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Learning Analytics for Educational
Design and Student Predictions:
Beyond the Hype with Real-LifeExamples
Join presentation with “demo” LectureTools account:
1. Go to
http://my.lecturetools.com
•Login with e-
mail “demo2721” (no password required)
• Click
on subsequent page.
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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Learning Analytics for
Educational Design and
Student Predictions
Nynke Kruiderink – University of Amsterdam
Nynke Bos – University of Amsterdam
Perry J. Samson –
University of Michigan- Ann Arbor
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7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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Who we are
Nynke BosHead of ICT, Faculty of Humanities
Nynke KruiderinkTeamleader Educational Technology of Social Sciences, Faculty of Social and BehavioralSciences
University of Amsterdam, The Netherlands30,000 students
5000 employees
annual budget 600 Million euro‟s (810 Million dollars) 57 bachelor‟s programmes
92 masters‟s programmes
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7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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Lessons LearnedFeb 2012-present
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Proof of Concept
Two tiered:
Interviews with lecturers, professors, managersGather and store data in central place for easy
access
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Lessons Learned
1. Emotional response to „Big Brother' aspect of
accessing data2. Data from LMS not detailed enough (folder
based not file based)
3. 50% of learning data available
4. Piwki, not secure enough
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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Next steps
Focus group Learning Analytics
Professor Erik Duval – KU Leuven
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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What is the problem?
Recorded lectures
Recording of face-to-face lectures
No policy at the University of Amsterdam
Different deployment throughout the curriculum
Not at all (fears/ emotional)
Week after the lecture
Week before the assessment
And all the scenario‟s in between
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Student vs. Policy
Students „demanded‟ policy
Quality assurance department wanted insight intoacademic achievement before doing so
Development of didactic framework
Research: Learning Analytics
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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Design
Two courses on psychology
Courses run simultaneously
Intervention in one condition, but not in the other
A thank you
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Data collection
Viewing of recorded lecture
Lecture attendance per lecture
Final grade on the course more segmented view
Grades on previous courses
Distance to the lecture hall
Gender Age
Hits in Blackboard
Inventory Learning Style (ILS: Vermunt, 1996)
Students were asked to fill out a consent form
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Lessons Learned
Let people know what you are doing
Data preparation: fuzzy, messy Choose the data
Simplify the data
Keep an eye on the prize
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LectureTools: Student View
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LectureTools: Responder
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LectureTools: Questions
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LectureTools: Analytics
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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LectureTools: Analytics
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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LectureTools: Analytics
7/27/2019 Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)
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LectureTools: Analytics
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LectureTools: Analytics