Kathrin Figl

Cognitive complexity in business process modeling

Although (business) process models are frequently used to promote human understanding of processes, practice shows that understanding complex models soon reach cognitive limits. The aim of this paper is to investigate the cognitive difficulty of understanding different relations between model elements. To allow for empirical assessment of this research question we systematically constructed model sets and comprehension questions. The results of an empirical study with 199 students tend to suggest that comprehension questions on order and concurrency are easier to answer than on repetition and exclusiveness. Additionally, results lend support to the hypothesis that interactivity of model elements influences cognitive difficulty. While our findings shed light on human comprehension of process models, they also contribute to the question on how to assure understandability of models in practice.

On the Cognitive Effectiveness of Routing Symbols in Process Modeling Languages

Process models provide visual support for analyzing and improving complex organizational processes. In this paper, we discuss differences of process modeling languages using cognitive effectiveness considerations, to make statements about the ease of use and quality of user experience. Aspects of cognitive effectiveness are of importance for learning a modeling language, creating models, and understanding models. We identify the criteria representational clarity, perceptual discriminability, perceptual immediacy, visual expressiveness, and graphic parsimony to compare and assess the cognitive effectiveness of different modeling languages. We apply these criteria in an analysis of the routing elements of UML Activity Diagrams, YAWL, BPMN, and EPCs, to uncover their relative strengths and weaknesses from a quality of user experience perspective. We draw conclusions that are relevant to the usability of these languages in business process modeling projects.

Cognitive effectiveness of visual instructional design languages

The introduction of learning technologies into education is making the design of courses and instructional materials an increasingly complex task. Instructional design languages are identified as conceptual tools for achieving more standardized and, at the same time, more creative design solutions, as well as enhancing communication and transparency in the design process. In this article we discuss differences in cognitive aspects of three visual instructional design languages (E^2ML, PoEML, coUML), based on user evaluation. Cognitive aspects are of relevance for learning a design language, creating models with it, and understanding models created using it. The findings should enable language constructors to improve the usability of visual instructional design languages in the future. The paper concludes with directions with regard to how future research on visual instructional design languages could strengthen their value and enhance their actual use by educators and designers by synthesizing existing efforts into a unified modeling approach for VIDLs.

Comprehension of Procedural Visual Business Process Models

Visual process models are meant to facilitate comprehension of business processes. However, in practice, process models can be difficult to understand. The main goal of this article is to clarify the sources of cognitive effort in comprehending process models. The article undertakes a comprehensive descriptive review of empirical and theoretical work in order to categorize and summarize systematically existing findings on the factors that influence comprehension of visual process models. Methodologically, the article builds on a review of forty empirical studies that measure objective comprehension of process models, seven studies that measure subjective comprehension and user preferences, and thirty-two articles that discuss the factors that influence the comprehension of process models. The article provides information systems researchers with an overview of the empirical state of the art of process model comprehension and provides recommendations for new research questions to be addressed and methods to be used in future experiments.

Online versus Face-to-Face Peer Team Reviews

Peer-reviewing is gaining importance as didactic technique in computer science courses. Through reviewing their peers, students develop evaluation skills, increase their reflection ability, and develop awareness of their own works quality. This paper presents an experimental study exploring communication and collaboration aspects of the peer-reviewing task. In particular, the study analyzes differences between the face-to-face and the online setting. Both settings were implemented and investigated with respect to communication and collaboration in and among teams as well as workload distribution. The results show that students highly appreciated many aspects of the online reviewing tool but found themselves constrained by the lack of discussion, which they experienced and valued in the face-to-face process. The paper discusses further results regarding team communication and collaboration and their implications on the specific didactical use of online and face-to-face peer-reviewing

