is about Embracing Complexity Dragan Ga evi @dgasevic 23 rd - - PowerPoint PPT Presentation

▶
is about embracing complexity
SMART_READER_LITE
LIVE PREVIEW

is about Embracing Complexity Dragan Ga evi @dgasevic 23 rd - - PowerPoint PPT Presentation

Oct 11, 2022 201 likes •724 views

Learning Analytics in Higher Education is about Embracing Complexity Dragan Ga evi @dgasevic 23 rd October 2018 NFETL Dublin, Ireland http://sheilaproject.eu/ Current state Understanding & supporting learning Moving away from

slide-1
SLIDE 1

Learning Analytics in Higher Education is about Embracing Complexity

Dragan Gašević @dgasevic

23rd October 2018 NFETL Dublin, Ireland

http://sheilaproject.eu/

slide-2
SLIDE 2

Current state

Understanding & supporting learning

Moving away from deficit models

slide-3
SLIDE 3

Our institution is in early days of adoption

slide-4
SLIDE 4

ADOPTION CHALLENGES

slide-5
SLIDE 5

Current state – Oz and Europe

http://sheilaproject.eu/ http://he-analytics.com

slide-6
SLIDE 6

Adoption challenge

Leadership for strategic implementation & monitoring

Tsai, Y. S., & Gašević, 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).

slide-7
SLIDE 7

Adoption challenge

Equal engagement with different stakeholders

Tsai, Y. S., & Gašević, 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).

slide-8
SLIDE 8

Adoption challenge

Policies for learning analytics practice

Tsai, Y. S., & Gašević, 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).

slide-9
SLIDE 9

DIRECTIONS

slide-10
SLIDE 10

Inclusive adoption process

slide-11
SLIDE 11

Inclusive adoption process

http://sheilaproject.eu/

slide-12
SLIDE 12

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.

slide-13
SLIDE 13

Methodology

Literature

  • Policy
  • Adoption

Academic staff

  • Survey
  • Focus groups

Students

  • Survey
  • Focus

groups

Senior managers

  • Survey
  • Interviews

Experts

  • Group concept

mapping

SHEILA framework Institutional policy/strateg y Other stakeh.

  • Workshops
  • Committees
slide-14
SLIDE 14

SHEILA framework

http://sheilaproject.eu/

Tsai, Y. S., Moreno-Marcos, P. M., Tammets, K., Kollom, K., & Gašević, D. (2018, March). SHEILA policy framework: informing institutional strategies and policy processes of learning analytics. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 320-329). ACM.

slide-15
SLIDE 15

SHEILA framework

http://sheilaproject.eu/

http://sheilaproject.eu/sheila-framework/

slide-16
SLIDE 16

SHEILA framework

http://sheilaproject.eu/

slide-17
SLIDE 17

Map political context

Internal and external drivers for learning analytics adoption

slide-18
SLIDE 18

http://davideldon.typepad.com/eldononline/2013/05/index.html

slide-19
SLIDE 19

SHEILA framework

http://sheilaproject.eu/

slide-20
SLIDE 20

Identify key stakeholders

The project sponsor on the senior management team

slide-21
SLIDE 21

Students’ perspective

Students expect the use of their data provided ethics & privacy is assured

slide-22
SLIDE 22

Students’ perspective

Do we have legitimate interests for use?

Cross-country differences in student expectations

slide-23
SLIDE 23

Teaching staff’s perspective

Concerned about their workload

slide-24
SLIDE 24

Experts’ perspective

Purpose, ethics, and privacy need to be addressed first

slide-25
SLIDE 25

SHEILA framework

http://sheilaproject.eu/

slide-26
SLIDE 26

Identify desired behavior changes

Identify areas where decisions will be informed by learning analytics

slide-27
SLIDE 27

Define implications for primary users

Dashboards can be harmful

slide-28
SLIDE 28

Define implications for primary users

Dashboards can be harmful

Can lower GPA

Chaturapruek, S., Dee, T. S., Johari, R., Kizilcec, R. F., & Stevens, M. L. (2018). How a Data-driven Course Planning Tool Affects College Students’ GPA: Evidence from Two Field Experiments. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale (pp. 63:1–63:10). New York, NY, USA: ACM.

slide-29
SLIDE 29

SHEILA framework

http://sheilaproject.eu/

slide-30
SLIDE 30

Develop engagement strategy

Alignment of learning analytics with the wider institutional strategies

slide-31
SLIDE 31

Develop engagement strategy

How interventions will be triggered and who is responsible?

slide-32
SLIDE 32

SHEILA framework

http://sheilaproject.eu/

slide-33
SLIDE 33

Analyze internal capacity

Data storage, disposal, integration, and security evaluation

slide-34
SLIDE 34

Analyze internal capacity

Human, financial, and infrastructural capacity

slide-35
SLIDE 35

Analyze internal capacity

Evaluate institutional culture

Trust in data Decision-making based on data Openness to changes and innovation

Macfadyen, L. P., & Dawson, S. (2012). Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan. Educational Technology & Society, 15(3).

slide-36
SLIDE 36

SHEILA framework

http://sheilaproject.eu/

slide-37
SLIDE 37

Establish monitoring & learning frameworks

Highly immature and few actual examples

slide-38
SLIDE 38

Establish monitoring & learning frameworks

Establish quantitative and qualitative indicators of success

Stage the process to recognize institutional development

slide-39
SLIDE 39

Establish monitoring & learning frameworks

Isolating the effect of learning analytics against other initiatives

slide-40
SLIDE 40

EPILOGUE

slide-41
SLIDE 41

Learning analytics principles

Incomplete data and human involvement Transparency of data collection, use, and sharing Good governance as the core of the approach

The University of Edinburgh (2017). Learning Analytics Policy, https://www.ed.ac.uk/academic-services/policies-regulations/learning-and- assessment/learning-analytics

slide-42
SLIDE 42

Learning analytics principles

Avoiding deficit models to address needs of all learners Algorithms can perpetuate bias Learning analytics not used to monitor staff performance

The University of Edinburgh (2017). Learning Analytics Policy, https://www.ed.ac.uk/academic-services/policies-regulations/learning-and- assessment/learning-analytics

slide-43
SLIDE 43

Learning analytics purposes

Quality, equity, personalized feedback, coping with scale, student experience, skills, and efficiency

The University of Edinburgh (2017). Learning Analytics Policy, http://www.ed.ac.uk/academic-services/projects/learning-analytics-policy

slide-44
SLIDE 44

Scott, A.-M. (2018, June 22). Learning Analytics Policy Development. Retrieved June 27, 2018, from https://ammienoot.com/brain-fluff/learning-analytics-policy- development/

slide-45
SLIDE 45

FINAL REMARKS

slide-46
SLIDE 46

Embracing complexity of educational systems

slide-47
SLIDE 47

Critical role of leadership for adoption

  • f learning analytics
slide-48
SLIDE 48

Development of culture for data-informed decision making

slide-49
SLIDE 49

Sign up for the SHEILA MOOC

Launch with edX planned in late November 2018

slide-50
SLIDE 50

Learning Analytics in Higher Education is about Embracing Complexity

Dragan Gašević @dgasevic

23rd October 2018 NFETL Dublin, Ireland

http://sheilaproject.eu/