As training, education, teaching and learning are constantly adapting to new technological developments it is not surprising that in the dawning age of data these areas are finding new ways to engage learners, provide teachers and learners with new insights about learning, and to find new ways to recognise and acknowledge learning. In an time when we might be considered as “always-on” and generating data in unprecedented volumes we are possibly more able to engage in more organic learning activities that do not require high-stakes testing regimes for us to evidence our learning. This session will consider the more recent developments in data-informed learning and teaching, learning analytics; and new forms of credentials as they influence our experience of learning across a range of contexts. Presented at Forward Government Learning Forum 2016 (Canberra for the ARK Group) and at Digicon 2016 for DLTV (Swinburne, Melbourne).

1. Big Data, Analytics
and
the Future of
Learning
Kim Flintoff
DLTV Digicon 2016
July 2016, Melbourne

2. Abstract
Einstein's ideas were pivotal in shifting the way we think about the physical world -
from the Newtonian to the Quantum models - in turn this changed the way we think
about the world and allowed us to develop new ways of engaging with the world.
We are at a similar juncture now with the Information Age and the global Internet of
Everything. The development of computational technologies allows us to think about
and to make meaning from data about the world in what might be called the age of
algorithms and computational thinking.
Data science, conducted with global computational resources changes the way we
think about, define and solve problems; and in turn, the ways in which we learn.
An age of creativity for research teams working in partnership with computational
resources may be upon us, extending data science impacts across all fields.
Einstein Schrödinger
Gödel Bohr

3. Presentation Timeline
Building a
Digital
Learning
Ecosystem
Learning
Analytics
Data-
Informed
Learning
and Teaching
Data Ethics,
Privacy and
Security
DiscussionNew forms of
Credentials

4. TL@C is a university-wide strategy which will apply innovative thinking to our
learning and teaching. It will enable us to:
•evolve a contemporary student experience,
•align our graduate outcomes with the expectations of employers, and
•remain highly competitive in a dynamic global market.
Transforming Learning
Learning Futures
Learning at Curtin is
"on your terms"!
Personal, collaborative,
innovative, richly interactive,
flexible and, above all, global.

5. Curtin Converged
Learning Futures
The new Curtin model for
Teaching and Learning is Curtin
Converged, a mix of traditional
lectures, flipped-classes,
technology enriched
environments and distributed
learning techniques (Massive
Online Open Courses (MOOCs)
and high-end video and 3-D
technologies) that actively
engage students whether they
attend classes on campus or
from another location.

6. Digital Learning Strategy
Learning Futures
The purpose of this strategy is to re-imagine the provision of digitally delivered
learning focussing on transformed processes, innovative recognised credentialing
and the adaptive business models needed to implement change. The scenarios
highlight the need for a digitally mature organisation with staff equipped with the
necessary skills to lead, create and facilitate digital learning in all modes.

7. Digital Learning @ Curtin
Learning Futures
The strategy is based on eight transformational pillars:

8. Credentialling
Learning Futures

9. Credentialling
Learning Futures

10. Credentialling
Learning Futures

11. Big Data and Computational Capacity
Institute for Computation, CISCO IoT Innovation Hub, Pawsey Supercomputing Centre
Computation is an increasingly
important activity in most disciplines,
leading to new fields such as
computational science and
engineering, computational
humanities, computational finance and
many others.
Universities have found it difficult to
bring these inherently cross-discipline
subjects into the curriculum. By
bringing together the leading
computational researchers at Curtin,
the institute is looking to build the
computational skills across the entire
university community.
BIG DATA ANALYTICS -- SIMULATION – VISUALISATION –
MODELLING AND OPTIMISATION -- EDUCATION
BIG DATA ANALYTICS -- SIMULATION – VISUALISATION –
MODELLING AND OPTIMISATION -- EDUCATION

12. 03Developing digitally capable learning spaces
From collaborative learning spaces to next generation learning spaces.
Curtin has redeveloped a
number of its existing teaching
and learning spaces with the
goal to transform learning at
the University. These vibrant
new spaces have been
designed to increase student
engagement, foster
collaboration between staff and
students and provide flexible,
technology-rich environments
which support active student
learning.

