An introductory presentation on learning analytics. It includes a learning analytics maturity model and a schema for thinking about xAPI, data modelling, xAPI activity providers and how analytics should inform continuous improvement.

1. What does xAPI mean for your
Learning Analytics & Data
Strategy

2. Topics • The role of Learning Analytics
• A contemporary vision for Learning Analytics
• Measuring your current Learning Analytics maturity
• Current digital data traces
• What are the gaps in your organisation
• The role of xAPI in addressing gaps

3. Are you currently using
Learning Analytics?
How are they
being used?
What type
of analytics?
What insights are
being generated?

4. The role of
Learning Analytics

5. Learning Analytics is 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.
- Society for Learning Analytics Research
A workable definition for
Learning Analytics

6. What is the most
important current
measure?
For Learning in
your organisation:
Why does your organisation
position this as the most
important measure?
What might be a more
effective measure for
learning?

7. Role of Learning
Analytics
There are many reasons
why an organisation
would want to leverage
Learning Analytics.
Here are just a few….
1. Identifying what learning resources improve
team or organisational performance
2. Identifying if social platforms like Yammer
and Workplace are improving collaboration
3. Identifying if employees are enabled with
learning resources in their moment of need
4. Identifying usage and adoption of existing
learning technologies
5. Improving training return on investment by
checking what learning solutions deliver you
the best workplace outcomes

8. Which reason is most
important for your
organisation right now?
Identifying if social platforms like Yammer
improve collaboration at work
Identifying if employees are enabled with
learning resources in their moment of need
Identifying what learning resources improve
team or organisational performance
Identifying usage and adoption
of learning technologies
Improving training return on investment by
checking what learning solutions deliver
the best workplace outcomes
1
2
3
4
5

9. Vision for Learning
Analytics

10. Why a
vision? It is important that organisations implementing
learning analytics are aware of what vision they
have for its implementation, and have a clear
communication policy to explain how the data
is being used and why.

11. Prioritise projects that
form part of the learning
analytics initiative
3 reasons for a Vision Statement
2Manage concerns about
Privacy and the ethical
use of learning data
1
Guide ongoing implementation3

12. Components of a
Vision Statement
1. To be the best provider of digital
learning in your industry sector.
2. More engaging and unique
learning experiences.
3. Better marketing and matching
of new employees to existing
learning products.
4. Helping employees make good choices
about training opportunities and learning
for career progression.
5. Fine grained, real time segmenting of the
employee base and targeted training.
6. The identification of underserviced
employee groups.
7. Targeted development of new training
products to address identified gaps.
8. The building of professional ePortfolios
via Personal Learning Record stores that
employees can use to track competency
and job role proficiency.

13. A clear and well-articulated vision will help your
organisation build a comprehensive longer-term
plan. This will help to avoid the risk of a scatter gun
approach, where projects are picked up and then
dropped as a new digital learning fads emerge.
A cautionary note

14. Measuring Learning
Analytics Maturity

15. Aware
▪ Basic reports
▪ Log data
Experimentation
▪ Drill down reports
▪ Sample dashboards
Organisation
Employees
Manager
▪ Learner dashboards
▪ Manager dashboards
▪ BI reporting tools
▪ Cross-system data integration
Organisational
Transformation
▪ Predictive models
▪ Peronalised learning
▪ Measured by impact &
organizational strategy
Sector
Transformation
▪ Data sharing capabilities
▪ Innovation
▪ Open data
▪ Sector-wide agility
AdvancedBeginning
LimitedIntegrated
Team/OrganisationalImpact
Maturity of Learning Analytics Deployment Siemens, Dawson and Lynch (2013)

16. Learning Analytics Maturity
Where are you
on the Model?
Where do you want to
be in 12 months time?
Where do you want
to be in 3 years?

17. Digital data traces –
How to mature?

18. Data traces are possible because of:
Improved standards
New ways of
thinking about
learning
Advances in
technologies

19. Test a
hypothesis
• How can time to job
role proficiency be
reduced?
• How can the impact of
leadership programs
be improved?
Identify data
source
• Workplace activity
• Formal and informal
learning
• Business systems data
Establish xAPI
activity providers
• Learning Experience
Platforms
• Business apps
• Social collaboration
platforms - Yammer /
Workplace
Connect data
source to
repository
• Learning Record Store
• Extendable database
Creating a Data Trace

20. identifying learning data sources
Workplace
learning
Performance
Support Tools
Courses
Coaching /
mentoring
Evidence &
Engagement
Assessment
Recognition &
Motivation
Business
Systems
CRM
Helpdesk
HRIS

21. What kinds of data…..
Would you collect from assessments?
Would you collect from your Helpdesk? Would you collect from the CRM?
Would you collect from courses?
Would you collect from
performance support tools?

22. What the data
traces reveal? • Our sentiments
• Our attitudes
• Our social connections
• Our intentions
• What we know
• How we learn
• What we might do next?
A data trace reveals:

23. Why are each of
these important?
What data traces might you want to
collect in the future?
Which data traces do you collect now?

24. The role of xAPI
in plugging gaps

25. Have you heard of xAPI?
Can you explain xAPI to others?
Who is using / has experimented with xAPI?
Share your use case with folk on LinkedIn
Enter xAPI –
a universal
language for
Learning &
Performance

27. 5 hacks to measure learning
impact and tell stories with data
Develop a clear vision
for your learning
analytics project.
1

28. 5 hacks to measure learning
impact and tell stories with data
Pay close attention to your current data
sources, and map out data requirements
for any future learning solutions that you
decide to prioritise
2

29. 5 hacks to measure learning
impact and tell stories with data
Collect data that enables actionable insights
within the context of your learning analytics
vision….. so that meaningful correlations
can be extracted from the data.
3

30. 5 hacks to measure learning
impact and tell stories with data
Ensure interoperability between data
collected from multiple platforms (not just
the LMS) is a core requirement in any future
software acquisitions.
4

31. 5 hacks to measure learning
impact and tell stories with data
Construct a data model which enables
interoperability between current data sources that
are prioritised as important, and ensures long term
data interoperability in the future learning
paradigm.
5

32. James Stack
Director & Co Founder
james@obviouschoice.com.au
+61 4 39 393 961Contact
Details
www.obviouschoice.com.au