The document discusses learning analytics, outlining its definition, uses, and the potential benefits for learners and educators, such as monitoring progress and optimizing learning environments. It emphasizes the importance of aligning analytics with pedagogical goals and explores the ethical considerations and diverse data sources involved in the analytics process. Additionally, it provides examples of how learning analytics can be integrated within various educational contexts, including MOOCs and library services.

1. Learning analytics:
answering the FAQs
Rebecca Ferguson
The Open University
SCONUL: June 2014

2. Take a minute to write down
or tweet the three questions
that would head your list of
FAQs about learning analytics
#sconulfaqs

3. Who are you?
• The Open University: largest in Europe
• Making use of data for more than 40 years
• Informal learning: iTunes, YouTube…
• MOOCs on FutureLearn and OpenLearn
• Learning analytics research / events
• LACE project

4. What are analytics?
High-level figures
Brief overview for internal and external reports
Academic analytics
Figures on retention and success, for the institution to
assess performance
Educational data mining
Searching for patterns in the data
Learning analytics
Use of [big] data to provide actionable intelligence for
learners and teachers

5. Is there a precise definition?
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.

6. Why do learners use analytics?
• Monitor their own activities and interactions
• Monitor the learning process
• Compare their activity with that of others
• Increase awareness, reflect and self reflect
• Improve discussion participation
• Improve learning behaviour
• Improve performance
• Become better learners
• Learn!

7. Why might I use analytics?
• Monitor the learning process
• Explore student data
• Identify problems
• Discover patterns
• Find early indicators for success
• Find early indicators for poor marks or drop-out
• Assess usefulness of learning materials
• Increase awareness, reflect and self reflect
• Increase understanding of learning environments
• Intervene, advise and assist
• Improve teaching, resources and the environment

8. Can you give me an example?
• Aligned with
clear aims
• Huge and
sustained effort
• Agreed proxies
for learning
• Clear and
standardised
visualisation
• Driving
behaviour at
every level
Individual assessment within cohort

9. Is that an ideal example?
Can we achieve this?
• Aligned with clear aims
• Huge and sustained effort
• Agreed proxies for learning
• Clear and standardised visualisation
• Driving behaviour at every level
Can we avoid this?
• Instructivist approach
• Stressed, unhappy learners
• Analytics with little value for learners or teachers
• Omission of key areas, such as collaboration

10. Don’t start with the data –
start with the pedagogy
How do people learn?
How can I use data to facilitate that process?
Social learning analytics:
How do people learn socially & in social settings?
How can I use data to facilitate that process?
How could we achieve that?

11. What questions should I ask?
• Which elements are learners struggling with?
• Which sections engage them the most?
• What prompts them to ask questions?
• How are they navigating resources?
• What misconceptions have they shown?
• Are there any accessibility issues?
How can analytics be used to
achieve desired learning outcomes?

12. • Demographic data
• Calendar information about assignments
• VLE activity data (including forums).
• Lists of required reading
• Library resources usage data
• Library helpdesk enquiries
• Library website usage and analytics data
• Assessment results
• User survey results
• Student retention and attainment data
What data could I use?

13. Does HE use learning analytics?
Purdue
University

14. SNAPP:
British Columbia
Are all analytics like that?

15. Disparate data
VLE (Moodle) data
Survey data
Help desk data
Library data
Assessment data
Registration data 250,000 students
around the world
Faculty expertise
Learning design
Learning outcomes
Assessment strategy
Module connections
Resource understanding
Data
Wranglers
Do you have an OU example?

16. Resource page? Sub page? URL?
Significance of dates?
What does a Wrangler do?

17. Reach agreement on conventions
80% agreed or strongly agreed that….
Is that
80% of registered students?
80% of those who completed the survey?
80% of those who completed both survey and course?
Or is it
80% of survey respondents who completed the
course and did not select ‘not applicable’
What else do Wranglers do?

18. Relate analytics to learning design
How many forums?
What were their roles?
How were they timetabled?
Anything else?

19. Support, not surveillance
Reporting at module level, not individual level
Survey responses kept apart from activity data
Making data accessible, not overwhelming
Negotiating meaning, not dictating interpretation
Are there any ethical issues?

20. Shared knowledge building
Is it all about wrangling?

21. Shared knowledge building
Does your library use analytics?

22. What about informal learning?

23. Social
Network
Status
Domain
Expert
Reputation

24. Massive
thousands may sign up
Open
no payment is required
Online
resources on the Internet
Courses
time-bounded cohorts
Any links with MOOCs?
(What are MOOCs?)

25. Introduction to
Forensic Science
University of Strathclyde
You have been actively engaged in
the discussions, which is excellent,
thank you, but with more than
23,000 participants it means that our
responses and comments risk
getting lost.
Analytics could help to filter discussions
How could MOOCs use analytics?

26. Introduction to
Forensic Science
University of Strathclyde
This will be primary school material
for some of you and exactly the
opposite for others. It is just not
possible to tailor the material to
each of you […]
How could MOOCs use analytics?
Analytics could help to group learners

27. Analytics could help to focus attention
How could MOOCs use analytics?

28. Helping to identify useful analytics
What do learners need to know in order to
network, collaborate, browse or reflect?
What do educators need to know to support them?
Helping to identify gaps in the data
Which data do we need to collect?
Helping to identify gaps in our toolkit
Which design elements can we look at easily?
Which ones still pose problems?
Any links with learning design?

29. Helping to frame and focus analytics questions
What did they learn?… in relation to learning outcomes
Were they social?... when they were collaborating
Did they share links?... when encouraged to browse
Did they return to steps?... when encouraged to reflect
Helping to identify appropriate forms of analysis
The same content, but with a focus on
Number of visits if content
Length, quality, number of comments if conversational
Dwell time and repeat visits if reflection
Any links with learning design?

30. How are analytics used in libraries?
Mission
To impact student measures of satisfaction
To demonstrate value-added to users
To inform and justify policy
Teaching and learning
To target and assess interventions
To position library teaching effort
To track user journeys
Recommendations
To promote use of content beyond reading list
To link discovery, lists and recommendations
To surface unused content jisclamp.mimas.ac.uk

31. How are analytics used in libraries?
Collection management
To deliver better / best value for money
To promote evidence-led decision-making
To identify how faculties use the library
Data
To merge data from multiple systems
To incorporate web analytics
To provide compelling visualisations
Service
To correlate feedback, enquiries and collection strength
To understand access patterns
To target skills development jisclamp.mimas.ac.uk

32. How are you using analytics?
Collection management
Mission
Data
Teaching and learning
Recommendations
Service
jisclamp.mimas.ac.uk

33. bit.ly/1130R0Y
bit.ly/VUGBfJ
Where can I find out more?
jisclamp.mimas.ac.uk
bit.ly/1qulB06