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Join the learning analytics party!Exploring the full potential of using data to support learning
> >Slide Join the learning analytics party!
Introduction>Strategic importance of learning analytics>What problems could we solve?>Evidence that it works>Business case
>Jisc national learning analytics>What Jisc is doing now
>The future>Where it could lead
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Strategic importance of learning analyticsDr. Phil Richards, Chief innovation officer, Jisc
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Join the learning analytics party!
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:
>Eg:>Improve retention>Improve achievement>Improve employability>Reduce differential outcomes
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Problems: Retention, attainment, differentialsHESA non-continuation rates 2016-17 “headline increase from 6% to 6.2%”
Director of Fair Access Les Ebdon “particularly concerned that the non-continuation rates for young people from the most disadvantaged backgrounds have risen faster than for other groups”, and expects the next round of access agreements to particularly focus on the issue of retention. (WonkHE)
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Evidence>Columbus State
University College (USA) retention rose by 4.2% (5.7% for low-income students)
>Open University (UK) pilots have seen a 2.1% boost in retention
>University of New England (Australia) saw drop-out rates fall from 18% to 12%
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Business case outlines>Typical university 20,000 students, 6% first year
non-completion improves to 4%>Annual benefit in reducing lost fees £7.2M-£10.8M>(Annual LA cost < £0.1M)
>High retention university, 20,000 students 2% first year non-completion improves to 1.5%>Annual benefit £1.8M-£2.7M £
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Evidence for LA in access agreementsClick to icon to add image
https://analytics.jiscinvolve.org/wp/2017/01/10/whats-the-evidence-for-learning-analytics/
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Jisc – Developing the UK’s national learning analytics serviceRob Wyn Jones, Senior data and analytics integrator, Jisc
Join the learning analytics party!
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Join the learning analytics party!
Learning analytics – three strands
Learning analytics service
Toolkit Community
Jisc learning analytics
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LA community>Blog (40+ blog posts)>http://analytics.jiscinvolve.org ~ 40
blog posts>Mailing: 500+ members (190+
organisations)>[email protected]
>9th network meeting ~600+ participants
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Legal and ethical>Code of Practice
jisc.ac.uk/guides/code-of-practice-for-learning-analytics
>Literature Reviewhttp://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf
>Template Learning Analytics Policyhttps://analytics.jiscinvolve.org/wp/2016/11/29/developing-an-institutional-learning-analytics-policy
>Guidance on consent for learning analyticshttps://analytics.jiscinvolve.org/wp/2017/02/16/consent-for-learning-analytics-some-practical-guidance-for-institutions
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Learning analytics – accessibility and analytics labs>Blog Post: accessibility and considerations for learning
analyticshttps://analytics.jiscinvolve.org/wp/2016/12/14/accessibility-considerations-for-learning-analytics
>Invitation to join Jisc/ HESA analytics labs: April – July 17 - - FOC Agile delivery, BI Tableau + knowledge transfer)http://bit.ly/jisc_bi_team_application
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UK learning analytics serviceJisc learning analytics open architecture: core
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Our confirmed partners…>Look out for further
announcements soon….>Dynamic purchasing
agreement to make it easier for institutions…
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LA product/ service roadmap
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Now and for the future – Jisc UK learning analytics 2017-2019Rob Wyn Jones, Senior data and analytics integrator, Jisc
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Products and tools (as at March 2017)>Learning records warehouse (LRW) – active + APIs>Jisc Data Explorer – basic visualisations >Student Unified Data Definition – version 1.2.7, upcoming 1.3.0 and
examples major SRS and automated validation>VLE – xAPI recipe and plugins for Blackboard and Moodle>Attendance tracking – xAPI recipe (2 pilots)>Study Goal – version 1.0 on iOS and Android pilots - (3)>Tribal Student Insights and LAP (14)>Open Learning Analytics Processor (4)>Student Success Planner – SSP (2)
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Current implementation approach
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Analyse and pilot Choose
full product
Historic data
Analyse results
Live data
Deploy dashboards/other tools
SuppliersInstitution team End users
Model build
Deploy Study Goal
Deploy DataX
Analyse and pilot
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Study Goal (formely ‘Student App’)>First version includes:>Overall engagement>Comparisons>Self declared data>Consent management
Bespoke development by Therapy Box
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Jisc - Data Explorer>Basic dashboard/ vis
tool>Enables initial data
exploration and assist institutions to chose suitable commercial solutions and set a basic expectation
>Being used by several pilot institutions
>Demo uses dummy data from University of Jisc 21
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Join us – getting startedLearning analytics – onboarding processhttps://analytics.jiscinvolve.org/wp/on-boarding
>Stage 1: Orientation>Stage 2: Discovery>Stage 3: Culture and organisation setup>Stage 4: Data integration (crucial too, and can take
time!)>Stage 5: Implementation planning
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Learning analytics, and the unfolding education landscapeDr. Phil Richards, Chief innovation officer, Jisc
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HESA data futures/ HEDIIP alignment for UDDClick to icon to add image
jisc.ac.uk/rd/projects/information-hub-prototype
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HEFCE learning gain call – May 2015>Standardised tests>Grades>Self-reporting surveys>Mixed methods>Other qualitative
methods
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Teaching excellence framework and quality assessment
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LA warehouse: our DNA bank for higher e-learning?
