This document discusses the need for data interoperability to enable lifelong learning analytics. It notes that currently most learning analytics focus on understanding and optimizing formal learning environments rather than the learner perspective across multiple contexts. The lack of interoperability between different education systems means data is often stored in incompatible ways, making analysis difficult. The document proposes using open standards like xAPI to better link learning data across systems and support personalized, lifelong learning through interoperable analysis.

1. D ATA I N T E R O P E R A B I L I T Y F O R
L E A R N I N G A N A LY T I C S A N D
L I F E L O N G L E A R N I N G
Kirsty Kitto
Queensland University of Technology
kirsty.kitto@qut.edu.au
@KirstyKitto
www.beyondlms.org

2. L E A R N I N G A N A LY T I C S ?
Learning analytics is the measurement, collection,
analysis and reporting of data about learners and their
contexts, for purposes of understanding and optimising
learning and the environments in which it occurs.
SoLAR definition
But very little emphasis upon
LA for learners at present

3. L E A R N E R S P E R S P E C T I V E
http://www.elearning.ac.uk/mle.html
W H Y D O N ' T
E - P O R T F O L I O S
E V E R TA K E O F F ?
T H A T S F R O M 2 0 0 6

5. N O I N T E R O P E R A B I L I T Y

6. W H AT H A P P E N S AT O N E P O I N T
I N T H AT L E A R N I N G J O U R N E Y ?

8. A D AY I N M Y L I F E W H E N D O I N G
L E A R N I N G A N A LY T I C S …
• jump for joy because you finally got
ethics approval for your current
research project
• spend ages trying to interface with
different APIs for different systems
• extract data that is somehow always
in slightly different form
• spend most of your time trying to
get it to look like your other data
sets so you can use existing tools
• give up and develop a new bespoke
solution
http://datascience.la/data-science-toolbox-survey-results-surprise-r-and-python-win/

9. T H E R E H A S T O B E A
B E T T E R WAY

10. xAPI could be it
but it would need to scale up fast

11. L I F E L O N G P E R S O N A L I S E D L E A R N I N G
the holy grail of education
a growing obsession with EdTech
impossible without data interoperability

12. A S A C O M M U N I T Y W E N E E D T O D E S I G N
F O R D ATA I N T E R O P E R A B I L I T Y
The killer app of xAPI

13. H O W ?

14. H I G H L E V E L
P R O F I L E S A N D
R E C I P E S
• Analysis across different
platforms made easier with
early planning
• Recipes are essential!
- Microblogging
- Content Creation
- Collaborative Content
Authoring
- Content Curation
- Association with Course, Team
and Instructor
Bakharia, Kitto, Pardo, Gašević, Dawson (In press). Recipe for Success —
Lessons Learnt from Using xAPI within the Connected Learning Analytics
Toolkit, Learning Analytics and Knowledge 2016 (LAK16)

15. O N E R E P O S I T O RY T H AT
I S P U B L I C LY AVA I L A B L E !

16. I N T E R E S T I N G A N A LY T I C S W I L L
E N C O U R A G E I N T E R O P E R A B I L I T Y

17. C L A T O O L K I T
D A S H B O A R D S
Reports generated about
- Activity
- Social Networks
- Content Analysis
www.beyondlms.orgOpen dashboards and learning analyticsAnyone could use them if they have the
same data structures…

18. L E S S O N S F R O M
T H E C L A T O O L K I T
P R O J E C T
• Context is not optional
‣ the more details the
better for learning
analytics
‣ it gets complicated!
• Recipes are essential for
keeping context under
control and reusable
• Same thing with timestamps
(time series common in LA)
https://github.com/kirstykitto/CLRecipe/blob/master/microblogging/
microblogging-tweetwithhashtagsandmentions.json

19. L I S T E N T O T H E L A C O M M U N I T Y
http://www.laceproject.eu/d7-4-learning-analytics-interoperability-requirements-specifications-and-adoption/

20. T H I S P R O J E C T I S S U P P O R T E D B Y T H E A U S T R A L I A N
G O V E R N M E N T ’ S O F F I C E F O R L E A R N I N G A N D T E A C H I N G
Q U E E N S L A N D U N I V E R S I T Y O F T E C H N O L O G Y:
Kirsty Kitto (Lead Investigator), Mandy Lupton, John Banks, Dann Mallet, Peter
Bruza, Aneesha Bakharia
U N I V E R S I T Y O F S O U T H A U S T R A L I A
Shane Dawson, Dragan Gašević (Uni of Edinburgh)
U N I V E R S I T Y O F T E C H N O L O G Y, S Y D N E Y
Simon Buckingham Shum
U N I V E R S I T Y O F S Y D N E Y
Abelardo Pardo
U N I V E R S I T Y O F T E X A S ( A R L I N G T O N )
George Siemens
I D 1 4 - 3 8 2 1 : E N A B L I N G C O N N E C T E D L E A R N I N G
V I A O P E N S O U R C E A N A LY T I C S I N T H E W I L D :
L E A R N I N G A N A LY T I C S B E Y O N D T H E L M S

21. www.beyondlms.org