Towards a Conceptual Framework Fostering Process Comprehension in Healthcare

Despite the widespread use of process models in healthcare organizations, there are many unresolved issues regarding the reading and comprehension of these models by domain experts. This is aggravated by the fact that there exists a plethora of process modeling languages for the graphical do-cumentation of processes, which are often not used consistently for various reasons. Hence, the identification of those factors fostering the comprehension of process models becomes crucial. We have developed a conceptual framework incorporating measurements and theories from cognitive neuroscience and psychology to unravel factors fostering the comprehension of process models within organizations. We believe that a better comprehension of process models will enhance the support of healthcare processes significantly

Utilizing the Capabilities Offered by Eye-Tracking to Foster Novices' Comprehension of Business Porcess Models

Business process models constitute fundamental artifacts for enterprise architectures as well as for the engineering of processes and information systems. However, less experienced stakeholders (i.e., novices) face a wide range of issues when trying to read and comprehend these models. In particular, process model comprehension not only requires knowledge on process modeling notations, but also skills to visually and correctly interpret the models. In this context, many unresolved issues concerning the factors hindering process model comprehension exist and, hence, the identification of these factors becomes crucial. Using eye-tracking as an instrument, this paper presents the results obtained of a study, in which we analyzed eye-movements of novices and experts, while comprehending process models expressed in terms of the Business Process Model and Notation (BPMN) 2.0. Further, recorded eye-movements are visualized as scan paths to analyze the applied comprehension strategies. We learned that experts comprehend process models more effectively than novices. In addition, we observed particular patterns for eye-movements (e.g., back-and-forth saccade jumps) as well as different strategies of novices and experts in comprehending process models

An evaluation on the comprehensibility of UML activity and state chart diagrams with regard to manual test generation

The activity and state chart diagrams are the most frequently used UML diagrams for testing a system based on its specification. One of the key important qualities of the UML diagrams is their comprehensibility. The content analysis of previous studies highlighted the lack of experts’ evaluation of the comprehensibility of activity and state chart diagrams with regard to test case generation. Thus, the main objective of this study is to evaluate the comprehensibility of the UML activity and state chart diagrams for test case generation. First, a content analysis was performed to identify the comprehensibility criteria. The criteria are perceived difficulty and subjective confidence. Next, a set of evaluation questions was designed based on the content analysis. Then, test cases were generated from activity and state chart diagrams manually of an adapted case study. An interview was conducted with five experts to validate the evaluation questions. The experts evaluated the comprehensibility of the activity and state chart diagrams by using the evaluation questions. The result of the study provided specific details of the different characteristics of activity and state chart diagrams. Further, it suggested that the activity diagram is more comprehensible than the state chart diagram in the aspect of test case generation. The finding of this study could assist software testers in choosing the appropriate UML diagrams for software testing

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

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

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

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

A Qualitative Comparison of Approaches Supporting Business Process Variability

The increasing adoption of process-aware information systems, together with the reuse of process knowledge, has led to the emergence of process model repositories with large process families, i.e., collections of related process model variants. For managing such related model collections two types of approaches exist. While behavioral approaches take supersets of variants and derive a process variant by hiding and blocking process elements, structural approaches take a base process model as input and derive a process variant by applying a set of change operations to it. However, at the current stage no framework for assessing these approaches exists and it is not yet clear which approach should be better used and under which circumstances. Therefore, to give first insights about this issue, this work compares both approaches in terms of understandability of the produced process model artifacts, which is fundamental for the management of process families and the reuse of their contained process fragments. In addition, the comparison can serve as theoretical basis for conducting experiments as well as for fostering the development of tools managing business process variability

Understanding understandability of conceptual models - what are we actually talking about? - Supplement

Investigating and improving the quality of conceptual models has gained tremendous importance in recent years. In general, model understandability is regarded one of the most important model quality goals and criteria. A considerable amount of empirical studies, especially experiments, have been conducted in order to investigate factors in-fluencing the understandability of conceptual models. However, a thorough review and reconstruction of 42 experiments on conceptual model understandability shows that there is a variety of different understandings and conceptualizations of the term model understandability. As a consequence, this term remains ambiguous, research results on model understandability are hardly comparable and partly imprecise, which shows the necessity of clarification what the conceptual modeling community is actually talking about when the term model understandability is used. This contribution represents a supplement to the article „ Understanding understandability of conceptual models – What are we actually talking about?” published in the Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012) which aimed at overcoming the above mentioned shortcoming by investigating and further clarifying the concept of model understandability. This supplement contains a complete overview of Table 1 (p. 69 in the original contribution) which could only be partly presented in the conference proceedings due to space limitations. Furthermore, an erratum concerning the overview in Table 2 (p. 71 in the original contribution) is presented

How Social Distance of Process Designers Affects the Process of Process Modeling: Insights From a Controlled Experiment

The increasing adoption of process-aware information systems (PAISs) by enterprises has resulted in large process model collections. Usually, process models are created either by in-house domain experts or external consultants. Thereby, high model quality is crucial, i.e., process models should be syntactically correct and sound, and also reflect the real business processes properly. While numerous guidelines exist for creating correct and sound process models, there is only little work dealing with cognitive aspects affecting process modeling. This paper addresses this gap and presents a controlled experiment using construal level theory. We investigate the influence the social distance of a process designer to the modeled domain has on the creation of process models. In particular, we are able to show significant differences between high and low social distance in respect to model quality and granularity. The results may help enterprises to compose adequate teams for creating or optimizing business process models

Considering Social Distance as an Influence Factor in the Process of Process Modeling

Enterprise repositories comprise numerous business process models either created by in-house domain experts or external business analysts. To enable a widespread use of these process models, high model quality (e.g., soundness) as well as a sufficient level of granularity are crucial. Moreover, they shall reflect the actual business processes properly. Existing modeling guidelines target at creating correct and sound process models, whereas there is only little work dealing with cognitive issues influencing model creation by process designers. This paper addresses this gap and presents a controlled experiment investigating the construal level theory in the context of process modeling. In particular, we investigate the influence the social distance of a process designer to the modeled domain has on the creation of process models. For this purpose, we adopt and apply a gamification approach, which enables us to show significant differences between low and high social distance with respect to the quality, granularity, and structure of the created process models. The results obtained give insights into how enterprises shall compose teams for creating and evolving process models