LRT Talks 20161103 JISC Learning Analytics

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Using Data to Improve the Student Learning Experience Prof Mark Stubbs | @thestubbs

Transcript of LRT Talks 20161103 JISC Learning Analytics

Page 1: LRT Talks 20161103 JISC Learning Analytics

Using Data to Improve the Student Learning ExperienceProf Mark Stubbs | @thestubbs

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Case Study: Integrated Response to Improving Student Experience

NSS Analysis, Focus Groups, Surveys

Use of Data #1

Satisfaction means targeting

‘hygiene factors’

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University-wide Change Programme

PHASE 1

Coordinated

Step-change

Improvement

PHASE 2 Systematic

Continuous

Improvement

Listen to Student VoiceBe Bold & Joined-up

Balance Consistency & OwnershipAddress Dissatisfaction

Embed Student VoiceEmpower Programme & Module Leads

with Actionable Learner AnalyticsEmpower Students & Personal Tutors

with Actionable Learning Analytics

Refresh CurriculumRefresh Admin ProcessesWrap University Around Learner

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Wrapping the University around the Learner

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Delivering Intended Benefit of Improved Satisfaction

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Current Project(s)• University-wide Data Warehouse

powering Dashboards for Personal Tutors, Heads and Programme & Module Leaders with data from• Student Records, Moodle,

Submissions, Attendance, Surveys• Embedding in standard CMI & SEM

processes• Challenges:

• Data Quality & Ownership• Verifying Accuracy of Novel

Insights• Meeting Demand with Scarce

Expertise• ‘Grounded Theory’ analysis of

comments to target improvements in:• Technology-Enhanced Learning• Assessment

Future• Opening R&A and Staff lines of

enquiry• Student App

Microsoft BI Stack | Data from Sept 201130 Fact Tables (biggies 40-50M rows) | 42 Dimensions

Approx. 700K rows added by weekly ETL

Use of Data #2

Driving Continuous Improvement

of Student Outcomes