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Software and Systems Modeling
Published in: Software and Systems Modeling 4/2022

09-01-2022 | Regular Paper

Are models better read on paper or on screen? A comparative study

Author: Mohamed El-Attar

Published in: Software and Systems Modeling | Issue 4/2022

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Abstract

Is it really better to print everything, including software models, or is it better to view them on screen? With the ever increasing complexity of software systems, software modeling is integral to software development. Software models facilitate and automate many activities during development, such as code and test case generation. However, a core goal of software modeling is to communicate and collaborate. Software models are presented to team members on many mediums and two of the most common mediums are paper and computer screens. Reading from paper or screen is ostensibly considered to have the same effect on model comprehension. However, the literature on text reading has indicated that the reading experiences can be very different which in turn effects various metrics related to reader performance. This paper reports on an experiment that was conducted to investigate the effect of reading software models on paper in comparison with reading them on a computer screen with respect to cognitive effectiveness. Cognitive effectiveness here refers to the ease by which a model reader can read a model. The experiment used a total of 74 software engineering students as subjects. The experiment results provide strong evidence that displaying diagrams on a screen allows subjects to read them quicker. There is also evidence that indicates that on screen viewing induces fewer reading errors.
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Appendix
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Literature
1.
Hitchman, S.: The details of conceptual modelling notations are important-a comparison of relationship normative language. Commun. Assoc. Inf. Syst. 9(1), 10 (2002)
2.
Irani, P., Ware, C.: Diagramming information structures using 3D perceptual primitives. ACM Trans. Comput. Hum. Interact. (TOCHI) 10(1), 1–19 (2003)CrossRef
3.
Braude, E.J.: Software Design: From Programming to Architecture. Wiley, Hoboken (2004)
4.
Moody, D.L.: The ‘physics’ of notations: toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Softw. Eng. 35(6), 756–779 (2009)CrossRef
5.
Green, T.R.: Cognitive dimensions of notations. People and computers V, pp 443–460 (1989)
6.
Green, T.R.G., Petre, M.: Usability analysis of visual programming environments: a ‘cognitive dimensions’ framework. J. Vis. Lang. Comput. 7(2), 131–174 (1996)CrossRef
7.
Blackwell, A., Green, T.: Notational systems–the cognitive dimensions of notations framework. In: HCI Models, Theories, and Frameworks: Toward an Interdisciplinary Science. Morgan Kaufmann (2003)
8.
Badreddin, O., Khandoker, R., Forward, A., Masmali, O., Lethbridge, T.C.: A decade of software design and modeling: a survey to uncover trends of the practice. In: Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, pp. 245–255 (2018)
9.
Wright, P., Lickorish, A.: Proof-reading texts on screen and paper. Behav. Inf. Technol. 2(3), 227–235 (1983)CrossRef
10.
Mangen, A., Walgermo, B.R., Brønnick, K.: Reading linear texts on paper versus computer screen: effects on reading comprehension. Int. J. Educ. Res. 58, 61–68 (2013)CrossRef
11.
Rasmusson, M.: Reading paper-reading screen-a comparison of reading literacy in two different modes. Nord. Stud. Educ. 35(01), 3–19 (2015)CrossRef
12.
Ackerman, R., Lauterman, T.: Taking reading comprehension exams on screen or on paper? A metacognitive analysis of learning texts under time pressure. Comput. Hum. Behav. 28(5), 1816–1828 (2012)CrossRef
13.
Noyes, J., Garland, K., Robbins, L.: Paper-based versus computer-based assessment: is workload another test mode effect? Br. J. Educ. Technol. 35(1), 111–113 (2004)CrossRef
14.
Dündar, H., Akçayır, M.: Tablet vs. paper: the effect on learners’ reading performance. Int. Electron. J. Elem. Educ. 4(3), 441–450 (2012)
15.
Margolin, S.J., Driscoll, C., Toland, M.J., Kegler, J.L.: E-readers, computer screens, or paper: does reading comprehension change across media platforms? Appl. Cogn. Psychol. 27(4), 512–519 (2013)CrossRef
16.
Spencer, C.: Research on learners’ preferences for reading from a printed text or from a computer screen. J. Distance Educ. 21(1), 33–50 (2006)
17.
Köpper, M., Mayr, S., Buchner, A.: Reading from computer screen versus reading from paper: does it still make a difference? Ergonomics 59(5), 615–632 (2016)CrossRef
18.
