The document discusses learning analytics and the Jisc learning analytics service. It provides an overview of what learning analytics is, the goals of the Jisc service which include helping institutions get started with learning analytics and providing standard tools, and the components of the Jisc service including a code of practice, community resources, data collection and products like Data Explorer and Study Goal. It also discusses working with institutions, engagement activities, the on-boarding process, and engaging with solution providers.
4. “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
5. Agenda
Learning Analytics Service
Descriptive or 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
6. 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
7. David Lewis, Senior Analytics Consultant, Digital Futures
Jisc learning analytics service
https://docs.analytics.alpha.jisc.ac.uk/docs/learning-analytics/Home
8. 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
9. 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
10. 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/
11. 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/
12. Data
Collection
Data
Storage
and Analysis
Presentation
and Action
Jisc Learning Analytics open architecture: core
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. Learning Analytics Service
Data collection
About the student Activity data
TinCan
(xAPI)ETL
Learning
Data Hub
Attendance StudyGoal
14. 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
15. 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
17. 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
18. Who we are working with….
Jisc learning analytics service
19. 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/
20. 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
21. 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
22. 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
» University of SouthWales
» 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
23. 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
24. Vendor engagement
Learning Analytics Solution and Service
Providers
› Altis, HT2, Phoenix Software, SolutionPath,
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
25. 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 using data to enhance
the curriculum
26/11/2013 Jisc Co-design 25
27. Except where otherwise noted, this work is licensed under CC-BY-NC-ND.
Dicky Maidment-Otlet
Director of marketing
Dicky.maidment-otlet@jisc.ac.uk
Thankyou