Assessing the Impact of Hierarchy on Model Understandability – A Cognitive Perspective

  • Stefan Zugal
  • Jakob Pinggera
  • Barbara Weber
  • Jan Mendling
  • Hajo A. Reijers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7167)

Abstract

Modularity is a widely advocated strategy for handling complexity in conceptual models. Nevertheless, a systematic literature review revealed that it is not yet entirely clear under which circumstances modularity is most beneficial. Quite the contrary, empirical findings are contradictory, some authors even show that modularity can lead to decreased model understandability. In this work, we draw on insights from cognitive psychology to develop a framework for assessing the impact of hierarchy on model understandability. In particular, we identify abstraction and the split-attention effect as two opposing forces that presumably mediate the influence of modularity. Based on our framework, we describe an approach to estimate the impact of modularization on understandability and discuss implications for experiments investigating the impact of modularization on conceptual models.

Keywords

Business Process Cognitive Load Systematic Literature Review Model Size Composite State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Zugal
    • 1
  • Jakob Pinggera
    • 1
  • Barbara Weber
    • 1
  • Jan Mendling
    • 2
  • Hajo A. Reijers
    • 3
  1. 1.University of InnsbruckAustria
  2. 2.Humboldt-Universität zu BerlinGermany
  3. 3.Eindhoven University of TechnologyThe Netherlands

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