Talk on the future of learning analytics given at RMIT, Melbourne, on 13 March 2018.

1. Rebecca Ferguson, The Open University, UK
Preparing for
the future

2. Learning analytics
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.

3. Learning analytics help us
to identify and make sense
of patterns in the data
to improve our teaching,
our learning and
our learning environments

4. EU priority areas for education
• Open and innovative education and training, fully
embracing the digital era.
• Strong support for teachers, trainers, school leaders
and other educational staff.
• Relevant and high-quality knowledge, skills and
competences developed throughout lifelong learning.
• Focus on learning outcomes for
employability, innovation, active
citizenship and well-being and
inclusive education, equality,
equity, non-discrimination and
the promotion of civic
competences.

5. • Safety and wellbeing: all children
and young people are protected
from harm and vulnerable children
are supported to succeed with
opportunities as good as those for
any other child.
• Educational excellence
everywhere: every child and
young person can access high-
quality provision, achieving to the
best of his or her ability regardless
of location, attainment and
background.
• Prepared for adult life: all 19-year-
olds complete school or college
with the skills and character to
contribute to the UK’s society and
economy and are able to access
high-quality work or study options.

6. RMIT exists to create
transformative experiences for
our students, getting them ready
for life and work, and to help
shape the world with research,
innovation, teaching and
engagement.
RMIT has a unique approach to
meeting the challenge of being
ready for life and work: we offer
an education deeply grounded in
ideas and cross-disciplinary
understanding, applied through
innovative, enterprising practice
to solving problems and meeting
the needs of our community.

7. Preparing for the future
careers2030.cst.org/jobs

8. 12 years of change
2012: ‘Year of the MOOC’
2007: Launch of the iphone
2006: First tweets

9. Priority areas for education and training
9
Bringing together higher education, schools & workplace learning
Building networks that outlived the project’s funding period
Helping to develop learning analytics capability
Creating and sharing resources
Developing visions of the future and agreeing how to work towards them
http://www.laceproject.eu/

10. Full report
bit.ly/28X5tq7
Visions of
the future

11. Provocation 1:
Learners are
monitored by
their learning
environmnent

12. Provocation 2:
Learners’ personal
data are tracked

13. Provocation 3:
Analytics are
rarely used

14. Provocation 4:
Learners
control
their own
data

15. Provocation 5:
Open systems
are widely
adopted

16. Provocation 6:
Learning analytics are essential tools

17. Provocation 7:
Analytics help
learners make the
right choices

18. Provocation 8:
Analytics have
largely replaced
teachers

19. New provocations from Neil Selwyn
• Socially sympathetic
design
• Transparency of
algorithms
• Student control
• Sharing the profits of
learning data
• Working towards a
better public
understanding of
analytics
• Seeing ethics in
terms of power
Image: Neil Selwyn, LAK18

20. LAEP
Learning analytics for European education policy
• What is the current state of
the art?
• What are the prospects for
the implementation of
learning analytics?
• What is the potential for
European policy to be used to
guide and support the take-up
and adaptation of learning
analytics to enhance
education in Europe?

21. Strategy
Research and development
Infrastructure
Context
Standards
Skills
Outreach
Action for analytics

22. Strategy
• Align work on learning analytics with
strategic objectives and priority areas for
education and training
• Develop a roadmap for learning analytics
• Assign responsibility for development of
learning analytics
• Identify and build on work in
related areas and other countries
• Build on learning analytics
work to develop new priorities
Example of a framework for learning analytics: Siemens, G., Gašević, D., Haythornthwaite, C.,
Dawson, S., Buckingham Shum, S., Ferguson, R., Duval, E., Verbert, K. & Baker, R.S.J.d. (2011).
Open Learning Analytics: An Integrated and Modularized Platform. Download from solaresearch.org

23. Research and development
• Develop pedagogy that
makes good use of analytics
• Develop analytics that
address strategic objectives
and priorities
• Develop technology that
enables deployment of
analytics
• Develop frameworks that
enable development of
analytics
Image: sheilaproject.eu

24. Infrastructure
• Increase data-handling capability
• Create organisational structures to
support use of learning analytics
• Use Evidence Hub to identify areas for
development
• Develop methods of
sharing experience
and good practice

25. Context
• Align learning
analytics work with
different
sectors of education
• Develop practices that
are appropriate to
different contexts
• Identify successful
financial models

26. Standards
• Adapt and employ
interoperability standards
• Develop and employ
ethical standards,
including data protection
• Align analytics with
assessment practices
• Develop a robust quality
assurance process
• Develop evaluation
frameworks

27. Skills
• Identify the skills required in
different areas
• Train and support educators
to use analytics to support
achievement
• Train and support
researchers and developers
to work in this field
• Develop and support
educational leaders to
implement these changes
• Educate learners to use
analytics to support their own
achievement

28. Outreach
• Engage stakeholders
throughout the learning
analytics process
• Support collaboration
with commercial
organisations
• Promote awareness of
learning analytics

29. Stay connected
solaresearch.org • LAK conferences • LASI events • LACE

30. slideshare.net/R3beccaF
r3beccaf.wordpress.com/
twitter.com/R3beccaF