m25 jisc learninganalytics-20july2016

Paul Bailey, Senior Codesign Manager, Research and DevelopmentJisc learning analytics service

http://www.slideshare.net/paul.bailey/

M25 Group Presentation: learning analytics service 2

Effective Learning Analytics ChallengeRationale»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 basic learning analytics service with app for students»Provide a network to share knowledge and experienceTimescale»2015-16—test and develop the tools and metrics»2016-17—transition to service (freemium)»Sep 2017—launch, measure impact: retention and achievement


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 attainment (current project)» Improve employability (future project)»Personalised learning (future project)


Retention 178,100 students aged 16-18 failed to finish post-secondary

school qualifications they started in the 2012/13 academic year costing £814 million a year - 12 per cent of all government

spending on post-16 education and skills (Centre for Economic and Social Inclusion

8% of undergraduates drop out in their first year of study This costs universities around £33,000 per student students with 340 UCAS points or above were considerably less

likely (4%) than those with less UCAS points (9%) to leave their courses without their award


Attainment 70% of students reporting a parent with HE qualifications

achieved an upper degree, as against 64% of students reporting no parent with HE qualifications

In all disciplines except Computer Science, Medicine and Dentistry, and Physical Science, students with a parent with an HE qualification were more likely to have achieved an upper degree

Overall, 70% of White students and 52% of BME students achieved an upper degree


Jisc’s Learning Analytics ProjectThree core strands:

Learning Analytics Service

Toolkit Community

Jisc Learning Analytics


Community: Project Blog, mailing list and network eventsBlog: http://analytics.jiscinvolve.org

Mailing: [email protected]


http://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics

Toolkit: Code of Practice

http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf






Toolkit: Learning analytics

http://repository.jisc.ac.uk/5657/1/Learning_analytics_report.pdf

The current state of play in UK higher and further education





M25 Group Presentation: learning analytics service 10Toolkit: Learning Analytics in Higher Education: A review of UK and international practice

Including case studies on Traffic Lights and Interventions: Signals at Purdue

University Analysing use of the VLE at the University of Maryland,

Baltimore County Identifying at-risk students at New York Institute of

Technology Fine-grained analysis of student data at California

State University Transferring predictive models to other institutions

from Marist College Enhancing retention at Edith Cowan University Early alert at the University of New England Developing an ‘analytics mind-set’ at the Open

University Predictive analytics at Nottingham Trent University Analysing social networks at the University of

Wollongong Personalised pathway planning at Open Universities

Australiahttps://www.jisc.ac.uk/reports/learning-analytics-in-higher-education

https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education





Learning Analytics Service Architecture


DashboardsVisual 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)


Alert and Intervention SystemTools 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)


First version will include: »Overall engagement»Comparisons»Self declared data»Consent management

Bespoke development by Therapy Box

Student App


Stats – Provides an engagement and attainment overview and drilling down to gives comparative activity graphs.

Log – Allows you to log time spent on specified activities e.g. reading for an assignment

Target – Allows you set personal targets to improve your engagement e.g. study for 10 hours this week


Toolkit: Discovery Institutional ReadinessA process to support institutions to access their readiness to implement learning analytics 2015-16 – Three days onsite consultancy visit of workshops, focus groups and

interviewsReview of the reports form 26 institutions are being used to develop a new readiness process 2016 -17 – Overview workshop, introducing a “Readiness Toolkit” with a

diagnostic set of questions and support materials leading to implementation.

Further details will be announced via analytics @jiscmail.ac.uk


Discovery Institutional Readiness Update2016 - 17

5. Implementa

tion Support

4. Signed-up for

Service

3. Institutional Readiness

2. Self-assessme

nt 1.

Workshop


Discovery Readiness Questionnaire• Culture and Vision• Strategy and

Investment• Structure and

governance• Technology and data• Skills


Initial Implementation Guidelines/ChecklistCulture and Organisation Setup Decide on institutional aims for learning

analytics Senior management approval and you

have a nominated project lead Undertake the readiness assessment Decision on learning analytics products to

pilot Legal and ethical considerations in hand Address readiness recommendations Data processing agreement signed Select student groups for the pilot and

engage staff/students

Technical setup Learning records warehouse setup Extract student data to UDD and

upload to LRW Historical data extracted from the VLE

and SRS and uploaded to the LRW VLE plugin installed and live data

being uploaded View in data explorer to check valid Contact Jisc to start implementation


The Learning Analytics Project in numbersExpressions of interest: 85+Engaged in activity: 35Discovery to Sept 16: agreed (26), completed (14), reported (10)Learning Analytics Pre-Implementation: (12)Learning Analytics Implementation: (7)


Phase 1&2Sep 15 – Apr 16

Phase 2&3 Jan – Sept

16

Transition to Service

Sept 16 – July 17

Jisc Learning Analytics

Service Sept 2017

Contacts

Paul Bailey [email protected]

Further Information: http://www.analytics.jiscinvolve.org

Join: [email protected]


mailto:[email protected]

http://www.analytics.jiscinvolve.org/

http://www.analytics.jiscinvolve.org/

http://elevator.jisc.ac.uk/