Learning Analytics for Educational Design and Student Predictions: Beyond the Hype with Real-Life Examples (179547767)

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:

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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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

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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