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How quickly do we learn conceptual models?

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  • Palash Bera
  • Geert Poels

Abstract

In organisations, conceptual models are used for understanding domain concepts. Learning the domain from models is crucial for the analysis and design of information systems that are intended to support the domain. Past research has proposed theories to structure conceptual models in order to improve learning. It has, however, never been investigated how quickly domain knowledge is acquired when using theory-guided conceptual models. Based on theoretical arguments, we hypothesise that theory-guided conceptual models expedite the initial stages of learning. Using the REA ontology pattern as an example of theoretical guidance, we show in a laboratory experiment how an eye-tracking procedure can be used to investigate the effect of using theory-guided models on the speed of learning. Whereas our experiment shows positive effects on both outcome and speed of learning in the initial stages of learning, the real contribution of our paper is methodological, i.e. an eye-tracking procedure to observe the process of learning from conceptual models.

Suggested Citation

  • Palash Bera & Geert Poels, 2019. "How quickly do we learn conceptual models?," European Journal of Information Systems, Taylor & Francis Journals, vol. 28(6), pages 663-680, November.
    • Handle: RePEc:taf:tjisxx:v:28:y:2019:i:6:p:663-680
    DOI: 10.1080/0960085X.2019.1673972
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