4,680 research outputs found

    Using Insights from Cognitive Neuroscience to Investigate the Effects of Event-Driven Process Chains on Process Model Comprehension

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    Business process models have been adopted by enterprises for more than a decade. Especially for domain experts, the comprehension of process models constitutes a challenging task that needs to be mastered when creating or reading these models. This paper presents the results we obtained from an eye tracking experiment on process model comprehension. In detail, individuals with either no or advanced expertise in process modeling were confronted with models expressed in terms of Event-driven Process Chains (EPCs), reflecting different levels of difficulty. The first results of this experiment confirm recent findings from one of our previous experiments on the reading and comprehension of process models. On one hand, independent from their level of exper-tise, all individuals face similar patterns, when being confronted with process models exceeding a certain level of difficulty. On the other, it appears that process models expressed in terms of EPCs are perceived differently compared to process models specified in the Business Process Model and Notation (BPMN). In the end, their generalization needs to be confirmed by additional empirical experiments. The presented expe-riment continues a series of experiments that aim to unravel the factors fostering the comprehension of business process models by using methods and theories stemming from the field of cognitive neuroscience and psychology

    The Repercussions of Business Process Modeling Notations on Mental Load and Mental Effort

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    Over the last decade, plenty business process modeling notations emerged for the documentation of business processes in enterprises. During the learning of a modeling notation, an individual is confronted with a cognitive load that has an impact on the comprehension of a notation with its underlying formalisms and concepts. To address the cognitive load, this paper presents the results from an exploratory study, in which a sample of 94 participants, divided into novices, intermediates, and experts, needed to assess process models expressed in terms of eight different process modeling notations, i.e., BPMN 2.0, Declarative Process Modeling, eGantt Charts, EPCs, Flow Charts, IDEF3, Petri Nets, and UML Activity Diagrams. The study focus was set on the subjective comprehensibility and accessibility of process models reflecting participant's cognitive load (i.e., mental load and mental effort). Based on the cognitive load, a factor reflecting the mental difficulty for comprehending process models in different modeling notations was derived. The results indicate that established modeling notations from industry (e.g., BPMN) should be the first choice for enterprises when striving for process management. Moreover, study insights may be used to determine which modeling notations should be taught for an introduction in process modeling or which notation is useful to teach and train process modelers or analysts. \keywords{Business Process Modeling Notations, Cognitive Load, Mental Load, Mental Effort, Human-centered Desig

    Cognitive Insights into Business Process Model Comprehension: Preliminary Results for Experienced and Inexperienced Individuals

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    Process modeling constitutes a fundamental task in the context of process-aware information systems. Besides process model creation, the reading and understanding of process models is of utmost importance. To better understand the latter, we have developed a conceptual framework focusing on the comprehension of business process models. By adopting concepts from cognitive neuroscience and psychology, the paper presents initial results from a series of eye tracking experiments on process model comprehension. The results indicate that experiences with process modeling have an influence on overall model comprehension. In turn, with increasing process model complexity, individuals with either no or advanced expertise in process modeling do not significantly differ with respect to process model comprehension. The results further indicate that both groups face similar challenges in reading and comprehending process models. The conceptual framework takes these results into account and provides the basis for the further experiments

    Event boundary perception among the visually impaired in audio described films

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    Audio description (AD) serves a critical role in making film narratives accessible to visually impaired audiences, aiming to enhance their viewing experience and comprehension. One method to assess the comprehension of film narratives, is through an event segmentation task, wherein participants delineate the narrative unfolding into distinct meaningful events. In the present study, both sighted and visually impaired participants engaged in such tasks. Sighted participants watched a Swedish film, while visually impaired participants experienced the same film with two AD versions—one explicitly expressing key event boundaries and another containing more implicitly conveyed ones. Our findings indicate that visually impaired participants perceived event boundaries similarly to sighted participants, suggesting that AD effectively conveys the event structure. However, in the AD version with implicit expressions, event boundaries were less likely to be recognized. These results shed light on event segmentation dynamics in films, emphasizing the importance of how event boundaries are presented in AD. This has significant implications for improving the cinematic experience for visually impaired viewers, emphasizing the need for clear, explicit information about event boundaries within AD

    Measuring the Cognitive Complexity in the Comprehension of Modular Process Models

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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

    How quickly do we learn conceptual models?

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    In organizations, conceptual models are used for understanding domain concepts. Learning the domain from models is crucial for the analysis and design of information systems that are intended to support the domain. Past research has proposed theories to structure conceptual models in order to improve learning. It has, however, never been investigated how quickly domain knowledge is acquired when using theory-guided conceptual models. Based on theoretical arguments, we hypothesize that theory-guided conceptual models expedite the initial stages of learning. Using the REA ontology pattern as an example of theoretical guidance, we show in a laboratory experiment how an eye-tracking procedure can be used to investigate the effect of using theory-guided models on the speed of learning. Whereas our experiment shows positive effects on both outcome and speed of learning in the initial stages of learning, the real contribution of our paper is methodological, i.e. an eye-tracking procedure to observe the process of learning from conceptual models

    Towards the Applicability of Measuring the Electrodermal Activity in the Context of Process Model Comprehension: Feasibility Study

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    Process model comprehension is essential in order to understand the Five Ws (i.e., who, what, where, when, and why) pertaining to the processes of organizations. However, research in this context showed that a proper comprehension of process models often poses a challenge in practice. For this reason, a vast body of research exists studying the factors having an influence on process model comprehension. In order to point research towards a neuro-centric perspective in this context, the paper at hand evaluates the appropriateness of measuring the electrodermal activity (EDA) during the comprehension of process models. Therefore, a preliminary test run and a feasibility study were conducted relying on an EDA and physical activity sensor to record the EDA during process model comprehension. The insights obtained from the feasibility study demonstrated that process model comprehension leads to an increased activity in the EDA. Furthermore, EDA-related results indicated significantly that participants were confronted with a higher cognitive load during the comprehension of complex process models. In addition, the experiences and limitations we have learned in measuring the EDA during the comprehension of process models are discussed in this paper. In conclusion, the feasibility study demonstrated that the measurement of the EDA could be an appropriate method to obtain new insights in process model comprehension
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