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England (south)
Thursday 12 July
Exploring learning analytics
Karl Molden – Senior Analyst, University of
Greenwich
»22,000 students
»4 Faculties / 24 Departments
»3 campuses in SE London and Kent
University of Greenwich
»“… the measurement, collection, analysis and reporting of data
about learners and their contexts, for purposes of
understanding and improving learning and the environments in
which it occurs…”
Learning analytics and knowledge conference, 2011
»At Greenwich we want to maximise student engagement so
that retention, achievement and employability are optimised
What is it?
Learning analytics
»Fits within a programme of work looking at factors affecting
student achievement:
› Teaching methods
› Value-added
› Commuter students
Wider context
Learning analytics
»Part of an ongoing process of developing the institution’s data
capabilities
› Data warehouse
› Automation of reporting
› Dashboards
› Analytics
Wider context – data/technology
Learning analytics
»Part of Jisc learning analytics network since 2015
»One of thirty institutions currently working on / looking at
implementing Jisc learning analytics solutions
»Part of smaller groups focussed on implementation in
September and also longer term developments
jisc.ac.uk/rd/projects/effective-learning-analytics
https://analytics.jiscinvolve.org/wp/
Wider context – Jisc project
Learning analytics
»Institutional readiness review
»Data analysis and prototyping to fit Jisc definitions
› Student data
› VLE
› Attendance
»Testing and trials of Jisc software with staff
»Feedback into Jisc development cycle
»Governance documentation
Project so far
Learning analytics
»Preparation for roll-out in September
› Finalisation of data connections
› Linking Greenwich systems to Jisc systems
› Training materials
› Communications package
› Pilot of student application
Current work
Learning analytics
»Assessment of success of September roll-out
»Library data
»Predictive modelling
»Bespoke analysis via data extracted through API
»Further work with Jisc – continuing to develop processes
and systems
The future
Learning analytics
»Senior management buy-in from outset
»Faculty staff kept up-to-date on progress
»Training of wider academics has begun
»Student union has been consulted at several points in project
»Student representation on project steering group
Staff/student engagement
Learning analytics
»Project board chaired by Deputy vice chancellor
»Reports into our IT strategy board
»Policy documents approved and published – based on
Jisc template
»Data security compliance
»GDPR
»Ethics
Governance
Learning analytics
»Maximising engagement with the system
»How to use the data to ‘nudge’ students?
»Monitoring success
»Moving from experimentation to implementation
»Supporting key staff involved in roll-out
»Getting the right staff on board
»Ethics
Challenges
Learning analytics
»Getting this to work is a long process!
»Needs a wide mix of staff involved and senior buy-in
»Need accurate data
»Wider academic/student community needs to support the
project aims
»Working as part of a community has great advantages
Lessons
Learning analytics
“Prediction is very difficult,
especially about the future”
Niels Bohr
Questions?
Except where otherwise noted, this work is licensed under CC-BY-NC-ND.
Karl Molden
Senior analyst – Planning & Statistics
k.molden@Greenwich.ac.uk
Thankyou

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Exploring learning analytics

  • 2. Exploring learning analytics Karl Molden – Senior Analyst, University of Greenwich
  • 3. »22,000 students »4 Faculties / 24 Departments »3 campuses in SE London and Kent University of Greenwich
  • 4. »“… the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and improving learning and the environments in which it occurs…” Learning analytics and knowledge conference, 2011 »At Greenwich we want to maximise student engagement so that retention, achievement and employability are optimised What is it? Learning analytics
  • 5. »Fits within a programme of work looking at factors affecting student achievement: › Teaching methods › Value-added › Commuter students Wider context Learning analytics
  • 6. »Part of an ongoing process of developing the institution’s data capabilities › Data warehouse › Automation of reporting › Dashboards › Analytics Wider context – data/technology Learning analytics
  • 7. »Part of Jisc learning analytics network since 2015 »One of thirty institutions currently working on / looking at implementing Jisc learning analytics solutions »Part of smaller groups focussed on implementation in September and also longer term developments jisc.ac.uk/rd/projects/effective-learning-analytics https://analytics.jiscinvolve.org/wp/ Wider context – Jisc project Learning analytics
  • 8. »Institutional readiness review »Data analysis and prototyping to fit Jisc definitions › Student data › VLE › Attendance »Testing and trials of Jisc software with staff »Feedback into Jisc development cycle »Governance documentation Project so far Learning analytics
  • 9. »Preparation for roll-out in September › Finalisation of data connections › Linking Greenwich systems to Jisc systems › Training materials › Communications package › Pilot of student application Current work Learning analytics
  • 10. »Assessment of success of September roll-out »Library data »Predictive modelling »Bespoke analysis via data extracted through API »Further work with Jisc – continuing to develop processes and systems The future Learning analytics
  • 11. »Senior management buy-in from outset »Faculty staff kept up-to-date on progress »Training of wider academics has begun »Student union has been consulted at several points in project »Student representation on project steering group Staff/student engagement Learning analytics
  • 12. »Project board chaired by Deputy vice chancellor »Reports into our IT strategy board »Policy documents approved and published – based on Jisc template »Data security compliance »GDPR »Ethics Governance Learning analytics
  • 13. »Maximising engagement with the system »How to use the data to ‘nudge’ students? »Monitoring success »Moving from experimentation to implementation »Supporting key staff involved in roll-out »Getting the right staff on board »Ethics Challenges Learning analytics
  • 14. »Getting this to work is a long process! »Needs a wide mix of staff involved and senior buy-in »Need accurate data »Wider academic/student community needs to support the project aims »Working as part of a community has great advantages Lessons Learning analytics
  • 15. “Prediction is very difficult, especially about the future” Niels Bohr
  • 17. Except where otherwise noted, this work is licensed under CC-BY-NC-ND. Karl Molden Senior analyst – Planning & Statistics k.molden@Greenwich.ac.uk Thankyou

Editor's Notes

  1. Use for North and South England
  2. Reposition /resize /remove text box as required
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