning analytics is the measurement,
collection, analysis and reporting of data
about learners and their contexts for the
purposes of understanding and optimising
learning and the environments in which it
occurs
[LAK2011]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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LTAG Horizon Scanning
- 1. Learning Analytics LTAG Horizon Scanning Anne-Marie Scott (IS) 13 June 2013
- 2. Learning analytics is… • Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and optimising learning and the environments in which it occurs [LAK2011]
- 3. Learning analytics is… • Is the analysis of many kinds of learner- produced and learner-related data • Seeks to monitor learner activity and progress and to predict learner outcomes • Enables interventions and decision making about learning by instructors and students
- 4. It can be used for… • Sense making • Identifying students ‘at-risk’ • Driving pedagogic change
- 7. What does it mean for UoE?
- 8. • Increase student satisfaction with academic and pastoral support • Increase the level of overall satisfaction expressed in responses to the NSS, PTES, PRES student surveys to at least 88% [University Strategic Plan 2012-2016]
- 9. Opportunities / Barriers • Much of what can be measured easily is not necessarily of use • What is student ‘success’? • Do we understand what data / measurements are significant for our students? • Ethical issues • Data literacies
- 10. Opportunities / Barriers • Increased use of VLEs – ECA portfolio – eeMec – eeVec – Learn – Moodle
- 11. Opportunities / Barriers 71% 2012/13 63% 2011/12 54% 2010/11 48% 2009/10 Schools with <70% courses in Learn ECA 47% Law 4% MVM 3% Dick Vet 36% Clinical Sciences 34% Informatics 8% Growth of academic courses in Learn
- 12. Opportunities / Barriers • Other data – Library usage – Computing labs? – Wireless network?
- 13. Opportunities / Barriers • Vendor growth – Course Signals – Tribal Student Insight – Blackboard Analytics – Various retention systems packaged up as analytics (Starfish etc)
- 14. Final thoughts… • Big vs Small – What is possible / appropriate to do at an institutional level? – What is best done at a local level (School, programme, course)? • What do we want to predict / change? • What are the ‘success’ criteria? • How is it measured?
Notas do Editor
- PredictionInterventionPersonalisationAdaptation
- What is student ‘success’Pass?Pass above average?Exceed individual expectation?
- Tools within the VLEs (SNAPP, Retention Center, MVM efforts)