research-article

How visual cognition influences process model comprehension

Decision Support Systems, Volume 96, Issue C

Pages 1 - 16

https://doi.org/10.1016/j.dss.2017.01.005

Published: 01 April 2017 Publication History

Abstract

Process analysts and other professionals extensively use process models to analyze business processes and identify performance improvement opportunities. Therefore, it is important that such models can be easily and properly understood. Previous research has mainly focused on two types of factors that are important in this context: (i) properties of the model itself, and (ii) properties of the model reader. The work in this paper aims at determining how the performance of subjects varies across different types of comprehension tasks, which is a new angle. To reason about the complexity of comprehension tasks we take a theoretical perspective that is grounded in visual cognition. We test our hypotheses using a free-simulation experiment that incorporates eye-tracking technology. We find that model-related and person-related factors are fully mediated by variables of visual cognition. Moreover, in comparison, visual cognition variables provide a significantly higher explanatory power for the duration and efficiency of comprehension tasks. These insights shed a new perspective on what influences sense-making of process models, shifting the attention from model and reader characteristics to the complexity of the problem-solving task at hand. Our work opens the way to investigate and develop effective strategies to support readers of process models, for example through the context-sensitive use of visual cues. We use Visual Cognition research model to explain understanding of process modelsIt has better explanatory power than model based on Complexity and Reader ExpertiseVisual Cognition mediates Comprehension Performance (e.g. Correctness, Task time)We test hypotheses using an experiment that makes use of eye-tracking technology

References

[1]

M. Dumas, M. La Rosa, J. Mendling, H.A. Reijers, Fundamentals of Business Process Management, Springer, 2013.

Digital Library

[2]

H.A. Reijers, J. Mendling, A study into the factors that influence the understandability of business process models, Syst. Man Cybern. Part A Syst. Hum. IEEE Trans. 41 (3) (2011) 449-462.

Digital Library

[3]

J. Mendling, M. Strembeck, J. Recker, Factors of process model comprehension--findings from a series of experiments, Decis. Support. Syst. 53 (1) (2012) 195-206.

Digital Library

[4]

J.C. Recker, A. Dreiling, The effects of content presentation format and user characteristics on novice developers' understanding of process models, CAIS 28 (6) (2011) 65-84.

[5]

J. Recker, Continued use of process modeling grammars: the impact of individual difference factors, Eur. J. Inf. Syst. 19 (1) (2010) 76-92.

[6]

A. Burton-Jones, P.N. Meso, The effects of decomposition quality and multiple forms of information on novices' understanding of a domain froma conceptual model, JAIS 9 (12) (2008) 748.

[7]

K. Figl, R. Laue, Influence factors for local comprehensibility of processmodels, Int. J. Hum. Comput. Stud. 82 (2015) 96-110.

Digital Library

[8]

H.L. Fromkin, S. Streufert, Laboratory Experimentation, No. 343, Herman C. Krannert Graduate School of Industrial Administration, Purdue University, 1972.

[9]

D.L. Moody, Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions, DKE 55 (3) (2005) 243-276.

Digital Library

[10]

J. Recker, H.A. Reijers, S.G. van deWouw, Process model comprehension: the effects of cognitive abilities, learning style, and strategy, CAIS 34 (1) (2014) 9.

[11]

A. Gemino, Y. Wand, A framework for empirical evaluation of conceptual modeling techniques, Requir. Eng. 9 (4) (2004) 248-260.

Digital Library

[12]

J. Mendling, H.A. Reijers, J. Cardoso, What makes process models understandable? Business Process Management, Springer 2007, pp. 48-63.

Digital Library

[13]

J. Cardoso, Evaluating workflows and web process complexity, Workflow Handbook 2005 2005, pp. 284-290.

[14]

L. Sanchez Gonzalez, F. Garcia Rubio, F. Ruiz Gonzalez, M. Piattini Velthuis, Measurement in business processes: a systematic review, Bus. Process. Manag. J. 16 (1) (2010) 114-134.

