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Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
Published on: January 23, 2017
When a model gives you mixed signals: cognitive effects and visual behavior
Amine Abbad-Andaloussi1, Marco Franceschetti1, Hugo A López2
1University of St.Gallen, St. Gallen, Switzerland.
Abstract:
Ambiguity in business process models can result in multiple interpretations by model readers. This leads to undesirable outcomes such as misunderstandings, unclear allocation of responsibilities, and unexpected behaviors. Despite these potential consequences, the impact of ambiguity on model readers has received limited attention so far. This article presents an eye-tracking study designed to investigate the effects of various types of ambiguity (i.e., layout, semantic, syntactic, and lexical) on readers' cognitive load, comprehension, and visual associations while interpreting process models. In addition, the study delves into the behaviors of model readers when resolving ambiguity in process models. These behaviors are investigated following a qualitative approach combining both eye-tracking and think-aloud data. The results demonstrate that ambiguities significantly influence cognitive load, comprehension, and visual associations, emphasizing the negative effects of ambiguity. Moreover, the qualitative insights suggest that participants exhibit specific behaviors when trying to resolve ambiguities. These findings underscore the need for advanced mechanisms to detect and mitigate ambiguity in process models.
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