Implementing analytics - Myles Danson, Shri Footring, David Matthews, James Foster

PowerPoint Presentation

Implementing analyticsLearning Analytics and Business Intelligence

24/06/20162Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Session outlineOverview of the Learning Analytics service The user voiceOverview of the Business Intelligence projectThe user voiceGroup exercise

Learning Analytics324/06/2016

Overview of LA service Shri (5 mins)User voice David Matthews (10 mins)Overview of BI-Myles (5 mins)The user voice-James (10 mins)Group exercise-Shri (20 mins)Whats coming next- Shri and Myles (5 mins)


Learning Analytics


Effective Learning Analytics ChallengeRationaleUniversities and colleges wanted help to get started and have access to a standard set of tools and technologies to monitor and intervene Priorities identifiedCode of Practice on legal and ethical issuesDevelop a basic learning analytics service including an app for studentsProvide a network to share knowledge and experienceTimescale2015-16 - Test and develop the tools and metrics2016-17 - Transition to service (Freemium)Sept 2017 Launch. Measure impact on retention and achievementLearning Analytics524/06/2016

The effective learning analytics challenge was initiated from consultation with stakeholders, senior manager and practitioners who felt the sector need support to get up to speed with learning analytics. They prioritised three main areas, a Code of Practice to address legal and ethical issues of using learning analytics; a set of basic learning analytics tools to allow institutions to get started and make informed decisions; and a network to allow institutions to share practice and learn from each other.The current project has procured suppliers to provide a learning analytics service which are currently being tested by several institutions. This will be developed into a full service next year and provided as a new Jisc service from Sept 2017.24/06/20165Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

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)


What do we mean by learning analytics. The service we are developing will collect data and undertake statistical analysis of historical and current data derived from the learning process to create models that allow for predictions that can be used to improve learning outcomes.Models are developed by mining large amounts of data to find hidden patterns that correlate to specific outcomesE.g. Mine VLE event data to find usage patterns that correlate to course gradesThe service will provide predictive models initially for retention (identify students at risk of failing) and attainment (identifying students at risk of not achieving a specified level of attainment). In the future we will look to offer predictive models to support employability and personal/adaptive learning.


Toolkit and communityBlog: http://analytics.jiscinvolve.orgReportsCode of Practice for Learning AnalyticsThe current state of play in UK Higher and Further EducationLearning Analytics in Higher Education: A review of UK and international practiceMailing: [email protected] Network meetings


The project consists of the learning analytics architecture (next slide), a toolkit and community.These consist of a blog with reports and information to assist institutions with readiness to implement learning analytics and technical implementation of the Jisc service.There are three reports all linked from the blog a Code of Practice for Learning Analytics, A report from 18 months ago that reviewed current state of learning analytics in the UK and a more recent report on the evidence base for the effectiveness of learning analytics with 12 international case studies.If you want to be involved and keep informed about the development of the service then join the analytics jiscmail listWe also hold quarterly network meetings which are promoted via the blog and jiscmail list24/06/20167Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Learning Analytics Architecture


Overview of learning analytics architecture. Red items are components that will include the tools in the project (Tribal student insight, Unicon/Apereo LAP and Student Success Plan, Student App) but also alternative third party or institutional tools.24/06/20168Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Current engagementExpressions of interest: 85Engaged in activity: 35Discovery to Sept 16: agreed (28), completed (18), reported (17)Learning Analytics Pre-Implementation: (12)Learning Analytics Implementation: (7)


We have ~400 people on the Jiscmail list and a pipeline of interested institution's (50+ HE, 20+FE). We are actively engaging with 35 institutions, 28 in discovery institutional readiness and 12 in beta implementations. 24/06/20169Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Future EngagementFrom Sept 2016Readiness Toolkit with a diagnostic set of questions and support materials leading to implementation Start-up guidelines to get ready for learning implementationFurther details will be announced via analytics @jiscmail.ac.uk


From Sept 16 well be introducing a new institutional readiness process to help institutions get ready for implementing learning analytics. This will consist of an overview workshop to introduce the service and an diagnostic assessment tool, institutions will complete the assessment tool and then undertake appropriate actions to address recommendations. For institutions who are ready to start implementation there will be set of guidelines to get set-up with data collection and visualisations, ready to implement a predictive analytics solution and the student app.Details will be announced via the jiscmail list so join it to participate.24/06/201610Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Connect More With Jisc 2016Embedding Learner AnalyticsDavid Matthews VLE Development [email protected]

RBC is a small specialist HEI, focusing on all aspects of theatre/performance training. Large online/distance learning cohorts, blended courses such as PGCTLHE, plus off-campus MA and significant study abroad elements (e.g. Erasmus and ATA). Want to use LA especially to help those students who are not on campus for extended periods of time during the working week. TDAP.Heard about the project through MASHEIN off-shoot of the Leadership Foundation but also have a long-standing relationship with Jisc/RSC/Evan and Martin

24/06/2016Leanring Analytics12

Existing use of Learner DataReporting out of Moodle (not very good or satisfactory) and other VLE servicesData held in Registry, e.g. HESA returns, DLHE, NSS and first impressions etc.Data held by IT and LRC, e.g. logins from College usernames etc. Google Analytics on College corporate websites and VLEData collected by programmes, e.g. end of module questionnaires, surveys


Learner Analytics Project

Joining the project

Introduced to Rob Wyn Jones and Paul Bailey who have made site visits (joined by Evan Dickerson)Involved Registry, Student Records and IT. Approval from SMC who are very keen on the project. Site visits and Skype/Google Hangouts meetings


Learner Analytics ProjectCurrent statusTransformation of student data into Jiscs LA data model is now taking place(being done in close collaboration with Jisc) Student data - LA data model is similar to HESA student return structure/ field specifications documented online at https://github.com/jiscdev/analytics-udd/Moodle data Historical data has been extracted from Moodle logs on our ULCC-hosted Moodle (via internal Jisc software) This is being push into the Jisc Learning Records Warehouse A LIVE data plug-in for Moodle (extracting engagement data moving forwards) has been evaluated and installed on our ULCC-hosted Moodle(Learning Locker screengrab)


Anticipated OutcomesImproved use of data across the CollegeRetention is already very good, but one student leaving a small cohort makes a big dent in statistics and in funding!Enable Registry to function effectively/grow post-TDAPBetter support for online/blended students and those on placements/Erasmus visits. Better or more timely interventionsA genuine development project that, as a small institution, we would not have been able to resource or support ourselves Excited to be part of an important project in an emerging field Very happy to continue our working relationship with Jisc


HESA and Jisc Business Intelligence

MylesJisc and HESA are collaborating to develop new national shared services for business intelligence, making better use of the national data landscape, reducing repetitive activities across universities, brining the benefits of BI to all Univerisits regardless of capability / expertise17

About HESA18


MylesHESA is a not for profit subscription organisation, so similar to Jisc in that sense. As well as a mandatory subscription, members are mandated to provide data collections covering the broad themes of Student, Staff, Destinations (of graduates) and Estates data. This is annual but in year collection is under consideration. HESA cleanse the data and provide back full data sets, published statistics and undertake bespoke analysis. Jisc and HESA membership is similar.18


MylesHeidi Plus is depicted on the left highlight the trucks driving in to the HESA data warehouse. HESA mandates that all publicly funded HEPs provide performance data on students, destinations of leavers, staff, finance and estates. Currently an annual collection they are moving to more frequent in year collections. The data is cleansed and a new team undertake dashboard development. Quality is assured as the dashboards are offered throught the radio mast in the middle a new national BI dashboard delivery service offered to all HESA customers (currently 180 HEPs and associated organisations and departments). Built with Jisc and launched as a HESA service in November. Includes legal framework and national training programme. Replaces a system with 6.5K users. Lowers the bar to usage through the interactive dashboards so could take BI to a woder range of staff than is currently possible.Heidi Lab is depicted to the right. A Jisc led alpha July 15 July 16. Highlight the trucks again and note its a two way street a data sharing agreement allows HESA data into the Heidi Lab secure data processing environment. Agile analysis teams are created from multiple universities and given access. They identify commonly felt problems spaces, explore the wider national data landscape, acquire non-HESA data and cleanse, link and transform it creating new proof of concept dashboards. Highlight the trucksa driving from the Lab to the Radio Mast. Successful dashboards will be branbded produced by Jisc and delivered via Heidi Plus.Piece in the middle is the beta service what comes next Heidi Plus is sustained by HESA as a service. We have proved there is real merit in Heidi Labs and will launch a beta service July 16 July 17.

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James20

Heidi Plus The new business intelligence service for UK Higher EducationReplaces Heidi (which will be decommissioned in November 2016)Launched in November 2015 offering:Improved data content and functionalityDelivery of data sets through commercial data explorer toolNew visualisations and dashboards New training programme and support materialsAvailable to HE institutions with a full HESA subscriptionOver 80% of current Heidi subscribers have started the Heidi Plus application process (40% completed)Learning Analytics2124/06/2016

JamesHESAs current data delivery service is known as HEIDI (Higher Education Information Database for Institutions) developed in house in 2007. Jisc and HESA collaborated to replace this with a more up to date service. We procured Tableau, market leading data exploration software and now offer Heidi Plus Feedback has been extremely good across the sector

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Heidi Lab overview


MylesHeidi Lab as a Jisc Alpha project (proof of concept) engaged with 290 individuals from 130 universities to develop a successful model of agile analysis. 50 analysts (planners, directors of planning from 44 universities volunteered to join cross institutional agile analysis teams for three Heidi Lab cycles of 3 months each at just 0.2 FTE. Teams were supported as they identified and refined widely felt problem areas (see example on the slide covered student, staff, research, estates etc) linked to national policy. They explored the data landscape for supportive insights, recording the issues encountered in our data catalogue. Finally they produced interactive dashboards using Tableau software as proofs of concept to offer through Heidi Plus

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Secure data processing environment

Technical infrastructure bound by legal agreements to ensure data and dashboards are secure Learning Analytics2324/06/2016

Myles

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Information improvement manager UEL with;Kent, Middlesex, Brunel, Royal HollowayStrategic planning and BI manager Sunderland with;Glasgow, Glasgow Caledonian, St Andrews, SunderlandDirector of planning, Kent with;Birkbeck, Cardiff, Oxford, Southampton, SouthamptonStrategic Planning Manager, MMU with;Leicester, Leicester, Cambridge, Bishop GrossetesteWinter teamsLearning Analytics2424/06/2016

Led by a senior staff member with knowledge of the information needs of a wide range of staff and institutions as well as national policy and what is up stream24

Upskilling of staff resource across sector Opening up of collaborative relationships across other organisations Value, saving and efficiency gains from the creation and delivery but also the actions subsequently taken due to the insights gained across research, student, staff and estates and possibly internationallyOpening up access to disparate data sets and making sense of them in an HE contextPossible national licensing deals for paid access to data

Team member experiences


James adjust to suit your own experiences25

Winter team dashboardsLearning Analytics2624/06/2016

James to lead26

Dashboard: Course Market Analysis for InstitutionsWhat is it?An Overview MoviePurpose:This dashboard is designed to support a universitys strategic planner in designing course by allowing comparison across the sector.

Use case:As a Strategic planner when working out which courses to teach I want to examine competition to my course offerings to ensure I target recruitment activity most effectively.

Data sources:National Pupil Database: http://bit.ly/224CU8IKey Information Sets: http://bit.ly/1ZYnG5zNational Pupil Database: http://bit.ly/224CU8IHESA DataWhat needs to be done and issuesTime and Effort to MarketWhere there is scope for improvement:Generally very polishedSome work on the interface required perhaps to sign-post the featuresLicencing issues for league table data need to be negotiated.Data sources would need updating each year particularly the school data.


James to continue with these (as many as time permits)27

Dashboard: University Finder for StudentsWhat is it?An Overview MoviePurpose:This dashboard is targeted at students who are looking for a university course to fit their needs. By needs we don't only mean course but also: cost, employability, location and entry tariff.

Use case:As a student when working out which university course offers best fit my needs, I want to understand factors of relevance to me (course, cost, employability, location, cost of living, rural/urban and entry tariff) to compare and match offers to my circumstances.

Data Sources:Key Information Sets: http://bit.ly/1ZYnG5zHESA DataWhat needs to be done and issuesTime and Effort to MarketThis dashboard supplies a unique perspective on data and services that are already available to students. In some ways this is a crowded marked. So the unique selling point of this product would need to be promoted that is that the data already available to students is amalgamated and drawn together to create a wizard like app for students to find courses.What would need to be done:Identify appropriate vehicle for deliveryMarket uniqueness of the the productNegotiate data licences for league table data


James to continue with these (as many as time permits)

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Dashboard: Finding Comparable InstitutionsWhat is it?An Overview MoviePurpose:This dashboard can be used to identify a universitys relative performance against a benchmark of similar institutions.

