Learning Analytics from vision to implementation

1. Learning Analyticsfrom vision to implementation Trevor Meek, University of Bradford t.meek@bradford.ac.uk

2. Do we all agree on what LA are? “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Long & Siemens,2011) Easing the burden of accountability Help students succeed To argue for increased funding to support student preparation..

3. What is it all about? • What’s working and what is not working? • Student retention and institutional auditing… using data to inform the process and practices of higher education.

4. Activity 1 In some cases it is doing something about what we already know….. What are the top 3 strategic challenges to starting out with learner analytics?

5. The Challenge • Acceptance • Variability • Belief • Buy-in • Costs (/benefit) • Security • Legality • Longevity

6. Can it be this simple? Use data to create a SSP… (Student Success Plan) Does it NEED to be dynamic?

7. Who are you? Practitioner Researcher

8. International Perspectives

9. International Commonality Predicting student potential Identify effective instructional techniques Analysis of on-line and off-line data Analysing Assessment data Testing and Evaluation of curricula Note these very closely follow the IBM predictions of strategic success (2001)

10. Activity 2 From your list of strategic challenges (Activity 1) how do you overcome the most demanding of the three? “Selling” the concept to Faculty Increasing organisational productiviy

11. What we need… • Strategy • Sustainability • Belief • Use • Longevity (process/models) • Support • IT, Core staff, Management, Students

12. Activity 3 What are the top 5 operational hurdles to implementing learning analytics? Predictors of success vary from institution to institution From.. Faculty to Faculty From course to course…. From Semester to Semester External factors – what if I change x.

13. Implementation • Try – something! • Toe in Water • Planning • Test • Evaluate • Model – local • National/International initiatives • Research and innovate

14. What do we need to deliver? To students…? Personlised learning (Knowledge gap analysis) Learning resources Increased reflection Behaviour traits – “Encourage change…” Who is best placed/going to do this? How will we measure the effect? Blind trial? ????!!!!!

15. Conclusions Pick a track.. And GO! What ever the mechanics of starting are…

16. But wait….. Must we do this? Should we do it? Would we be neglectful not doing it? How accountable are we for accuracy What if we get it wrong?

17. The bigger picture of Big data Why not a World Database: Predicting future changes in pedagogic practice: True Internationalisation!

18. Ponderances… Learning analytics offers HEI’s a valuable tool in their on-going efforts to select actions that are “achievable within the capacity of the organization to absorb change and resource constraints” (Kavanagh & Ashkanasy, 2006) Effective institutions have “ a campus ethos devoted to student success “. (Gibbs,2010) Create a sense of urgency and hence the necessary levels of motivation required for sustaining the change process…(Kotter,1996)

19. Final thoughts… • We have so much data… • Some of it might (at the moment) be less than robust • Some will be of good standing • Try something! • Experiment • Surprise yourself with what you can already do • Build, build , build on those experiences • Don’t wait for the boat to go out… • …because what is coming soon?

20. TEF • A shift from process-driven assurance to analysis of student academic outcomes. …builds on existing institutional activity to drive excellence and innovation in learning and teaching in the context of an institution’s own mission, location and modes of delivery, and the nature of their student body.