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Research and Deployment of Analytics in Learning Settings
 

Research and Deployment of Analytics in Learning Settings

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    Research and Deployment of Analytics in Learning Settings Research and Deployment of Analytics in Learning Settings Presentation Transcript

    • Research and Deployment of Analytics in Learning Settings
      Katrien Verbert
      ARIADNE/K.U.Leuven
    • overview
      visualizing activities for self-reflection and awareness
      dataTEL initiative
      collection and sharing of data
      research on recommendation for learning
      visualizing usage of widgets and services in PLEs
    • visualizing activities for self-reflection and awareness
    • problem
    • objectives
      self-monitoring for learners
      awareness for teachers
      learning resource recommendation
    • student activity monitor
      http://ariadne.cs.kuleuven.be/monitorwidget-lak11/
    • student activity monitor
    • student activity monitor
    • student activity monitor
    • data & deployments
      Contextualized Attention Metadata (CAM) data
      deployed in:
      ROLE PLE
      RWTH-Aachen engineering
      Moodle
    • evaluation
      usability and user satisfaction evaluation
      12 CS students
      2 evaluation sessions:
      task based interview with think aloud (after 1 week of tracking)
      user satisfaction (SUS & MSDT) (after 1 month)
      • in general, people understand the visualizations well!
      • some issues were uncovered...
      learnability, errors & efficiency
      Details in:
      StenGovaerts, Katrien Verbert, JorisKlerkx, Erik Duval (2010). Visualizing Activities for Self-reflection and Awareness. Proceedings of the 9th International Conference on Web-based Learning, ICWL 2010
    • user satisfaction
    • use it!?
      we can put your data into the tool!
      we would like to use your course for evaluation!
      Questionnaire: http://bit.ly/laksurv
    • dataTEL initiative
    • What is dataTEL?
      dataTEL is a Theme Team funded by the STELLAR network of excellence.
      It addresses 2 STELLAR Grand Challenges
      Connecting Learner
      Contextualisation
    • dataTEL::Objective
      Five core questions:
      How can data sets be shared according to privacy and legal protection rights?
      How to develop a respective policy to use and share data sets?
      How to pre-process data sets to make them suitable for other researchers?
      How to define common evaluation criteria for TEL recommender systems?
      How to develop overview methods to monitor the performance of TEL recommender systems on data sets?
      Standardize research on recommender systems in TEL
    • Free
      the data
      By HendrikDrachsler & Tom Raftery http://bit.ly/e8mLfY
    • Why?
      By HendrikDrachsler & Tom Raftery http://bit.ly/e8mLfY
    • Because we
      will get new
      insights
      By HendrikDrachsler & Tom Raftery http://bit.ly/e8mLfY
    • dataTEL challenge & dataTEL cafe event
      a call for TEL datasets
      several datasets submitted
      http://bit.ly/ieqmWW
    • Recommendation for learning?
      Users who bought the same product also bought product B and C
      Details on Tuesday:
      Katrien Verbert, HendrikDrachlser, Nikos Manouselis, RiinaVuorikari and Erik Duval
      Dataset-driven Research to Improve TEL Recommender Systems
    • visualizing PLE usage
    • ROLE vision: empower learners to build their own PLE
      Responsiveness (reflective support)
      User-centred (operational support)
      R. Klamma
    • first prototype
      Username: role@test.com
      Password: rolespace
      http://graaasp.epfl.ch/role_project
    • Pre-analysis Layer
      SOAP
      request
      REST
      request
      JSON
      format
      XML
      format
      CAM Storage Layer
      CAM
      Dashboard
    • 1
      2
      3
      5
      4
    • Thank You!Questions?
      slides will appear on http://www.slideshare.net/kverbert
      Email: ariadne@cs.kuleuven.be