Building a national learning analytics service. Presentation at UKSG in 3 June 2016

1. Paul Bailey, Senior Codesign Manager, Research and Development
Jisc Building a national learning analytics service

2. Outline
Background
Overview of the LearningAnalytics Service
A user view of the service
Library Analytics Labs
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3. About Jisc…
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It operates shared digital
infrastructure and services,
negotiates sector-wide deals
with IT vendors and commercial
publishers, and provides trusted
advice and practical assistance
for universities and colleges.
Jisc is the UK higher and
further education sectors’
not-for-profit
organisation for digital
service and solutions.
UKSG Building a national learning analytics service

4. Effective Learning Analytics Challenge
Rationale
Universities and colleges don't have enough useful data about students and how they are learning.
What they have they don’t analyse and interpret.They are missing opportunities to use technology to
provide feedback to students.They need to support staff who could be using analytics and a standard
set of tools and technologies to monitor and intervene.
Who it affects and how
Students are missing out on the possibility of an improved experience, better retention, and better
achievement.
Staff are missing the opportunity to develop skills to use analytics to improve support, teaching and
curriculum design.
Timescale
Pilot tools and metrics 1-2 years
Impact on retention, achievement and progression 3-4 years.
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5. Learning Analytics
What is learning analytics?
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6. 6
“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 – Society for Learning Analytics Research
UKSG Building a national learning analytics service

7. What do we mean by Learning Analytics?
The application of big data techniques such as machine based learning
and data mining to help learners and institutions meet their goals:
For our project:
» Improve retention (current project)
» Improve attainment (current project)
» Improve employability (future project)
» Personalised learning (future project)
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8. Retention
 178,100 students aged 16-18 failed to finish post-secondary school
qualifications they started in the 2012/13 academic year
 costing £814 million a year - 12 per cent of all government spending on
post-16 education and skills (Centre for Economic and Social Inclusion
 8% of undergraduates drop out in their first year of study
This costs universities around £33,000 per student
 students with 340 UCAS points or above were considerably less likely
(4%) than those with less UCAS points (9%) to leave their courses
without their award
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9. Attainment
 70% of students reporting a parent with HE qualifications achieved
an upper degree, as against 64% of students reporting no parent
with HE qualifications
 In all disciplines except Computer Science, Medicine and Dentistry,
and Physical Science, students with a parent with an HE
qualification were more likely to have achieved an upper degree
 Overall, 70% ofWhite students and 52% of BME students achieved
an upper degree
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10. Jisc’s Learning Analytics Project
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Three core strands:
Learning
Analytics Service
Toolkit Community
Jisc Learning Analytics
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11. Community: Project Blog,
mailing list and network events
Blog: http://analytics.jiscinvolve.org
Mailing: analytics@jiscmail.ac.uk
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12. http://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics
Toolkit: Code of Practice
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http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf

13. Toolkit: Learning analytics
http://repository.jisc.ac.uk/5657/1/
Learning_analytics_report.pdf
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The current state of play in UK higher
and further education

14. Toolkit: Learning Analytics in Higher Education: A
review of UK and international practice
Including case studies on
 Traffic Lights and Interventions: Signals at Purdue University
 Analysing use of theVLE at the University of Maryland, Baltimore
County
 Identifying at-risk students at NewYork Institute ofTechnology
 Fine-grained analysis of student data at California State University
 Transferring predictive models to other institutions from Marist
College
 Enhancing retention at Edith Cowan University
 Early alert at the University of New England
 Developing an ‘analytics mind-set’ at the Open University
 Predictive analytics at NottinghamTrent University
 Analysing social networks at the University of Wollongong
 Personalised pathway planning at Open Universities Australia
https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education
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15. Toolkit: Discovery Institutional Readiness
A process to support institutions to access their readiness to implement learning
analytics
 2015-16 –Three days onsite consultancy visit of workshops, focus groups and
interviews
Review of the reports form 26 institutions are being used to develop a new readiness
process
 2016 -17 – Overview workshop, introducing a “Readiness Toolkit” with a diagnostic
set of questions and support materials leading to implementation.
Further details will be announced via analytics @jiscmail.ac.uk
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16. Toolkit: Data structures and definitions
Contains the Student Unified Data Definitions and the
Jisc xAPI recipes (for learner activity data)
The main branch contains the latest agreed versions
»Other branches contain versions in development
Contributions and modifications are welcome!
https://github.com/jiscdev/learning-analytics
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17. Learning Analytics Service Architecture
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18. DataVisualisations straight out of theWarehouse
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19. Dashboards
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Visual tools to allow lecturers, module leaders,
senior staff and support staff to view:
» Student engagement
» Cohort comparisons
» etc…
Based on either commercial tools from Tribal
(Student Insight) or open source tools from
Unicon/Marist (OpenDashBoard)
Learning Analytics - Initial Meetings 2015

23. 23Learning Analytics - Initial Meetings 2015

24. Alert and Intervention System
Tools to allow management of interactions with students
once risk has been identified:
» Case management
» Intervention management
» Data fed back into model
» etc…
Based on open source tools from Unicon/Marist
(Student Success Plan)
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25. 25Learning Analytics - Initial Meetings 2015

26. First version will include:
» Overall engagement
» Comparisons
» Self declared data
» Consent management
Bespoke development by Therapy Box
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Student App
Learning Analytics - Initial Meetings 2015

27. Student Learning Analytics App 27
Stats – Provides an engagement
and attainment overview and
drilling down to gives
comparative activity graphs.
Log – Allows you to log time
spent on specified activities e.g.
reading for an assignment
Target – Allows you set personal
targets to improve your
engagement e.g. study for 10
hours this week

28. The Learning Analytics Project in numbers
Expressions of interest: 85
Engaged in activity: 35
Discovery to Sept 16: agreed (26), completed (14),
reported (10)
Learning Analytics Pre-Implementation: (12)
Learning Analytics Implementation: (7)
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29. Learning Analytics - Initial Meetings 2015 29
Phase 1&2
Sep 15 – Apr 16
Phase 2&3
Jan – Sept 16
Transition to
Service
Sept 16 – July 17
Jisc Learning
Analytics Service
Sept 2017

30. Building on the learning analytics service
 Freemium vs premium service
 Integration of third party products into the architecture
 Briefing day in April attended by 30 suppliers
 Supplier demos and panel at network meeting 22 June, Newman College,
Birmingham
 Analytics Labs
 Development teams work with data to produce new dashboards and
visualisations
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31. Analytics Labs – user stories approach
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32. Library Analytics Labs
 Open call for expressions of interest to join a team working on Library BI
Stories at 0.2 FTE, total estimated effort 15 days
 Both Product Owners and Sector Data Experts invited:
 Product Owner from the sector to steer which stories are of interest
 Sector Experts to understand what data sources are available & what is in the data
 JiscContracted Data transformation specialist (CETIS)
 Jisc Agile Scrum Master &Tableau User
 Teams receive experience and guidance of Agile working
 Option forTableau Desktop training to help with creating visualisations
 Apply at http://bit.ly/jisc_library_data_labs_applications
 Queries to siobhan.burke@jisc.ac.uk or myles.danson@jisc.ac.uk
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Call for Library LabTeams 20 July – 6 Oct

33. Contacts
Paul Bailey paul.bailey@jisc.ac.uk
Further Information:
http://www.analytics.jiscinvolve.org
Join: analytics@jiscmail.ac.uk
Student Learning Analytics App 33