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Learnometrics Keynote LAK2011
 

Learnometrics Keynote LAK2011

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Keynote at Learning Analytics and Knowledge 2011

Keynote at Learning Analytics and Knowledge 2011

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    Learnometrics Keynote LAK2011 Learnometrics Keynote LAK2011 Presentation Transcript

    • Learnometrics: Metrics for Learning (Objects) Xavier Ochoa Escuela Superior Politécnica del Litoral Guayaquil, Ecuador
    • http://www.slideshare.net/xaoch
    •  
    •  
    • Research about Learning Objects But what?
    • What is a Learning Object? Not a good idea
    • What is a Learning Object? Not a good idea
    • How many learning objects are published? How many learning objects are reused? How many objects are produced by each teacher? How many times a learning object is reused? What is the average size of a LO repository?
    •  
    • Learning Object Repositories
    • Size of Repositories Repository Referatory OCW LMS IR
    • A medium sized LMS has more objects than MERLOT
    • Distribution of Objects
    • There is a long tail of resources How can we find them?
    • Growth – in Objects
    • Growth in Contributors
    • Growth is Linear Ouch!
    • But there is hope…
    • Connexions Growth in Contributors
    • Connexions Growth in Objects
    •  
    • Objects per Contributor LORP - LORF Lotka / Log-Normal “ fat-tail”
    • Objects per Contributor OCW - LMS Weibull “ fat-belly”
    • Objects per Contributor IR Lotka high alpha “ light-tail”
    • The key is the engagement There must be a value proposition
    • Engagement
    • If only our LMSs could be our repositories OERs could be the key
    • Reuse of LO
    • Reuse is the raison d’être of Learning Objects But very little is know about actual reuse
    • Reuse Paradox
    • Measuring Reuse
    • Measuring Reuse
    • Measuring Reuse ~20%
    •  
    • REUSE IS HAPENNING with or without us Let’s help to make it easier
    • Our understanding of Re-use needs to be re-examined We need more studies!
    • Popularity vs. Reuse
    • Distribution of Reuse
    • We call this line of research Learnometrics Hey, it was good for my thesis 
    • Learnometrics
      • Study empirical regularities on data
      • Develop mathematical models
      • To understand the influence/impact
      • Produce useful metrics
    • Learnometrics
      • Study empirical regularities on data
      • Develop mathematical models
      • To understand the influence/impact
      • Produce useful metrics
    • Learning Analytics
      • Study empirical regularities on data
      • Develop mathematical models
      • To understand the influence/impact
      • Produce useful metrics
    • Educational Data Mining?
      • Study empirical regularities on data
      • Develop mathematical models
      • To understand the influence/impact
      • Produce useful metrics
    • Learngin Analytics or Educational Data Mining or Educational Research The same or different?
    •  
    • The questions are the same The difference is in the kind of answers
    • Gracias / Thank you / Merci Xavier Ochoa [email_address] http://ariadne.cti.espol.edu.ec/xavier Twitter: @xaoch