Influence factors for local comprehensibility of process models

The main aim of this study is to investigate human understanding of process models and to develop an improved understanding of its relevant influence factors. Aided by assumptions from cognitive psychology, this article attempts to address specific deductive reasoning difficulties based on process models. The authors developed a research model to capture the influence of two effects on the cognitive difficulty of reasoning tasks: (i) the presence of different control-flow patterns (such as conditional or parallel execution) in a process model and (ii) the interactivity of model elements. Based on solutions to 61 different reasoning tasks by 155 modelers, the results from this study indicate that the presence of certain control-flow patterns influences the cognitive difficulty of reasoning tasks. In particular, sequence is relatively easy, while loops in a model proved difficult. Modelers with higher process modeling knowledge performed better and rated subjective difficulty of loops lower than modelers with lower process modeling knowledge. The findings additionally support the prediction that interactivity between model elements is positively related to the cognitive difficulty of reasoning. Our research contributes to both academic literature on the comprehension of process models and practitioner literature focusing on cognitive difficulties when using process models. First analysis of influence factors for local comprehensibility of process models.Control-flow patterns influence cognitive difficulty of reasoning tasks.Sequence is relatively easy, while loops in a model are especially difficult to understand.Modelers with higher process modeling knowledge performed better and rated subjective difficulty of loops lower than modelers with lower process modeling knowledge.Interactivity between model elements is positively related to cognitive difficulty.

Comprehending Feature Models Expressed in CVL

Feature modeling is a common way to present and manage variability of software and systems. As a prerequisite for effective variability management is comprehensible representation, the main aim of this paper is to investigate difficulties in understanding feature models. In particular, we focus on the comprehensibility of feature models as expressed in Common Variability Language (CVL), which was recommended for adoption as a standard by the Architectural Board of the Object Management Group. Using an experimental approach with participants familiar and unfamiliar with feature modeling, we analyzed comprehensibility in terms of comprehension score, time spent to complete tasks, and perceived difficulty of different feature modeling constructs. The results showed that familiarity with feature modeling did not influence the comprehension of mandatory, optional, and alternative features, although unfamiliar modelers perceived these elements more difficult than familiar modelers. OR relations were perceived as difficult regardless of the familiarity level, while constraints were significantly better understood by familiar modelers. The time spent to complete tasks was higher for familiar modelers.

Individual Creativity in Designing Business Processes

Designing business processes in a creative way is an important requirement for implementing process-aware information systems. In this article we investigate how process modeling competence and individual creativity style and capacity influence creativity in a business process redesign task. We explore these relationships with a laboratory experiment with 48 business students. Our preliminary results showed that process modeling competence is positively associated with the creative quality of a business process redesign, while individual creativity style and capacity measured by well-known creativity inventories seem to be less relevant. The findings underline the importance of training in process modeling to enable employees to realize their full creative potential when redesigning process models in process improvement projects.

Open Data Hopes and Fears: Determining the Barriers of Open Data

In recent years, Open Data has gained considerable attention: a steady growth in the number of openly published datasets – mainly by governments and public administrations - can be observed as the demand for Open Data rises. However, many potential providers are still hesitant to open their datasets and at the same time users often face difficulties when attempting to use this data in practice. This indicates that there are still various barriers present both regarding usage and publishing of Open Data, but studies that systematically collect and assess these barriers regarding their impact are rare. Based on this observation we survey prior literature on barriers, and have developed a questionnaire aimed at both assessing the users and publishers views on obstacles regarding Open Data adoption. Using a sample of over 100 participants from Austria who completed our online survey, we draw conclusions about the relative importance of the barriers reported in the literature. The empirical findings presented in this study shall serve as a solid foundation for future research on the mitigation of Open Data barriers.

Towards learner-centered learning goals based on the Person-Centered Approach

While learning goals need to be predefined at the curriculum and course level, it is the concrete course offering, the instructor or facilitator, the student colleagues and learning designs that are decisive in determining whether learning goals can truly be called ldquolearner-centered.rdquo In this paper we identify features and preconditions of learner-centered learning goals, consider their context and focus on describing course-level scenarios that allow facilitators to include students in co-determining and following learning goals. Results are illustrated by student reactions and brief summaries of results and references to more detailed studies. The theoretical inspiration and interpersonal value system for learner-centeredness is borrowed from the person-centered approach.