The document discusses national learning analytics in the UK and Jisc's role in providing learning analytics services. It describes Jisc's learning analytics tools and products like the Data Explorer dashboards, Study Goal app, and Learning Data Hub. It outlines Jisc's onboarding process for institutions and examples of how they are working with universities and colleges to implement learning analytics.
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
4. Descriptive or predictive models
identify students at risk
Rich data on student
activity and attainment
Timely intervention by
teaching or support staff
Data shared with
student prompting
them to change own
behaviour
Data can be
explored to
understand patterns
of behaviour
Increased
retention
Better understanding
of the effectiveness of
interventions
Better student
outcomes
Better understanding
of the behaviours
linked to differential
outcomes
Learning analytics service
5. Learning analytics service
A more efficient campus
Buildings data
+
Learning space data
+
Location data
Improved teaching and curricula
Teaching quality data
+
Assessment data
+
Curriculum design data
Personalised and adaptive
learning
Content data
+
Learning pathways data
Improved teaching and
curricula
Better retention
and attainment
VLE data
+
Student record
system
+
Attendance data
+
Library data
Efficient campus
Retention and attainment
+
+
+
Learning
analytics
Institutional
analytics
Educational
analytics
Cognitive
Analytics andAI
Now Future
6. Rob Wyn Jones – Head of
data and analytics services
Jisc – UK learning analytics national service
https://docs.analytics.alpha.jisc.ac.uk/docs/learning-analytics/Home
7. 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
Effective Learning Analytics Challenge
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
9. Toolkit: Code of practice
» Code of practice
jisc.ac.uk/guides/code-of-practice-for-learning-
analytics
» Literature review
http://repository.jisc.ac.uk/5661/1/Learning_Ana
lytics_A-_Literature_Review.pdf
» Template learning analytics policy
https://analytics.jiscinvolve.org/wp/2016/11/29/d
eveloping-an-institutional-learning-analytics-
policy/
» Guidance on consent for learning analytics
https://analytics.jiscinvolve.org/wp/2017/02/16/c
onsent-for-learning-analytics-some-practical-
guidance-for-institutions/
10. Legal and ethical: consent and GDPR
» 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
Advice is:
11. Jisc learning analytics open architecture: core
Data
Collection
Data
Storage
and Analysis
Presentation
and Action Alert and
Intervention system
Other Staff
Dashboards
Student Consent
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
13. » 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. Includes hardware-independent Attendance
Tracking functionality, as standard
» 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 from TLC
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
Products and dashboards
14. Data Explorer
» Data Explorer Release 1.0
› 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/do
cs/data-explorer/Home
15.
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
› Exclusive – Student Attendance
Check-in
»Guides and videos
https://docs.analytics.alpha.jisc.ac.uk/
docs/study-goal/Home
17. Attendance check-in (via Study Goal)
» Cheap and simple to implement
» No hardware installation or maintenance required
» Attendance tracking only – no need to integrate with
timetabling systems
» Attendance monitoring can be done using our Data
Explorer tool – or extract yourself!
» Raw attendance data can be accessed directly from
our LDH, using our APIs
» Easy for staff and students to use
» Can be used alongside other attendance systems
eg to record attendance in locations where other
solutions are not installed
» Allows staff to monitor which students are attending
and see students who are not
» Identify students whose attendance pattern is poor
18. Who we are working with….
Jisc learning analytics service
19. 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
On-boarding process
https://analytics.jiscinvolve.org/wp/on-boarding
20. Topic ID Question Commentary Response Score
Leadership 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
Leadership 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
Leadership 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
Discovery readiness
A supported review of institutional readiness
21. »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 by Aug 2018
Engaging institutions
22. Institutional engagement (pathfinders)
» University of South Wales
» University of Brighton
» University of Abertay, Dundee
» Glasgow Caledonian University
» City, University of London
» Regents University
» Bath Spa University
» Milton Keynes College
» Kings College London
» University of Stirling
» Edinburgh Napier
» Plymouth University
» Aberystwyth University
» University of East Anglia
» Cardiff Metropolitan University
» University of Greenwich
» University of Gloucestershire
» Oxford Brookes University
» City of Wolverhampton College
» Newman University
» University of Chester
23. » USPs for Institutions:
› Marketplace for LA product and services compatible with the core Jisc service
› Procurement Framework – mini competitions can be easily initiated
› Mandatory clauses included – ensures a consistent and 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
Learning analytics purchasing service –
How we are working with suppliers of LA solutions
25. 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
Learning analytics workshops/consultancy
26. Except where otherwise noted, this work is licensed under CC-BY-NC-ND.
Rob Wyn Jones
Head of data and analytics services
rob.jones@jisc.ac.uk
Thankyou