13. Timeline for development 01
Write your subtitle in this line
Flexible Learning Policy and Procedures
Blackboard
OLAS
The Move Online
2008
eLearning Advisory Team
Curtin Online
Open Universities Australia
Centre for eLearning
2009
eScholars
Unit Outline Builder
Innovation
2010

14. Course redesign
HIVE
ART
2014
Blackboard Analytics
Curtin Challenge Platform
Transformation
2013
ECHO 360
Curtin Teaching and Learning
iPad User Group
Restructure
2012
Blackboard 9.1
Blackboard Collaborate
Managed Hosting
Infrastructure
2011

15. Greater Curtin
2030
1,000,000 Learners
2017
elsie
Curtin Institute for Computation
Consolidation
2016
The Agency
edX Consortium
Review
2015
Education and Innovation
Social and Cultural Networks
Urbanisation
Business and Research
Medical School
Insights Centre for Learning Analytics

16. Learning Management
SystemsLearning Futures

17. Mobile Support
Learning Futures

18. Campus Quest
Learning Futures
Games and
gamification as
data streams in
the learning
analytics
ecosystem.

19. Curtin Challenge
Learning Futures
Welcome to Curtin Challenge, where you can develop your skills, build your
networks, and shape your future.
Challenge is a fun and interactive way to learn, and is just one of the many ways
Curtin University is transforming your University experience.

20. Curtin Challenge
Learning Futures

21. Curtin Challenge
Learning Futures
Aggregation of data allows
rich insights to emerge and
more unique and
personalised solutions

22. Learning Futures
Smart Classrooms of the Future

23. Learning Futures
Smart Classrooms of the Future

24. Learning Futures
Smart Classrooms of the Future – The Agency

25. Learning Futures
Smart Classrooms of the Future – The HIVE

28. Educational Data Mining
From “what was” to “what could be”
“Goals of EDM:
1. Predicting students’ future learning behavior by
creating student models that incorporate such detailed
information as students’ knowledge, motivation,
metacognition, and attitudes;
2. Discovering or improving domain models that
characterize the content to be learned and optimal
instructional sequences;
3. Studying the effects of different kinds of pedagogical
support that can be provided by learning software; and
4. Advancing scientific knowledge about learning and
learners through building computational models that
incorporate models of the student, the domain, and the

29. Ethics and data collection
Ethics, security and privacy
Key questions
Who is allowed to collect data?
What can they do with it?
What limits should be in place?
Who owns data?
What data should be public domain?
At what point does tracking become stalking?
At what point does data hoarding become a Photo credit: We are Anonymous - https://www.flickr.com/photos/equinoxefr/6856903841/

31. Value
Difficulty
Information
Optimization
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
Prescriptive
Analytics
Hindsight
Insight
Foresight
What happened?
Why did it happen?
What will happen?
What should
I do?
Future Focussed Analytics
From “what was” to “what could be”

32. Personalisation at scale
Learning Futures
Curtin University has
embarked on an
ambitious project to
expand its
educational offerings
to the world - aiming
to engage one
million learners
across the globe by
2017.

33. Digital Enhancements to Assessment
Learning Futures
1. An authentic learning experience involving digital media, with
2. Embedded continuous unobtrusive measures of performance,
learning and knowledge, which
3. Creates highly detailed, high resolution data records which can be
computationally analyzed and displayed so that
4. Learners and teachers can immediately utilize the information to
improve learning.
Gibson, D. C., & Webb, M. (2013). Assessment as, for and of 21st century learning. In International Summit on ICT in Education (p. 17). Torun: EDUsummIT 2013.
Retrieved from http://www.edusummit.nl/fileadmin/contentelementen/kennisnet/EDUSummIT/Documenten/2013/6_WCCE_2013-
_Educational_Assessment_supported_by_IT_1_.pdf

34. Good ByeSee you next time, have nice day