The potential of learning from erroneous models: comparing three types of model instruction

Frances Martine Wijnen, Frances M. Wijnen, Y.G. Mulder, Stephen M. Alessi, Lars Bollen

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3 Citations (Scopus)
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Abstract

Learning from computer models is a promising approach to learning. This study investigated how three types of learning from computer models can be applied to teach high-school students (aged 14–17) about the process of glucose–insulin regulation. Two traditional forms of learning from models (i.e. simulating a predefined model and constructing a model) were compared to learning from an erroneous model. In this innovative form of learning from computer models, students are provided with a model that contained errors to be corrected. As such, students do not have to engage in the difficult task of constructing a model. Rather, they are challenged to work with and correct the model in order for the simulation to generate correct output. As predicted, learning from erroneous models enhances learning of domain-specific knowledge better than running a simulation or constructing a model.
Original languageEnglish
Pages (from-to)250-270
JournalSystem dynamics review
Volume31
Issue number4
DOIs
Publication statusPublished - 11 Feb 2015

Keywords

  • METIS-316249
  • IR-100056

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    Wijnen, F. M., Wijnen, F. M., Mulder, Y. G., Alessi, S. M., & Bollen, L. (2015). The potential of learning from erroneous models: comparing three types of model instruction. System dynamics review, 31(4), 250-270. https://doi.org/10.1002/sdr.1546