Overview of the Jisc learning analytics service

1. Paul Bailey, Senior Codesign Manager, Research and Development
Jisc learning analytics service
http://www.slideshare.net/paul.bailey/

2. Learning Analytics
What is learning analytics?
Learning Analytics Service

3. “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
Learning Analytics Service

4. Agenda
Learning Analytics Service
Predictive models
identify students at risk
Timely intervention by teaching or support
staff
Increased retention
Better understanding
of the effectiveness
of interventions
Rich data on student
activity and attainment
Data shared with
student prompting
them to change
own behaviour
Better student
outcomes
Data can be
explored to
understand patterns
of behaviour
Better understanding
of the behaviours
linked to differential
outcomes

5. Learning Analytics Service
VLE data
+
Student record system
+
Attendance data
+
Library data
Buildings data
+
Learning space data
+
Location data
Teaching quality data
+
Assessment data
+
Curriculum design data
Content data
+
Learning pathways data
Better retention
and attainment
Retention and
attainment
A more efficient
campus
Improved teaching
& curricula
Personalised and
adaptive learning
Efficient campus
Improving teaching
& curricula
Now
Learning
analytics
Institutional
analytics
Educational
analytics
Cognitive
Analytics and AI
Future

6. Paul Bailey, Senior Codesign Manager, Research and Development
Jisc learning analytics service
https://docs.analytics.alpha.jisc.ac.uk/docs/learning-analytics/Home

7. Effective Learning Analytics Challenge
Learning Analytics Service
Rationale
»Organisations wanted help to get started and have access to standard
tools and technologies to monitor and intervene
Priorities identified
»Code of Practice on legal and ethical issues
»Develop a core learning analytics service with app for students
»Provide a network to share knowledge and experience
Timescale
»2015-17 Development
»2017-18 Beta Service
»Aug 2018 Full Service

8. Community: Project Blog,
mailing list and network events
Blog: http://analytics.jiscinvolve.org
Docs: http://docs.analytics.alpha.jisc.ac.uk/
Mailing: analytics@jiscmail.ac.uk
Learning Analytics Service

9. Toolkit: Code of Practice
Learning Analytics Service
 Code of Practice
http://www.jisc.ac.uk/guides/code-of-practice-for-learning-
analytics
 Literature Review
http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-
_Literature_Review.pdf
 Template Learning Analytics Policy
https://analytics.jiscinvolve.org/wp/2016/11/29/developing-
an-institutional-learning-analytics-policy/
 Guidance on consent for learning analytics
https://analytics.jiscinvolve.org/wp/2017/02/16/consent-for-
learning-analytics-some-practical-guidance-for-institutions/

10. Legal and ethical: consent and GDPR
Learning Analytics Service
Advice is
 Make sure your collection notice covers the use of data
to support the student learning and wellbeing
 Not ask for consent for the use of non-sensitive data for
analytics (our current understanding is that this can be
considered as of legitimate interest or public interest)
 Ask for consent for use of sensitive data (which, under
the GDPR, is called “special category data”)
 Ask for consent to take interventions directly with
students on the basis of the analytics
https://analytics.jiscinvolve.org/wp/

11. Data
Collection
Data
Storage
and Analysis
Presentation
and Action
Jisc Learning Analytics open architecture: core
Alert and Intervention
system
Other Staff
Dashboards
Consent Service
(tbc)
Student App:
Study Goal
Jisc Learning
Analytics Predictor
Learning
Data Hub
Student Records VLE Library
Staff dashboards in
Data Explorer
Self Declared Data Attendance, Presence, Equipment use etc….
Data Aggregator
UDD Transformation Toolkit Plugins and/or Universal xAPI Translator

12. Learning Analytics Service
Data collection
About the student Activity data
TinCan
(xAPI)ETL
Learning
Data Hub
Attendance StudyGoal

13. Products and dashboards
Data Explorer: Learning Analytics dashboards for staff, focussing on showing learning analytics
data to staff based on their role.
Study Goal: An app for students - allowing them to view their learning analytics data, and set
measurable actions to support their success.
Learning Analytics Predictor: A predictive model designed to do one thing well - predict
success at course level. Output can be viewed in Data Explorer or any other system that can
integrated in the Learning Data Hub.
Traffic Lights Calculator: A straightforward rules based engine, allowing RAG status to be
calculated for online activity, attendance and achievement, at module level. Output fromTLC
can viewed in data explorer or any other system that can integrated in the learning data hub.
Learning Data Hub: the core of Jisc's learning analytics service, holds data about students,
works in conjunction with an institutions data warehouse, rather than replace it, to share data
between applications in a standard way, a collection point for semi-structured learning data
such as student activity.
Learning Analytics Service