Reference data» Demographics» Entry
qualifications» Learning and
employment – Longitudinal Educational Outcomes (LEO) data
Outcomes» Deep
understanding of e-learning
» Metrics for engagement, learning gain
» Personalised next generation e-learning and learner pathway guidance
Analytics number crunching
UK learning data warehouse
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Blended curriculum design
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AI and the analytics (r)evolution…
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jisc.ac.uk
Except where otherwise noted, this work is licensed under CC-BY-NC-ND
02/05/2023
Join the learning analytics party!> >
Contact details
Join the learning analytics journey
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Dr. Phil RichardsChief innovation officer, [email protected]
Rob Wyn JonesSenior data and analytics integrator (Learning analytics)[email protected]
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Join the learning analytics party!
Exploring learning analyticsPaul Bailey, Senior co-design manager
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Exploring learning analytics
Find out more at Digifest>Day 1: Tues>16:15 Attendance monitoring (demo)>Day 2: Weds>9:15 Debate: Human vs machine interventions>10:15 Business intelligence in HE (demo)>11:15 Learning design and leaner analytics (Patrick
Lynch)>13:30 Study Goal and Data Explorer (demo)>14:45 Learning analytics for FE Colleges
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Learning analytics explained
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Join us – getting startedLearning analytics – onboarding processhttps://analytics.jiscinvolve.org/wp/on-boarding
>Stage 1: Orientation>Stage 2: Discovery>Stage 3: Culture and organisation setup>Stage 4: Data integration (crucial too, and can take
time!)>Stage 5: Implementation planning
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Learning analytics online modulesThe following videos are extracts from some learning analytics online modules available soon>Module 1 - Introduction to learning analytics>Module 2 - Student and staff perceptions>Module 3 - Institutional readiness>Module 4 - The Jisc architecture
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Vision and goals for data analytics>Video Clip:
A shared vision for learning analytics (00:16 - 01:25)
>Discussion: What are your short-term (6-12 month) goals for learning analytics at your institution, and how are they aligned with your institutional goals?02/05/20
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Lindsay Pineda, Unicon
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The need for governance>Governance structures –
The role of governance in learning analytics (1:11 - 4:03)
>Discussion: Where do you believe the governance structures for learning analytics should fit into the rest of the institution?02/05/20
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Patrick Lynch, University of Hull
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A code of practice>Legal and ethical issues -
The need for a code of ethics (00:00 - 01:51)
>Discussion: What are some of the other ethical issues that arise in storing and combining learning data as we do in learning analytics? How can institutions ensure that they handle student data in a responsible manner?
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Martin Hall
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Data literacy>Digital literacy -
Data literacy - towards a data-informed culture (02:25 - 03:51)
>Discussion: How can technical staff and educators work together to ensure that learning analytics systems are optimised - both technically and pedagogically?02/05/20
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Martin Hall
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jisc.ac.uk
Except where otherwise noted, this work is licensed under CC-BY-NC-ND
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Exploring learning analytics> >
Contact details
Learning analytics
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Paul BaileySenior co-design [email protected]
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