LASI-Spain eMadridCarlos Delgado Kloos
Univ. Carlos III de Madrid, www.it.uc3m.es
Red eMadrid, www.emadridnet.org
LASI
SOLAR: Society for Learning Analytics Research
Learning Analytics Summer InstituteStanford U, 1-5 July 2013LASI-local events
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LASI-local
Local events around the world:Aalborg (.dk)Amsterdam (.nl)Boston (.us)Edinburgh (.uk)Granada (.es)Hong Kong (.hk)Lyon (.fr)Madrid (.es)Pretoria (.za)
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LASI-Spain eMadrid (ES)
Organized by eMadrid at UC3MMorning Session:
Stanford U presentations from previous days
Afternoon Session:Local presentations at UC3M
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LASI-Spain eMadrid (ES)
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LASI-Spain eMadrid (ES)
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What are they thinking about?
How boring!
I don't get anything!
How cool!
Are they following?
We'll find out at the exam
Fast Feedback Loop
Waiting until the exam is too late
Fast feedback cycle important for learning
Remediation when it most effective
Probe information during the learning process
Adapt teaching to learning
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(Big) Data
Highernumber of people (MOOCs)number of variables (pervasive technologies)number of time points
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Learning Interactionsin the Physical World
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prof student student
colab
lecture
tutor
read practice
exam practiceassess
Analytics
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No Data
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studentread
Data
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studentread
data
Data
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studentread
data
Learning Interactionsin the Digital World
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prof student student
colab
read
lecture
practice
tutor
exam practiceassess
Analytics
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data
info
action
visualization
Data
What kind?ClicksTimesUsers
ActivityAdvanceAccomplishment of exercisesUse of hintsSocial behaviour
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Information
What kind?Present status
Prediction aboutthe future
Plans for changingthe future
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Information
For whom? Learner (pilot) Teacher (air traffic controller)
Instructional designer Curriculum planner Institution Country authority Employer Tool developer
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Processing
Classical test theory
Item response theory
Aggregation
Averages
Classifiers
Markov models
…
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Visualization
a
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Action
Repetition
Reinforcement
Remediation
Rescheduling
Social interaction
…
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Issues
Privacy
Causality
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!
Privacy
By capturing data from persons,one has to be very careful withhow and what data is captured,and how it is used, etc.
The correct legal measureshave to be taken
Who owns the data?When it is raw?When it is processed?
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Causality
The brain is a big unknown
We know very little abouthow learning works
By correlating a few data,we are just scratching the surface
Learning Analytics is no silver bullet
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Conclusion
Turn the learning process into a controlled process,as many other processes (business, health, web)
Relevant are speed of feedback and amount of data
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Talks (be punctual!)
15:15-15:45: Á. Serrano (UCM): "Game analyticsand educational videogames: Can we know howmany students learn while playing videogames? "
15:45-16:15: R. Crespo, I. Gutiérrez (UC3M):"Learning analytics support for just-in-time teaching"
16:15-16:45: P. Muñoz Merino (UC3M): "Evaluationin e-learning platforms using learning analytics"
16:45-17:00: Break
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Talks (be punctual!)
17:00-17:30: G. Robles, J. González Barahona (URJC): "Lessons learned from ten years of software analytics that could be helpful for learning analytics"
17:30-18:00: J. García Zubía (U Deusto):"Learning analytics and remote experimentation:First experiences with Weblab-Deusto"
18:00-18:45: Live from Stanford U:Plenary: "Chief Data Scientists"Chair: Dragan Gasevic (Athabasca U)Speaker: Piotr Mitros (edX)
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