Using Co-Lab to build System Dynamics models: Students’ actions and on-line tutorial advice

Crescencio Bravo, Wouter van Joolingen, Ton de Jong

    Research output: Contribution to journalArticleAcademicpeer-review

    40 Citations (Scopus)

    Abstract

    Modeling offers a promising form of constructivist learning for students. By making and executing models of dynamic systems in a computer environment, students are stimulated to learn about the specific domain that is modeled as well as about the process of modeling in general. However, learning by modeling also leads to characteristic student mistakes, based on a combination of faulty domain knowledge and insufficient modeling skills. In this article, we describe a method of generating advice to students during their modeling process. The on-line advice system was informed by our observations of a teacher who gave advice via a textual communication tool to students building models with a System Dynamics model editor. The first version of the on-line advice system was evaluated in two ways: first, three teachers evaluated the advice the system generated for students’ final solutions; second, we analyzed the advice the system provided as it was used by a sample of students who were building a physics model. These evaluations showed that the overall approach, including matching a student solution to a family of reference solutions together with the other mechanisms of the advice system, is valid. However, they also highlighted the difficulty of building ‘intelligent’ support to help students to improve their models and gain modeling expertise. The article concludes with a discussion of our current efforts to improve the advice system based on the lessons learnt, which suggest extension of the range of solution representations and of the operations of the advice method.
    Original languageUndefined
    Pages (from-to)243-251
    JournalComputers & education
    Volume53
    Issue number2
    DOIs
    Publication statusPublished - 2009

    Keywords

    • Intelligent Tutoring Systems
    • Inquiry learning
    • System Dynamics modeling
    • Solution analysis
    • IR-67982

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