[15]

A. Polyvyanyy, L. Garcá-Bañuelos, M. Dumas, Structuring acyclic process models, Inf. Syst. 37 (6) (2012) 518-538.

Digital Library

[16]

K. Figl, J. Mendling, M. Strembeck, The influence of notational deficiencies on process model comprehension, J. Assoc. Inf. Syst. 14 (6) (2013) 312.

[17]

J. Recker, M. Rosemann, P.F. Green, M. Indulska, Do ontological deficiencies in modeling grammars matter? MIS Q. 35 (1) (2011) 57-79.

Digital Library

[18]

M. ZurMuehlen, J. Recker, How much language is enough? Theoretical and practical use of the business process modeling notation, CAiSE, Springer 2008, pp. 465-479.

Digital Library

[19]

P. Bera, Does cognitive overload matter in understanding bpmn models? J. Comput. Inf. Syst. 52 (4) (2012) 59-69.

[20]

H.A. Reijers, T. Freytag, J. Mendling, A. Eckleder, Syntax highlighting in business process-models, Decis. Support. Syst. 51 (3) (2011) 339-349.

Digital Library

[21]

R. Petrusel, J.Mendling,H.A. Reijers, Task-specific visual cues for improving processmodel understanding, IST 79 (2016) 63-78.

Digital Library

[22]

J. Mendling, H.A. Reijers, J. Recker, Activity labeling in process modeling: empirical insights and recommendations, Inf. Syst. 35 (4) (2010) 467-482.

Digital Library

[23]

M.A. Just, P.A. Carpenter, Eye fixations and cognitive processes, Cogn. Psychol. 8 (4) (1976) 441-480.

[24]

J.R. Anderson, D. Bothell, S. Douglass, Eye movements do not reflect retrieval processes limits of the eye-mind hypothesis, Psychol. Sci. 15 (4) (2004) 225-231.

[25]

R. Petrusel, J. Mendling, Eye-tracking the factors of process model comprehension tasks, CAiSE, Springer 2013, pp. 224-239.

Digital Library

[26]

A. Duchowski, Eye Tracking Methodology: Theory and Practice, vol. 373, Springer, 2007.

Digital Library

[27]

K. Holmqvist, M. Nystrom, R. Andersson, R. Dewhurst, H. Jarodzka, J. Van deWeijer, Eye Tracking: A Comprehensive Guide toMethods and Measures, Oxford University Press, 2011.

[28]

R. Baeza-Yates, B. Ribeiro-Neto, et al., Modern Information Retrieval, vol. 463, ACM press, New York, 1999.

Digital Library

[29]

J. Sweller, Cognitive load during problem solving: effects on learning, Cogn. Sci. 12 (2) (1988) 257-285.

[30]

S.J. Luck, E.K. Vogel, The capacity of visual working memory for features and conjunctions, Nature 390 (6657) (1997) 279-281.

[31]

G.A. Alvarez, Representing multiple objects as an ensemble enhances visual cognition, Trends Cogn. Sci. 15 (3) (2011) 122-131.

[32]

H.Y. Eng, D. Chen, Y. Jiang, Visualworking memory for simple and complex visual stimuli, Psychon. Bull. Rev. 12 (6) (2005) 1127-1133.

[33]

M. Weidlich, J. Mendling, M. Weske, Efficient consistency measurement based on behavioral profiles of process models, IEEE Trans. Softw. Eng. 37 (3) (2011) 410-429.

Digital Library

[34]

C. Conati, C.Merten, Eye-tracking for usermodeling in exploratory learning environments: an empirical evaluation, Knowl.-Based Syst. 20 (6) (2007) 557-574.

Digital Library

[35]

A. Field, Discovering Statistics Using IBM SPSS Statistics, Sage, 2013.

Digital Library

[36]

D.W. Hosmer Jr., S. Lemeshow, Applied Logistic Regression, JohnWiley & Sons, 2004.

[37]

J.H. Steiger, Tests for comparing elements of a correlation matrix, Psychol. Bull. 87 (2) (1980) 245.

[38]

C.M. Judd, D.A. Kenny, Process analysis estimatingmediation in treatment evaluations, Eval. Rev. 5 (5) (1981) 602-619.

