Measuring the Cognitive Complexity in the Comprehension of Modular Process Models

Winter, Michael and Pryss, Rüdiger and Probst, Thomas and Baß, Julia and Reichert, Manfred (2021) Measuring the Cognitive Complexity in the Comprehension of Modular Process Models. IEEE Transactions on Cognitive and Developmental Systems . (Accepted for Publication)

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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 paper presents the results of two exploratory studies (i.e., a survey research study with N = 95 participants; a follow-up eye tracking study with N = 19 participants), in which three types of modularization (i.e., horizontal, vertical, orthogonal) were applied to process models expressed in terms of the Business Process Model and Notation (BPMN) 2.0. Further, 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. Further, 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 model 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 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 paper.

Item Type: Article
Subjects: DBIS Research > Publications
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Publications
Depositing User: Herr Michael Winter
Date Deposited: 18 May 2021 11:53
Last Modified: 18 May 2021 11:53

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