The Impact of Modularization on the Understandability of Declarative Process Models: A Research Model
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Accepted author manuscript, 424 KB, PDF document
Process models provide a blueprint for process execution and an indispensable tool for process management. Bearing in mind their trending use for requirement elicitation, communication and improvement of business processes, the need for understandable process models becomes a must. In this paper, we propose a research model to investigate the impact of modularization on the understandability of declarative process models. We design a controlled experiment supported by eye-tracking, electroencephalography (EEG) and galvanic skin response (GSR) to appraise the understandability of hierarchical process models through measures such as comprehension accuracy, response time, attention, cognitive load and cognitive integration.
|Title of host publication||Information Systems and Neuroscience - NeuroIS Retreat 2020|
|Editors||Fred D. Davis, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane B. Randolph, Thomas Fischer|
|Number of pages||12|
|Publication status||Published - 2020|
|Event||Virtual conference NeuroIS Retreat, 2020 - Vienna, Austria|
Duration: 2 Jun 2020 → 4 Jun 2020
|Conference||Virtual conference NeuroIS Retreat, 2020|
|Periode||02/06/2020 → 04/06/2020|
|Series||Lecture Notes in Information Systems and Organisation|
© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
- DCR graphs, Declarative process models, Modularization, Neurophysiological experiment, Understandability