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How Do We Understand a System with (So) Many Diagrams? Cognitive Integration Processes in Diagrammatic Reasoning

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  • Jinwoo Kim

    (Yonsei University, Department of Business Administration, Seoul, 120–749, Korea)

  • Jungpil Hahn

    (University of Minnesota, Information and Decision Sciences, Minneapolis, Minnesota 55455)

  • Hyoungmee Hahn

    (LG Hitachi, Seoul, 150–756, Korea)

Abstract

In order to understand diagrammatic reasoning with multiple diagrams, this study proposes a theoretical framework that focuses on the cognitive processes of perceptual and conceptual integration. The perceptual integration process involves establishing interdependence between relevant system elements that have been dispersed across multiple diagrams, while the conceptual integration process involves generating and refining hypotheses about a system by combining higher-level information inferred from the diagrams. This study applies a diagrammatic reasoning framework of a single diagram to assess the usability of multiple diagrams as an integral part of a system development methodology. Our experiment evaluated the effectiveness and usability of design guidelines to aid problem solving with multiple diagrams. The results of our experiment revealed that understanding a system represented by multiple diagrams involves a process of searching for related information and of developing hypotheses about the target system. The results also showed that these perceptual and conceptual integration processes were facilitated by incorporating visual cues and contextual information in the multiple diagrams as representation aids. Visual cues indicate which elements in a diagram are related to elements in other diagrams; the contextual information indicates how the individual datum in one diagram is related to the overall hypothesis about the entire system.

Suggested Citation

  • Jinwoo Kim & Jungpil Hahn & Hyoungmee Hahn, 2000. "How Do We Understand a System with (So) Many Diagrams? Cognitive Integration Processes in Diagrammatic Reasoning," Information Systems Research, INFORMS, vol. 11(3), pages 284-303, September.
    • Handle: RePEc:inm:orisre:v:11:y:2000:i:3:p:284-303
    DOI: 10.1287/isre.11.3.284.12206
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    References listed on IDEAS

    as
    1. Jinwoo Kim & F. Javier Lerch, 1997. "Why Is Programming (Sometimes) So Difficult? Programming as Scientific Discovery in Multiple Problem Spaces," Information Systems Research, INFORMS, vol. 8(1), pages 25-50, March.
    2. Iris Vessey & Dennis Galletta, 1991. "Cognitive Fit: An Empirical Study of Information Acquisition," Information Systems Research, INFORMS, vol. 2(1), pages 63-84, March.
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    Citations

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    Cited by:

    1. Bin Zhu & Stephanie A. Watts, 2010. "Visualization of Network Concepts: The Impact of Working Memory Capacity Differences," Information Systems Research, INFORMS, vol. 21(2), pages 327-344, June.
    2. Merete Hvalshagen & Roman Lukyanenko & Binny M. Samuel, 2023. "Empowering Users with Narratives: Examining the Efficacy of Narratives for Understanding Data-Oriented Conceptual Models," Information Systems Research, INFORMS, vol. 34(3), pages 890-909, September.
    3. Andrew Burton-Jones & Peter N. Meso, 2006. "Conceptualizing Systems for Understanding: An Empirical Test of Decomposition Principles in Object-Oriented Analysis," Information Systems Research, INFORMS, vol. 17(1), pages 38-60, March.
    4. Yair Wand & Ron Weber, 2002. "Research Commentary: Information Systems and Conceptual Modeling—A Research Agenda," Information Systems Research, INFORMS, vol. 13(4), pages 363-376, December.
    5. Jan Claes & Irene Vanderfeesten & Frederik Gailly & Paul Grefen & Geert Poels, 2015. "The Structured Process Modeling Theory (SPMT) a cognitive view on why and how modelers benefit from structuring the process of process modeling," Information Systems Frontiers, Springer, vol. 17(6), pages 1401-1425, December.

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