Blehm, C., Vishnu, S., Khattak, A., Mitra, S., Yee, R.W.: Computer vision syndrome: a review. Surv. Ophthalmol. 50(3), 253–262 (2005)CrossRef
19.
Kong, Y., Seo, Y.S., Zhai, L.: Comparison of reading performance on screen and on paper: a meta-analysis. Comput. Educ. 123, 138–149 (2018)CrossRef
20.
Mayer, R.E., Moreno, R.: Nine ways to reduce cognitive load in multimedia learning. Educ. Psychol. 38(1), 43–52 (2003)CrossRef
21.
Bertin, J.: Semiology of Graphics: Diagrams, Networks, Maps. University of Wisconsin Press, Madison (1983)
22.
Kresser, C.: How artificial light is wrecking your sleep, and what to do about it. February, 22, 2013 (2013)
23.
Fucci, D., Scanniello, G., Romano, S., Juristo, N.: Need for sleep: the impact of a night of sleep deprivation on novice developers’ performance. IEEE Trans. Softw. Eng. 46(1), 1–19 (2018)CrossRef
24.
Kretzschmar, F., Pleimling, D., Hosemann, J., Füssel, S., Bornkessel-Schlesewsky, I., Schlesewsky, M.: Subjective impressions do not mirror online reading effort: concurrent EEG-eyetracking evidence from the reading of books and digital media. PLoS ONE 8(2), 6178 (2013)CrossRef
25.
Lauterman, T., Ackerman, R.: Overcoming screen inferiority in learning and calibration. Comput. Hum. Behav. 35, 455–463 (2014)CrossRef
26.
27.
28.
Sternberg, R.J.: Introduction to optimizing learning in college: tips from cognitive psychology. Perspect Psychol Sci 11(651), 10–1177 (2016)
29.
30.
Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) feasibility study. DTIC Document (1990)
31.
32.
33.
34.
Purchase, H.C., et al.: Comprehension of diagram syntax: an empirical study of entity relationship notations. Int. J. Hum Comput. Stud. 61(2), 187–203 (2004)CrossRef
35.
Gopalakrishnan, S., et al.: Adapting UML activity diagrams for mobile work process modelling: experimental comparison of two notation alternatives. In: Third IFIP WG 8.1 Working Conference, PoEM 2010, Delft, The Netherlands, pp. 145–161 (2010)
36.
Reijers, H.A., Mendling, J.: A study into the factors that influence the understandability of business process models. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 41(3), 449–462 (2011)CrossRef
37.
38.
Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3(2), 77–101 (2006)CrossRef
39.
Shapiro, S.S., Wilk, M.B.: An analysis of variance test for the exponential distribution. Techno Metrics 14, 355–370 (1972)MATHCrossRef
40.
Spearman, C.: The proof and measurement of association between two things (1961)
41.
Cliff, N.: Dominance statistics: ordinal analyses to answer ordinal questions. Psychol. Bull. 114(3), 494–509 (1993)CrossRef
42.
Cliff, N.: Answering ordinal questions with ordinal data using ordinal statistics. Multivar. Behav. Res. 31(3), 331–350 (1996)CrossRef
43.
Cliff, N.: Ordinal Methods for Behavioral Data Analysis. Lawrence Erlbaum Associates, Mahwah (1996)
44.
Romano, J., Kromrey, J.D., Coraggio, J., Skowronek, J.: Appropriate statistics for ordinal level data: should we really be using t-test and Cohen’s d for evaluating group differences on the NSSE and other surveys. In annual meeting of the Florida Association of Institutional Research, vol. 177 (2006)
45.
Wohlin, C., Runeson, P., Host, M., Ohlsson, M.C., Regnell, B., Wesslen, A.: Experimentation in Software Engineering: An Introduction. Kluwer (2000)MATHCrossRef
46.
El-Attar, M.: A comparative study of students and professionals in syntactical model comprehension experiments. Softw. Syst. Model. 18(6), 3283–3329 (2019)CrossRef
47.
Mackinlay, J.: Automating the design of graphical presentations of relational information. ACM Trans. Graph. 5(2), 110–141 (1986)CrossRef
48.
Winn, W.D.: An account of how readers search for information in diagrams. Contemp. Educ. Psychol. 18, 162–185 (1993)CrossRef
49.
Lohse, G.L.: A cognitive model for understanding graphical perception. Hum.-Comput. Interact. 8(4), 353–388 (1993)CrossRef
50.
Treisman, A.: Perceptual grouping and attention in visual search for features and for objects. J. Exp. Psychol. Hum. Percept. Perform. 8, 194–214 (1982)CrossRef
51.
Bramão, I., Reis, A., Petersson, K.M., Faísca, L.: The role of color information on object recognition: a review and meta-analysis. Acta Physiol. (Oxf) 138(1), 244–253 (2011)
52.
Wurm, L.H., Legge, G.E., Isenberg, L.M., Luebker, A.: Color improves object recognition in normal and low vision. J. Exp. Psychol. Hum. Percept. Perform. 19, 899–911 (1993)CrossRef
Metadata
Title
Are models better read on paper or on screen? A comparative study
Author
Mohamed El-Attar
Publication date
09-01-2022
Publisher
Springer Berlin Heidelberg
Published in
Software and Systems Modeling / Issue 4/2022
Print ISSN: 1619-1366
Electronic ISSN: 1619-1374
DOI
https://doi.org/10.1007/s10270-021-00966-y

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