14. Data Explorer
 Data Explorer Release 1.0
 View data in learning records warehouse
 Site Overview – overview of all data
 My Students and My Modules
 RAG Status and predictive models
 User Guide and videos
 https://docs.analytics.alpha.jisc.ac.uk/docs/d
ata-explorer/Home
Jisc Learning Analytics 2017

15. Learning Analytics Service

16. Study Goal
 Study Goal aims
 Social learning app with gamification
 Setting targets and logging self-declared activity
(fitbit model)
 View activity and attainment data
 Attendance check-in
 Guides and videos
https://docs.analytics.alpha.jisc.ac.uk/docs/study-
goal/Home
Jisc Learning Analytics 2017

17. Who we are working with….
Jisc learning analytics service

18. On-boarding Process
Stage 1: Orientation – get more info
Stage 2: Discovery – DIY and/or paid for consultancy
Stage 3: Culture and Organisation Setup – sign up for
Jisc service and/or supplier products
Stage 4: Data Integration - push data to learning data
hub
Stage 5: Implementation Planning
Learning Analytics Service
https://analytics.jiscinvolve.org/wp/on-boarding/

19. Discovery readiness
Topic ID Question Commentary Response Score
Leadersh
ip
1 The institutional senior management
team is committed to using data to
make decisions
Please provide a commentary on you
response to each question where
appropriate
0 - Hardly or not at
all
1 - To some extent
2 - To a great
extent
Leadersh
ip
2 Our vice-chancellor / principal has
encouraged the institution to
investigate the potential of learning
analytics
0 - Hardly or not at
all
1 - To some extent
2 - To a great
extent
Leadersh
ip
3 There is a named institutional
champion / lead for learning analytics
0 - No
2 - Yes
Vision 4 We have identified the key
performance indicators that we wish to
improve with the use of data
0 - Hardly or not at
all
1 - To some extent
2 - To a great
extent
Learning Analytics Service
A supported review of institutional readiness

20. Engaging institutions
2017-18 - Currently working with 20+ institutions (HE and
FE) on beta service
Deadline for beta service implementation is April 2018 (12
slots)
Target 40 institutions signed up to the learning analytics
service byAug 2018
Learning Analytics Service

21. Institutional engagement (pathfinders)
» Plymouth University
» Aberystwyth University
» University of East Anglia
» Cardiff Metropolitan University
» University of Greenwich
» University of Gloucestershire
» Oxford Brookes University
» City ofWolverhampton College
» Newman University
» University of Chester
» Dumfries & Galloway College
» Aston University
» University of SouthWales
» University of Brighton
» University of Abertay, Dundee
» Glasgow Caledonian University
» City, University of London
» Regent College University
» Bath Spa University
» Milton Keynes College

22. Learning Analytics Purchasing Service –
How we are working with suppliers of LA solutions
 USPs for Institutions:
 Marketplace for LA product & services compatible with the core Jisc service
 Procurement Framework – mini competitions can be easily initiated
 Mandatory clauses included – ensures a consistent & safe approach to data protection
 Institutions will control and own the contracts directly
 Framework will available to institutions from 18th September 2017
 Three categories of supplier services will be offered:
1. Learning Analytics Solutions
2. Learning Analytics Services
3. Learning Analytics Infrastructure
 https://docs.analytics.alpha.jisc.ac.uk/docs/learning-analytics/Learning-Analytics-Purchasing-
Service
Jisc Learning Analytics 2017

23. Vendor engagement
Learning Analytics Solution and Service
Providers
› Altis, HT2, Phoenix Software, SolutionPath,
Civitas Learning,Tribal, Unicon-Marist, Kortex
Data Sources including
› Tribal Education, Agresso (UNIT4), HESA,
Turnitin, Blackboard, Canvas, ExLibris,
OCLC (Online Computer Library Service),
Capita,Thales,TDS Student, Kortex

24. Learning Analytics Workshops/Consultancy
Examples
»Discovery- helps you assess readiness for implementing
learning analytics. Culture, Data, technology and
strategy
»Legal and ethical issues – explores data protection,
consent, GDPR
»Intervention planning to review data to plan
interventions with students and usingdata to enhance
the curriculum
26/11/2013 Jisc Co-design 24

25. Pricing formula from 2018-19
Learning Analytics Service
Formula per annum
£5K charge +
£1.80 per student for first 15,000 students +
50p per student thereafter
Examples
~5,000 students, £14k per annum
~10,000 students, £23K per annum
~18,000 students, £33K per annum
~27,000 student, £39K per annum

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