1) The document discusses challenges in adopting learning analytics and proposes a policy framework to guide the process. 2) Key adoption challenges include developing leadership, engaging stakeholders, providing training in data literacy, and establishing policies. 3) The framework suggests mapping the political context, identifying stakeholders, desired behavior changes, and developing an engagement strategy. It also involves analyzing capacity and establishing monitoring frameworks. 4) The goal is to provide an inclusive adoption process that embraces the complexity of educational systems and promotes innovation.

1. Let’s get there! Towards policy for
adoption of learning analytics
Dragan Gašević
@dgasevic
Oct 26, 2017
LSAC 2017
Amsterdam, The Netherlands
http://sheilaproject.eu/

2. Current state
Understanding & supporting learning
Moving away from deficit models

3. Learning analytics is about learning
Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71.

4. Field of research and practice
Gašević, D., Kovanović, V., & Joksimović, S. (2017). Piecing the Learning Analytics Puzzle: A Consolidated Model of a Field of Research and Practice. Learning:
Research and Practice, 3(2), 63-78. doi:10.1080/23735082.2017.1286142

5. Our institution is in
early days of adoption

6. ADOPTION CHALLENGES

7. Current state – Oz and Europe
http://sheilaproject.eu/http://he-analytics.com

8. Adoption challenge
Leadership for strategic
implementation & monitoring
Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education – challenges and policies: a review of eight learning analytics policies. In Proceedings of the
Seventh International Learning Analytics & Knowledge Conference (pp. 233-242).

9. Adoption challenge
Equal engagement with
different stakeholders
Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education – challenges and policies: a review of eight learning analytics policies. In Proceedings of the
Seventh International Learning Analytics & Knowledge Conference (pp. 233-242).

10. Adoption challenge
Training to cultivate data literacy
among primary stakeholders
Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education – challenges and policies: a review of eight learning analytics policies. In Proceedings of the
Seventh International Learning Analytics & Knowledge Conference (pp. 233-242).

11. Adoption challenge
Policies for learning analytics practice
Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education – challenges and policies: a review of eight learning analytics policies. In Proceedings of the
Seventh International Learning Analytics & Knowledge Conference (pp. 233-242).

12. What’s necessary to move forward?

13. DIRECTIONS

14. Inclusive adoption process

15. Inclusive adoption process
http://sheilaproject.eu/

16. Inclusive adoption process
Macfadyen, L., Dawson, S., Pardo, A., Gašević, D., (2014). The learning analytics imperative and the sociotechnical challenge: Policy for complex systems. Research
& Practice in Assessment, 9(Winter 2014), 17-28.

17. Methodology
Literature
- Policy
- Adoption
Academic staff
- Survey
- Focus groups
Students
- Survey
- Focus groups
Senior managers
- Survey
- Interviews
Experts
- Group concept
mapping
Policy
framework
Institutional
policy/strategy
Other stakeh.
- Workshops
- Committees

18. SHEILA policy framework
http://sheilaproject.eu/

19. SHEILA policy framework
http://sheilaproject.eu/

20. SHEILA policy framework
http://sheilaproject.eu/

21. Map political context
Internal and external drivers for
learning analytics adoption

22. Map political context
One size fits all does not work in
learning analytics

24. Map political context
Opportunities to build learning
analytics on existing projects/practice

25. SHEILA policy framework
http://sheilaproject.eu/

26. Identify key stakeholders
The project sponsor on
the senior management team

27. Students’ perspective
Students expect the use of their data
provided ethics & privacy is assured

28. Students’ perspective
But, they are not sure if teaching staff
will know to use learning analytics

29. Teaching staff’s perspective
Concerned about their workload

30. Contradictory views
Students and teaching staff
don’t share the same perspectives

31. Experts’ perspective
Privacy and ethics are most important
but easy to implement

32. Experts’ perspective
Purpose, ethics, and privacy need to
be addressed first

33. SHEILA policy framework
http://sheilaproject.eu/

34. Identify desired behavior changes
Identify areas where decisions will be
informed by learning analytics

35. Identify desired behavior changes
Define implications for primary users

36. Identify desired behavior changes
Identification of possible
inadvertent consequences

37. SHEILA policy framework
http://sheilaproject.eu/

38. Develop engagement strategy
Alignment of learning analytics with
the wider institutional strategies

39. Develop engagement strategy
Secure funding, establish a working
group, and raise awareness

40. Develop engagement strategy
Select data that will be fed back to users
Avoid impression of surveillance
Prevent data overload

41. Develop engagement strategy
How interventions will be triggered
and who is responsible?

42. SHEILA policy framework
http://sheilaproject.eu/

43. Analyze internal capacity
Data storage, disposal, and
security evaluation

44. Analyze internal capacity
Human, financial, and
infrastructural capacity

45. Analyze internal capacity
What about empirical research about
data privacy?
Privacy paradox
Barth, S., & de Jong, M. D. T. (2017). The privacy paradox – Investigating discrepancies between expressed privacy concerns and actual online behavior – A
systematic literature review. Telematics and Informatics, 34(7), 1038-1058. https://doi.org/10.1016/j.tele.2017.04.013

46. Analyze internal capacity
What do we do with GDPR 2016/679?

47. Analyze internal capacity
Evaluate institutional culture
Trust in data
Decision-making based on data
Openness to changes and innovation

48. SHEILA policy framework
http://sheilaproject.eu/

49. Establish monitoring & learning frameworks
Highly immature and
few actual examples

50. Establish monitoring & learning frameworks
Establish qualitative and quantitative
indicators of success
Stage the process to recognize institutional development

51. Establish monitoring & learning frameworks
Seek feedback from primary users
through various channels

52. Establish monitoring & learning frameworks
Isolating the effect of learning analytics
against other initiatives

53. FINAL REMARKS

54. Embracing complexity of
educational systems

55. One size fits all does not work in
learning analytics

56. Critical role of leadership for adoption
of learning analytics

57. Promoting and supporting innovation

58. Let’s get there! Towards policy for
adoption of learning analytics
Dragan Gašević
@dgasevic
Oct 26, 2017
LSAC 2017
Amsterdam, The Netherlands
http://sheilaproject.eu/