[39]

Z. Sharafi, Z. Soh, Y.-G. Gueheneuc, A systematic literature review on the usage of eye-tracking in software engineering, IST 67 (2015) 79-107.

Digital Library

[40]

J. Pinggera, M. Furtner,M.Martini, P. Sachse, K. Reiter, S. Zugal, B.Weber, Investigating the process of process modeling with eye movement analysis, Business Process Management Workshops, Springer 2013, pp. 438-450.

Cited By

Kaur KMishra AChopra P(2024)An amalgamation of cognitive aspects in software engineeringExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122968246:COnline publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122968
Winter MPryss R(2024)The effects of modular process models on gaze patterns - A follow-up investigation about modularization in process model literacyExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121176237:PAOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121176
Franceschetti MAbbad-Andaloussi ASchreiber CLópez HWeber B(2024)Exploring the Cognitive Effects of Ambiguity in Process ModelsBusiness Process Management10.1007/978-3-031-70396-6_28(493-510)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70396-6_28
Show More Cited By

Recommendations

Identifying Situated Cognition in Organizations

Using the established definition of situated cognition in organizations as "the interaction of cognitive schemas and organizational context" (Lant 2002), we examine empirical case studies from the last 15 years to illustrate what situated cognitions in ...
Cognition Beyond the Brain: Computation, Interactivity and Human Artifice
Interfaces of social psychology with situated and embodied cognition

The recent rise of interest in situated and embodied cognition has a strong interdisciplinary flavor, with contributions from robotics, cognitive anthropology, cognitive psychology, and developmental psychology, among other disciplines. However, social ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Decision Support Systems

Decision Support Systems Volume 96, Issue C

April 2017

130 pages

ISSN:0167-9236

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 April 2017

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 02 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kaur KMishra AChopra P(2024)An amalgamation of cognitive aspects in software engineeringExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122968246:COnline publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122968
Winter MPryss R(2024)The effects of modular process models on gaze patterns - A follow-up investigation about modularization in process model literacyExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121176237:PAOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121176
Franceschetti MAbbad-Andaloussi ASchreiber CLópez HWeber B(2024)Exploring the Cognitive Effects of Ambiguity in Process ModelsBusiness Process Management10.1007/978-3-031-70396-6_28(493-510)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70396-6_28
Winter MNeumann HPryss RProbst TReichert M(2023)Defining gaze patterns for process model literacy – Exploring visual routines in process models with diverse mappingsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119217213:PCOnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119217
Schreiber CAbbad-Andaloussi AWeber B(2023)On the Cognitive Effects of Abstraction and Fragmentation in Modularized Process ModelsBusiness Process Management10.1007/978-3-031-41620-0_21(359-376)Online publication date: 11-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-41620-0_21
Savary-Leblanc MPallec XKühn TSousa V(2022)Interactive highlighting for digital UML class diagramsProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings10.1145/3550356.3561557(247-256)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550356.3561557
Wang WChen TIndulska MSadiq SWeber B(2022)Business process and rule integration approaches—An empirical analysis of model understandingInformation Systems10.1016/j.is.2021.101901104:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.is.2021.101901
Tsagkani CTsalgatidou A(2022)Process model abstraction for rapid comprehension of complex business processesInformation Systems10.1016/j.is.2021.101818103:COnline publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.is.2021.101818
Fındık-Coşkunçay DÇakır M(2022)An investigation of the relationship between joint visual attention and product quality in collaborative business process modeling: a dual eye-tracking studySoftware and Systems Modeling (SoSyM)10.1007/s10270-022-00974-621:6(2429-2460)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s10270-022-00974-6
Jošt GHeriă?Ko MPolană?Iă? G(2019)Theoretical foundations and implementation of business process diagrams' complexity management technique based on highlightsSoftware and Systems Modeling (SoSyM)10.1007/s10270-017-0618-518:2(1079-1095)Online publication date: 17-May-2019
https://dl.acm.org/doi/10.1007/s10270-017-0618-5
Show More Cited By

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents