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Jisc Learning analytics – The FE story>Roy Currie, Bedford College>Aftab Hussain, Bolton College>Andy Cowan, Dumfries and Galloway College>Conrad Taylor, City of Wolverhampton College
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Learning Analytics for FE Colleges 3
IntroductionShri Footring, Senior co-design manager, JiscRob Wyn Jones, Senior data and analytics integrator - Jisc
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Learning Analytics for FE Colleges 4
Workshop structure>Welcome and introduction>Student data / activity – Rob Wyn Jones>The Bedford College story – Roy Currie>Integration of Grade Tracker with the
Jisc Learning Records Warehouse>Development of a Unified Data Definition for both
FE and HE students>Questions and panel discussion
- with Aftab Hussain, Andy Cowan, Conrad Taylor and Roy Currie
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BackgroundThe needs of FE colleges are different from those of universities>Complexity and diversity of both the types of learners, the
programmes of learning and of awarding bodies>Strategic importance of English, maths and work experience>Specific data, such as GCSE point score (prior learning) is of key
importance>A number of sophisticated systems which capture details of
students are performing are already available and in use A group of colleges and consultants are working on tailoring the Jisc Learning analytics solutions to the needs of FE Colleges
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Student Data / Activity - What are your experiences?
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Learning Analytics for FE Colleges 6
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Overview – Learning analytics (LA) for FE (Pilot journey)>Collect live academic progression data, then
historical >UDD – Unified Data Definition (HE and FE hybrid data spec)>xAPI – used to describe and store activity data (standard)
>ETL tools for student systems, Data Validation Tool (web)
>Provide Dashboard (DataX) for Live Descriptive Analytics
>Pseudo-LAP for entry-level analytics (progression triggers)
>Study Goal (iOS/ Android) Pilot>Premium (vendor) LAP for Predictive Analytics
(historical data)>Priority for 16-17: UDD bend to fit FE - piloting 4 to
6 FEIs
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Learning Analytics for FE Colleges 8
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Activity - Additional data sources for LA / BI purposes>What additional (student or demographic-centric) data
or datasets could you use in your institution for predictive analytics, beyond the standard data provided for ILR? Recruitment? Surveys?
>Is VLE data a key and consistent engagement indicator at your institution? If not, in addition to attendance, what other engagement or activity source would you have or like access to?
>What issues do you have / do you foresee with data collection at your institution? Are these business process and/ or technical?
>Can Jisc help with automating collection or extraction of certain student data / feedback, which are of benefit for BI or learning analytics?
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Integration of Bedford College Grade Tracker Jisc Learning Records WarehouseRoy Currie, Director of information and learning technologies, Bedford College
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Transforming Moodle>Adopted Moodle in 2009>Open source solution so customisable>Account and enrolment data driven from MIS system >Development expertise in Learning Technologies Team>We wanted to capitalise on available data and avoid
rework>We wanted to fill in the missing areas of Moodle and
provide a single integrated tool for the management of all aspects of teaching in learning
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The Plug-in Modules>Four enterprise-level Moodle extension modules
developed>GradeTracker>ePLP>Reporting Dashboard>Guardian/Employer Portal
>Funded by Jisc and Ufi Trust for development of community-release modules
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ePLP: Key Features>Includes punctuality and attendance, register
information, timetables, tutorial records, SMART targets, comments, qualifications on entry etc.
>Highly-modular system aggregates all of the key information relating to each learner in one place
>Ensures that the learner and all members of the teaching team share a common view
>Very easy to customise and extend – new modules added to support work experience tracking, enrichment and health needs
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GT: Key features>Fulfils similar role to tools like ProMonitor and eTracker
– can track nearly all main qualification types>Provides highly-visual tools to help learners and
teachers monitor progress against targets>Good tools to support ease of marking and updating
for teachers – including off-line spreadsheets>Avoids double-work as assessment setting, feedback
provision and progress tracking all take place within Moodle
>Very positive response from learners – they chase teachers to get marks put up on GradeTracker
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Data, Reporting tools and Learning analytics>Wide selection of preconfigured reports available and
tools for building custom reports>Drill down whole institution -> department -> course -
> learner>Automatic scheduling and email alerts>Ideal architecture for generation/capture of xAPI
events>Opportunity to use ePLP as xAPI aggregator>GT provides good source of unit information for UDD>GradeTracker provides rich source of novel xAPI data>Qualification progress and assessment submission
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Early indication of learner outcomesPredictions are based on individual PMD criteria achieved compared with maximum attainable at time. Also gives an indication of how much assessment has taken place on the course.
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Detailed Course-level analysisPredictions are based on individual PMD criteria achieved compared with maximum attainable at time. Also gives an indication of how much assessment has taken place on the course
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Impact and benefits of GradeTracker and ePLP>Moodle ‘centre stage’ in teaching and learning
>Growing momentum in eLearning development, especially on-line submission and management of assessment
>Provided fertile grounds for embedding eLearning in programmes of study (FELTAG Recommendations)
>Cost and efficiency gains – savings against the use of third-party systems plus more efficient use of teacher time
>Good feedback from learners regarding awareness of targets and their progress against them
>Enthusiastic feedback from Ofsted
>Rich source of data and analysis with regard to learner progress and behaviour – Jisc Learner Analytics
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Access the modules>If you are interested in trying out the GradeTracker
and ePLP in your own college>Visit http://moodleportal.bedford.ac.uk for more
details on all of the modules>Email: [email protected] to have an account set
up to access the download areas.
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Development of a Unified Data Definition for both FE and HE StudentsRoy Currie, Director of information and learning technologies, Bedford College
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Project background and Progress: 1>The Unified Data Definition: UDD
>Relatively static information about the learner, course etc.>Initial progress with examining the UDD requirements of the HE
sector>New focus on addressing the needs of FE institutions>Key Issues:
– Consideration of the analytics implications of full programmes of learning
– Complexity and diversity of FE qualifications and awarding bodies
– Diversity of learning modes: e.g. FT 16-18, Apprenticeships, HE in FE etc.
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Project background and Progress: 2>Current focus is on finalising V1.3.0 of the UDD>V1.3.0 is being developed with active consideration given to FE
requirements>Next step is to test the integrity of the UDD with model data
representing a wide range of potential learners that could be encountered in FE
>Once UDD has been proven to provide a valid representation for FE learners work will start on examining xAPI statements.
>Many aspects of the programme of learning, such as work experience, enhancement and tutorials can be described as learning events and are best reflected in xAPI statements
>This will compliment other rich ranges of learning behaviours such as library and computer use, VLE access, assessment submission behaviours and qualification completion progress 02/05/20
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jisc.ac.uk
Except where otherwise noted, this work is licensed under CC-BY-NC-ND
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Learning Analytics for FE Colleges 29 > >
Jisc Learning analytics onboarding for FE:Sarah Dunne, Senior co-design manager, JiscPaul Bailey, Senior co-design manager, JiscRob Wyn JonesSenior data and analytics integrator [email protected] FootringSenior co-design [email protected]
Contacts
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