Modularization has been extensively investigated for its role in enhancing the comprehension of process models by dividing them into smaller, self-contained and manageable modules. However, existing studies have reported inconclusive results, prompting further exploration into when modularization supports or impedes process comprehension. Among the key factors suggested to influence the effect of modularization is the type of the task at hand. Indeed, the fragmentation of information across several modules caused by modularization can challenge readers' comprehension of process models, especially if the task is not confined to a single module. While the effect of fragmentation has been explored for flow-based tasks, requiring understanding procedural aspects of process models, our work extends to circumstantial tasks, which instead demand comprehending model rules and constraints that rely on the broader context associated with specific process parts. Using eye-tracking, we investigate how the fragmentation of information caused by modularization impacts cognitive integration (i.e., the collection and synthesis of dispersed information) and its subsequent effect on cognitive load and model comprehension. Our findings demonstrate that fragmentation significantly affects cognitive integration in flow-based tasks only. Moreover, our results show that cognitive integration is linked to both cognitive load and readers' comprehension of process models. The outcome of this work provides a detailed model, explaining the task-specific effects of fragmentation. Practically, our findings highlight the need for modeling tools that dynamically adjust their user interface} to reduce cognitive integration demands, thereby enhancing model comprehension.
