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    Data-driven misconception discovery in constraint-based intelligent tutoring systems (2012)

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    12642247_Myse-ICCE2012-camera ready.pdf (159.5Kb)
    Type of Content
    Conference Contributions - Published
    UC Permalink
    http://hdl.handle.net/10092/7399
    
    Publisher
    University of Canterbury. Computer Science and Software Engineering
    ISBN
    978-981-07-4649-0
    Related resource(s)
    http://www.lsl.nie.edu.sg/icce2012/wp-content/uploads/2012/11/MAIN-Conference-E-BOOK.pdf
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    • Engineering: Conference Contributions [2307]
    Authors
    Elmadani, M.
    Mathews, M.
    Mitrovic, Antonija cc
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    Abstract

    Students often have misconceptions in the domain they are studying. Misconception identification is a difficult task but allows teachers to create strategies to appropriately address misconceptions held by students. This project investigates a data-driven technique to discover students' misconceptions in interactions with constraint-based Intelligent Tutoring Systems(ITSs). This analysis has not previously been done. EER-Tutor is one such constraint-based ITS, which teaches conceptual database design using Enhanced Entity-Relationship (EER) data modelling. As with any ITS, a lot of data about each student's interaction within EER-Tutor are available: as individual student models, containing constraint histories, and logs, containing detailed information about each student action. This work can be extended to other ITSs and their relevant domains.

    Citation
    Elmadani, M., Mathews, M., Mitrovic, A. (2012) Data-driven misconception discovery in constraint-based intelligent tutoring systems. Singapore: 20th International Conference on Computers in Education (ICCE), 26-30 Nov 2012. 9-16.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    Misconceptions; data mining; constraint-based modeling
    ANZSRC Fields of Research
    08 - Information and Computing Sciences::0806 - Information Systems::080602 - Computer-Human Interaction
    08 - Information and Computing Sciences::0801 - Artificial Intelligence and Image Processing::080105 - Expert Systems
    39 - Education::3904 - Specialist studies in education::390405 - Educational technology and computing
    Rights
    https://hdl.handle.net/10092/17651

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