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Inside Government - London
8/7/2015 Jisc Learning Analytics
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Jisc’s Learning Analytics Project
»About Jisc»Learning Analytics»Jisc’s Open Learning Analytics Project»Finding out more
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About Jisc…
MissionTo enable people in higher education, further education and skills in the UK to perform at the forefront of international practice by exploiting fully the possibilities of modern digital empowerment, content and connectivity
VisionTo make the UK the most digitally advanced education and research nation in the world
What does Jisc do?
Does 4 things…
Providing and developing a network infrastructure and related services that
meet the needs of the UK research and
education communities
Supporting the procurement of
digital content for UK education and research
Our network of national and regional teams
provide local engagement, advice and support to help you get
the most out of our service offer
Our R&D work, paid for entirely by our major
funders, identifies emerging technologies
and develops them around your particular
needs
Co-design challengesResearch at risk
(R@R)
Prospect to alumnus (P2A)
Learning analytics
Digital learning & capabilities
Implementing FELTAG
Business intelligence
Hosting platform Hosting platform
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About Learning Analytics…
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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 achievement (current project)» Improve employability (current project)»Personalised learning (future project)
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Jisc’s Learning Analytics Project
Three core strands:
Learning Analytics Service
Toolkit Community
Jisc Learning Analytics
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Jisc’s Learning Analytics Service and Open Learning Analytics Architecture
Learning Analytics Service
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Student App
Dashboards
Alert and Interventio
n
Structured Data
Machine based
learning
Learning Records Store
Transformations/Mining
About the student Activity Data
Consent
Data Collection
DataStorageand Analysis
Presentation and Action
Architecture overview
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Our project partners
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Presentation and Action Layer
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Presentation and Action Layer Pt1Dashboards
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)
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Presentation and Action Layer Pt2Student App
Specification still underdevelopment, but first version will include:
»Overall engagement»Comparisons»Self declared data»Consent management
Bespoke development by Therapy Box
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Presentation and Action Layer Pt 3Alert 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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Data Storage and analysis layer
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Open SourceCommercial
Predictive Analytics/Machine learning
Transformations and mining
Structured Data/
Business Intelligence
‘Big Data’ Learning Records Store Big Data
Data storage and analysis layer overview
Presentation layer
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Data Collection Layer
Title of presentation 00/00/2013 20
Learning Records Store
About the student
Activity dataTinCan (xAPI)
ETL Student
Record System
LibraryVLE Other
s
Data collection layer overview
Data Collection
DataStorageand Analysis
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Activity data via Tin Can API• People learn from interactions with
other people, content, and beyond.
• These actions can happen anywhere and signal an event where learning could occur.
• When an activity needs to be recorded, the application sends secure statements in the form of “Actor, verb, object” or “I did this” to the Learning Record Store (LRS.)
from: http://tincanapi.com/
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Activity Data (TinCan) examples
Actor Action Object
Result
Michael Accessed VLE
Sally Completed Basic Maths Test
85.0
Kim Module Comment
Added
https://registry.tincanapi.com
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Example as JSON code{ "actor": { "name": ”Michael", "mbox": "mailto:[email protected]" }, "verb": { "id": "http://adlnet.gov/expapi/verbs/accessed", "display": { "en-UK": ”accessed" } }, "object": { "id": "http://example.com/activities/vle", "definition": { "name": { "en-UK": ”VLE" } } …
Actor
Verb
Object
Title of presentation 00/00/2013 24
About the student’ data
Personal (demographic) data
Birthdate, gender etc.
Course data
mode of study, level etc.
Grade data
Assignment, module etc.
(aligned with HESA data)
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Jisc/Unicon Discovery
Jisc Learning Analytics
Implementation
Wish to explore readiness and products
Know you are ready and what you want
Want to get involved in tech work first
Blackboard Discovery
Unicon/Marist pre-
implementationTribal pre-
implementation
Other pre-implementation
Blackboard Trial
Moodle Trial
Other Learning Analytics
Implementation
Tech Trials Discovery Pre-implementation
Implementation
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Jisc Learning Analytics Toolkit
Toolkit
http://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics
First Publication: Code of Practice
Deeper Dive
http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf
Literature review – basis for the code of practice
Code of Practice
Privacy
Validity
Responsibility
AccessEnabling positive
interventions
Minimising adverse impacts
Transparency and consent
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Community
Community
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Project Blog, mailing list and network events
Blog: http://analytics.jiscinvolve.org
Mailing: [email protected]:
Next event: Bradford Oct 2015
One CastleparkTower HillBristolBS2 0JAT 020 3697 5800
Michael WebbDirector of Technology and Analytics
