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Attendance Monitoring in Higher Education Automated, cost-effective & essential data collection for descriptive & predictive learning analytics Rob Wyn Jones – Jisc Chris Stedham – Bath Spa University

Attendance monitoring in higher education

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Page 1: Attendance monitoring in higher education

Attendance Monitoring in Higher EducationAutomated, cost-effective & essential data collection for descriptive & predictive learning analytics

Rob Wyn Jones – JiscChris Stedham – Bath Spa University

Page 2: Attendance monitoring in higher education

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Attendance data – emergence, growth & relevancyRob Wyn Jones – Jisc

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Why Attendance Monitoring?> Continual driver was, and still is, UKVI (auditable)> Attendance slowly becoming a key retention

indicator> Used to enforce student attendance policies/

procedures> Could really be a key predictive indicator for

campus-based HEIs (VLE vs Attendance: consistency & coverage)

> OU vs the rest – spot the difference?> Automation vs Manual data collection – resource

overheads> Several HEIs implementing bespoke/ self-made

solutions> Several HEIs implementing expensive off-the-shelf

solutions

03/05/2023

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Market Research – Jisc Discovery> Jisc Discovery – UCISA, LA Network + other

channels> 61 HEIs responded> 51% use manual solutions, 41% automated

solutions> No clear leader in terms of preferred solution /

vendor> Need for close & seamless integration with

timetabling/ SRS> Simply too expensive – hardware, licenses,

support> Learning Analytics a driver; Jisc LA xAPI

integration in place> Jisc looking to support & delivery HEI pilots for

cost-effective automated attendance monitoring, sometime in 2017

03/05/2023

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Next Steps – Talk to us!> Looking for HEIs interested in piloting cost-

effective solutions (hardware & software), which are already in development or full-service operation within the HE sector

> Jisc’s aim would be to support & possibly partner with HEIs (subject to feasibility and successful pilot) to adoption of such solutions, to save the sector significant sums of money;

> Anticipated as a key consistent engagement indicator: cost-effective campus-wide adoption across several+ HEIs needed, sooner rather than later (in-budget), to further enable learning analytics/ student retention and attainment in UK HE;

03/05/2023

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Homegrown Attendance MonitoringChris Stedham – Bath Spa University

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Our Journey to Attendance Monitoring>Gemini 2000 card reader with in-

house software to gather taps>Student Timetable for attendance data

– Scientia>Combine card reads and attendance

data to monitor attendance – QlikView>Heavily utilized in-house skills to

achieve this.

03/05/2023

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Challenges….>Academic colleagues do not always use the

timetabled space in the way expected>We launched as a trial, with features missing

which we’ve had to rapidly improve>i.e. tapping students in who haven’t done it in time

>Biggest delay to initial project was installing readers in Grade 1 listed, concrete/glass buildings

03/05/2023

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What next…..>Phase 2 of project>Roll out to other campuses>Facility to input attendance retrospectively>Hand-held monitoring devices>Improved reporting

– Provide data to tutors

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Cost-effective attendance – Prifysgol Aberystwyth UniversityRob Wyn Jones – Jisc

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Architecture (in-house development)> Pilot - IS & Comp Sci jointly> SRS (in-house: ASTRA)> Scientia Integration> Campus-wide rollout = LIVE> ~ 300 access points> Multiple points in some rooms> Low (seriously low) cost!> Minimal Support

03/05/2023

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Now and next – campus wide learning analytics!> Interventions based on attendance – aligned to policy, UKVI> Aladdin – student/ staff tutoring system & dashboards> Key to Learning Analytics (predictive), back to Aladdin (+ VLE)> Staff T+A, ABW integration, exam attendance, security> Improved efficiency: by reducing the level of manual

recording from 371k in 14-15 S1 to 62k in 15-16> Increased attendance data collection: 371k in 14-15 S1

to 514k in 15-16 S1

03/05/2023

2015 2016Semester1 Semester 2 Semester 1 Semester 2

Auto = collected via card swipe. Manual = entered via SAMS. Auto Manual Auto Manual Auto Manual Auto ManualAttendance recorded - 285,963 - 203,228 343,815 48,437 - -Not attended - 85,811 - 100,238 108,095 14,099 - -

Statistic Details

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jisc.ac.uk

Except where otherwise noted, this work is licensed under CC-BY-NC-ND

03/05/2023

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Contact – Jisc Learning Analytics ProgrammeRob Wyn JonesSenior Data & Analytics [email protected]

Attendance Monitoring in Higher Education

Slide

Chris StedhamHead of IT Service Planning and [email protected]