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Learning Analytics
foundation of mass personalized education
Sander Latour
Bedankt voor de uitnodiging
Thank you for inviting me
Roadmap to the beer
The educational model
The revolution
The technology
Learning Analytics
The future of learning
Roadmap to the beer
Point out the irony of this talk
Walk out and get a beer
Alternative
What characterizes our model of education?
High school University
Traditional education
Teacher-centric
One-size fits all
Standardized
Passive
Individually
Assessment-centric
Certain ordering of topics
Does the system work?
Did it work for you? For your friends?For everybody in society?
Revolution in education
"the world of education is stirring"
Concerns on the surface
School
Society
19th
21st
Most watched?
Sir Ken Robinson
Big Breakthroughs Happen When What Is Suddenly Possible Meets What Is Desperately Necessary
- Thomas L. Friedman
Or: Old Wine In New Bottles
technically
So what is suddenly possible?
There are many developments that improve education
without (explicitly) using technology
Wait a minute
Online learning
Transformation or Digitalization?
Massive Open Online Course
Ever heard of MOOCs?
Not all Online Learning...
...is massive, open or even a course
Web-based ITS MOOC
Web-based ITS MOOC
Learning Analytics
foundation of mass personalized education
Many studentsIncreasing dataHow can you personalize?
Learning Analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environment in which it occurs.
Learners
Data
Analysis
Intervention
The Learning Analytics cycle
Doug Clow. 2012. The learning analytics cycle: closing the loop effectively.In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK '12)
Arnold, K. E. (2010). Signals: Applying Academic Analytics. Educause Quarterly, 33(1), n1
Purdue Course Signals
LearningAnalytics
EducationalDatamining
AcademicAnalytics
Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 30-32.
Learners
Data
Analysis
Intervention
The Learning Analytics cycle
Learners
Data
The Learning Analytics cycle
Browsing behaviorChat/forum/blog postsComments on chat/forum/blog postsLikes/ratingsAnswers/mistakes in quizzesTime spent on taskRequesting hintsSharing of resourcesSocial interactionsDrafts of end products
LocationBody sensorsEnvironment/contextVideo recording of the learning
Possible data sources
Learners
Data
Analysis
The Learning Analytics cycle
Recommendations for materialRecommendations for pupils / mentorsPrediction of students at riskFinding bottlenecks in contentUpdating cognitive / user modelsAnalysing video control behaviorSocial Network AnalysisDiscourse Analytics
Head pose trackingTracking speech at a table
Typical analysis
Learners
Data
Analysis
Intervention
The Learning Analytics cycle
ReflectionShowing a prediction of successOverview of what you didOverview of what the group didInsight in the group process
SuggestionLearning materialIntelligent CurriculumPotential partnersPotential mentorsBetter learning approach
Intervention via student
ReflectionShowing a prediction of successOverview of what a student didOverview of what the group didInsight in the group process
SuggestionNew learning materialPotential partnersPotential mentorsBetter teaching approach
Intervention via teacher
Adaptive learning materialAdaptive navigationAdaptive tests
Clean-up of bad material
Automatic intervention
Learners
Data
Analysis
Intervention
The Learning Analytics cycle
What are potential issues or downsides?
Critical thinking
Privacy
Lack of data
Pedagogical effect
Jumping to conclusions
Enforcing the factory model
Tool-centric vs. Learner-centric
Potential issues
What could possible scenarios be?
The future of learning
Official sources of information
People that inspired me
Sir Ken Robinson Noam Chomsky Eric Mazur
George Siemens Erik Duval Salman Khan
I'm not saying everything
should be changed
I'm saying everythingshould be questioned
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