Measuring the Cognitive Complexity in the Comprehension of Modular Process Models

Michael Winter,Manfred Reichert,Thomas Probst,Julia Bas,Rudiger Pryss

doi:10.1109/tcds.2020.3032730

Abstract

Modularization in process models is a method to cope with the inherent complexity in such models (e.g., model size reduction). Modularization is capable to increase the quality, the ease of reuse, and the scalability of process models. Prior conducted research studied the effects of modular process models to enhance their comprehension. However, the effects of modularization on cognitive factors during process model comprehension are less understood so far. Therefore, this article presents the results of two exploratory studies (i.e., a survey research study with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N = 95$ </tex-math></inline-formula> participants; a follow-up eye tracking study with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N = 19$ </tex-math></inline-formula> participants), in which three types of modularization (i.e., horizontal, vertical, and orthogonal) were applied to process models expressed in terms of the business process model and notation (BPMN) 2.0. Furthermore, the effects of modularization on the cognitive load, the level of acceptability, and the performance in process model comprehension were investigated. In general, the results revealed that participants were confronted with challenges during the comprehension of modularized process models. Furthermore, performance in the comprehension of modularized process models showed only a few significant differences, however, the results obtained regarding the cognitive load revealed that the complexity and concept of modularization in process models were misjudged initially. The insights unraveled that the attitude towards the application and the behavioral intention to apply modularization in process models is still not clear. In this context, horizontal modularization appeared to be the best comprehensible modularization approach leading to a more fine-grained comprehension of the respective process models. The findings indicate that alterations in modular process models (e.g., change in the representation) are important to foster and enable their comprehension. Finally, based on our results, implications for research and practice as well as directions for future work are discussed in this article.

Highlights

IntroductionThe processes, procedures, and operations of organizations from different domains (e.g., industry [1], healthcare [2]) are usually documented in textual or graphical artifacts (i.e., process models)
The processes, procedures, and operations of organizations from different domains are usually documented in textual or graphical artifacts
Concerning perceived usefulness for understandability (PUU) and perceived ease of understandability (PEU), it appears that the participants were indecisive regarding the benefits of modularization in process models

Summary

Introduction

The processes, procedures, and operations of organizations from different domains (e.g., industry [1], healthcare [2]) are usually documented in textual or graphical artifacts (i.e., process models). Technology artifacts (e.g., software code) are considered in detail and their effects on aspects of human cognition (e.g., reading and comprehension) are evaluated in order to reveal the inherent complexity of such artifacts as well as how to positively reduce this complexity (i.e., cognitive complexity [15]) For this reason, in the context of process model comprehension, more emphasis is put on subjective cognitive processes in respective research. Thereby, the approach was pursued in previous research to compare the effects between modularized and nonmodularized process models [28] As another contribution in this context, the work at hand presents two exploratory studies that investigated the effects of three different modularization types (i.e., horizontal, vertical, orthogonal) on the comprehension of process models expressed in terms of the BPMN 2.0 from a cognitive point of view. The following four research questions (RQ) were addressed in this work: RQ 1: Does the use of different modularization types in process models have an effect on the cognitive load during the comprehension of BPMN 2.0 process models?

Methods

Results

Conclusion