Use case:As a Planning Manager I want to select similar institutions based on metrics I choose so that I can determine the best institutions to compare with my own university to understand if our performance is relatively good or bad

Data Sources:HESA data from HeidiKey Information Sets: http://bit.ly/1ZYnG5zLeague Table Data will require licensingWhat needs to be done and issuesTime and Effort to MarketWhere there is scope for improvement:Data a relatively narrow data set was used for prototyping; a production version could accommodate a far more comprehensive data set.Filters searching and filtering could be enhancedLicencing Makes use of some league table data to benchmark against entry tariff. Licence for this need to be negotiated.


James to continue with these (as many as time permits)29

BI Group exercise


Shri or James to lead?30

As a: Strategic Planning ManagerWhen: Reviewing current course provisionI want to: Enable course/curriculum management planning to match national and local demandSo I can: Grow or at least maintain student recruitment

Data Sources: HESA student, DLHE, Award data, KIS, CUGSchool/College performance data (A level results and numbers, School Age Populations Forecasts, etc.)Labour market data from NOMIS (Employment rates, earnings, SOC, SIC

Group exerciseLearning Analytics3124/06/2016

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Feeding back

24/06/2016Learning Analytics32

Nominate a person from each table to feed back on a user story, explain we will photograph them all and feed into further cycles for consideration32

What next?

24/06/2016Learning Analytics33

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Library analytics labsTeams working on Library BI Stories at 0.2 FTE, total estimated effort 15 days from July - Oct 2016Both Product Owners and Sector Data Experts invited:Product Owner from the sector to steer which stories are of interestSector Experts to understand what data sources are available and what is in the dataJisc Contracted Data transformation specialist (CETIS)Jisc Agile Scrum Master and Tableau UserTeams receive experience and guidance of Agile workingOption for Tableau Desktop training to help with creating visualisationsApply at http://bit.ly/jisc_library_data_labs_applicationsQueries to [email protected] or [email protected]


Myles just to note we are running a set of teams from the library area to prove the concept transfers24/06/201634Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

FE analytics labsShri- can you add an overview and description of the three clustersLearning Analytics3524/06/2016

Shri very brief note to say we are running a College Labs experiment24/06/201635Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Analytics academy a Jisc beta service - October 2016Business intelligence offers value, savings and efficiencies to Universities through data informed enhanced planning / decision makingMany problem spaces are commonly felt, while the data landscape to support insights is vast Some universities have little access to good BI at all, while those with capability are often duplicating effortThere is no higher education focused CPD offer to train up BI expertiseAnalytics academy addresses these problems by providing expertise and tools for analysts (planning officers and others) to identify suitable problem areas (student, staff, research, estates etc), exploring the data landscape for insights and producing interactive dashboards for the sector


Myles a new Jisc offer to explode whether there is a sustainable service in this24/06/201636Title of presentation (Insert > Header & Footer > Notes and Handouts > Header > Apply to all)

Keep in touchbusiness-intelligence.ac.ukSubscribe via jiscmail.ac.uk/JISC-HESA-BUSINESS-INTEL Twitter @HESA @jisc #hesajiscbi


Dashboard: University Research BenchmarkingWhat is it?An Overview MoviePurpose:This dashboard is designed to answer a range of questions around the universitys research profile and potential vulnerability/strength.

Use case:As a Research Planning Officer, when influencing research policies, I want to assess individual cost centres' relative research strengths against national/mission group norms; so that I can help support the financial sustainability of the institution.

Data SourcesHESA data from HeidiKey Information Sets: http://bit.ly/1ZYnG5zWhat needs to be done and issuesTime and Effort to MarketThe research dashboard was a proof of concept using the limited research data that was available to the team. Identifying further data sources would make this into a powerful tool.Low level HESA data on researchResearch Grant Data fromFunding CouncilsEUOtherRef Data


In case anyone wants to see anther dashboard after the session38

Myles DansonSenior co-design managerShri Footring Co-design manager for [email protected]@jisc.ac.uk24/06/2016Learning Analytics39

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