The origin and evolution of syntax errors in simple sequence flow models in BPMN

How do syntax errors emerge? What is the earliest moment that potential syntax errors can be detected? Which evolution do syntax errors go through during modeling? A provisional answer to these questions is formulated in this paper based on an investigation of a dataset containing the operational details of 126 modeling sessions. First, a list is composed of the different potential syntax errors. Second, a classification framework is built to categorize the errors according to their certainty and severity during modeling (i.e., in partial or complete models). Third, the origin and evolution of all syntax errors in the dataset are identified. This data is then used to collect a number of observations, which form a basis for future research

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling

Toward a Taxonomy of Modeling Difficulties: A Multi-Modal Study on Individual Modeling Processes

Conceptual modeling is an essential activity during information systems development and, accordingly, a learning task faced by students of Information Systems. Presently, surprisingly little is known about how learning processes of conceptual modeling proceed, and about modeling difficulties learners experience. In this study, we integrate complementary modes of observation of learners\u27 modeling processes to identify modeling difficulties these learners face while performing a data modeling task using a modeling tool. We use the concept of cognitive breakdowns to analyze verbal protocols, recordings of learner-tool interactions and video recordings of learners\u27 modeling processes and survey learners about modeling difficulties. Our study identifies five types of modeling difficulties relating to different aspects of constructing conceptual data models, i.e., entity types, relationship types, attributes, and cardinalities. The identified types of modeling difficulties motivate a taxonomic theory of modeling difficulties intended to inform design science research on tool support for learners of conceptual modeling

Cognitive Mechanisms of Conceptual Modelling How Do People Do It?

Abstract. Conceptual modelling involves many higher order cognitive processes, such as relational reasoning and abstraction, which are based on integration and maintenance of information. Evidence from cognitive psychology suggests that these processes are subject to individual differences which cannot be explained by training and experience alone. In this review, we study how the cognitive processes that enable modelling interact to produce modelling behaviour, and where in this process we can find individual differences that may explain some of the variation in performance seen in actual modelling settings. We discuss interaction between working memory, executive control and attention as they facilitate relational reasoning and abstraction, which we consider to be key cognitive processes in modelling. Eventually, a thorough understanding of modelling cognition can help us to provide better cognitive support for modellers

Cognitive mechanisms of conceptual modelling: How do people do it?

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