tribal learning analytics r&d project - solar storm presentation
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Tribal Learning Analytics R&D Project6th December 2012
Chris Ballard – Innovation Consultant (Analytics)
@chrisaballard
www.triballabs.net
Who are we?
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Our work with Learning Analytics
“Every ….. days we create as much information as we did from the dawn of civilization up until 2003. That’s something like five exabytes of data.”
Eric Schmidt (Google CEO)
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Do we have Big Data in Higher Education?
Tribal Learning Analytics R&D Project
Do we have Big Data in Higher Education?
Yes, but…
Big is relative.
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Factors affecting Retention and Success
Academic Integration
Social Integration Preparation for HE
CircumstancesEngagement
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Factors affecting Retention and Success
Academic Integration
Social Integration Preparation for HE
CircumstancesEngagement
GradesProgress
VLE ActivityLibrary Activity
Social Background
ProximityStudent Debt
Forum interactionSocial networks
DemographicsQualifications
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Objectives for project
Steer students towards success
Enable “actionable insights”
Give staff better insight
Identify potential problem areas
Comparison to peers
Predict which students who may require additional support
Supporting the student
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Student “Success”
Withdrawal
True False
Quantitative
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Student “Success”
Withdrawal Success
PassedReached average
Completed
Exceeded expectatio
ns
Academic Success
Satisfaction
…
True False
Quantitative Qualitative
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Quantifying academic success
All students
Median Grade
Cluster
Median grade for cluster
Individual
Student
Attainment of cluster median grade
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Student Information System
Activity Data
Academic performance at
entrance
UCAS Application
Attendance
Contact with support services
VLE Usage
Library Usage
Proximity Door access
Social background
Assessments
Course Enrolment
Fees
Engagement
Predictive Model
Demographics
Contact with tutors
Campus PC Usage
Social interaction
Preparation for HE
Future data sources
Academic Integration
Open Data
IMD Spatial
Social Integration
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Predictions should help staff make informed decisions
Predictions from a model are just part of the picture
Predictions should be combined with staff experience and knowledge
Predictions should empower staff to ask the right questions
Visualising Predictions
Predictions are a tool to help staff understand where there might be issues and inform subsequent discussions
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Student Success
Often focused on “academic success”
Are the current definitions of student success too simplistic?
Predictive Model
The model needs to be “transparent”
Allow practitioners to see where likely issues may lie
Combining diverse models results in greater predictive accuracy
Summary
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Data Visualisation for Learning Analytics
Should be focused on providing information to help inform discussions
Supplement predictions with analytics based on underlying activity data
Comparison with cohort enables comparative judgements to be made
Actionable Insights
Embedding intervention recording, management and workflow
Feedback loop to understand whether interventions make a difference
Summary
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Chris BallardInnovation Consultant, Tribal
twitter: @chrisaballardblog: www.triballabs.net
Tribal Learning Analytics R&D Project