skip to main content
10.1145/3158191.3158200acmotherconferencesArticle/Chapter ViewAbstractPublication PageseooltConference Proceedingsconference-collections
research-article

Representations of equation-based models are not created equal

Authors Info & Claims
Published:01 December 2017Publication History

ABSTRACT

For equation-based modelling languages, modelling experts have many degrees of freedom when building a model from scratch. One of the most basic choices the expert faces is the mode of representation. The same system can be represented for instance as a block-diagram, by writing down the physical equations, by writing an algorithm, or by graphically connecting ready-made subcomponents. To give some guidance in this aspect, an experiment was conducted to measure the effects of different representations on various tasks. Participants had to identify models and predict their transient response. Both the time to execute the task and the correctness of the answer were measured. Participants also had to rate their confidence regarding the models. Results showed that tasks were executed much faster for graphical representations than for block-digrams. Equation-based and algorithm-based models can be grouped in the middle. The same results hold for rated confidence. Interestingly, the amount of errors was similar for all representations. Apparently, modelling experts largely compensate for difficulty by taking their time.

References

  1. James V Bradley. 1958. Complete counterbalancing of immediate sequential effects in a Latin square design. J. Amer. Statist. Assoc. 53, 282 (1958), 525--528.Google ScholarGoogle ScholarCross RefCross Ref
  2. Ap Dijksterhuis and Ad Van Knippenberg. 1998. The relation between perception and behavior, or how to win a game of trivial pursuit. Journal of personality and social psychology 74, 4 (1998), 865.Google ScholarGoogle ScholarCross RefCross Ref
  3. Thomas RG Green and R Navarro. 1995. Programming plans, imagery, and visual programming. In Human Computer Interaction. Springer, 139--144.Google ScholarGoogle Scholar
  4. Thomas R. G. Green and Marian Petre. 1996. Usability analysis of visual programming environments: a cognitive dimensions framework. Journal of Visual Languages and Computing 7, 2 (1996), 131--174.Google ScholarGoogle ScholarCross RefCross Ref
  5. Sture Holm. 1979. A simple sequentially rejective multiple test procedure. Scandinavian journal of statistics (1979), 65--70.Google ScholarGoogle Scholar
  6. Jill H Larkin and Herbert A Simon. 1987. Why a diagram is (sometimes) worth ten thousand words. Cognitive science 11, 1 (1987), 65--100.Google ScholarGoogle Scholar
  7. Dominik J Leiner. 2014. SoSci survey (version 2.5.00-i){computer software}. (2014).Google ScholarGoogle Scholar
  8. Margaret Shih, Todd L Pittinsky, and Nalini Ambady. 1999. Stereotype susceptibility: Identity salience and shifts in quantitative performance. Psychological science 10, 1 (1999), 80--83.Google ScholarGoogle Scholar
  9. Steven J Spencer, Claude M Steele, and Diane M Quinn. 1999. Stereotype threat and women's math performance. Journal of experimental social psychology 35, 1 (1999), 4--28.Google ScholarGoogle ScholarCross RefCross Ref
  10. Claude MSteele. 1997. A threat in the air: How stereotypes shape intellectual identity and performance. American psychologist 52, 6 (1997), 613.Google ScholarGoogle Scholar
  11. Iris Vessey and Dennis Galletta. 1991. Cognitive fit: An empirical study of information acquisition. Information systems research 2, 1 (1991), 63--84. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. EJ Williams. 1949. Experimental designs balanced for the estimation of residual effects of treatments. Australian Journal of Chemistry 2, 2 (1949), 149--168.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Representations of equation-based models are not created equal

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          EOOLT '17: Proceedings of the 8th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools
          December 2017
          95 pages
          ISBN:9781450363730
          DOI:10.1145/3158191
          • General Chair:
          • Dirk Zimmer,
          • Program Chair:
          • Bernhard Bachmann

          Copyright © 2017 ACM

          Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 1 December 2017

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate10of11submissions,91%
        • Article Metrics

          • Downloads (Last 12 months)2
          • Downloads (Last 6 weeks)0

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader