Exploring cognitive style and task-specific preferences for process representations

Requirements Engineering

Volumn 21, Issue 1, 2016, Pages 63-85

  Figl, Kathrin ^a   Recker, Jan ^b  

^a VIENNA UNIVERSITY OF ECONOMICS AND BUSINESS   (Austria)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Business process modeling; Cognitive style; Conceptual modeling; Model evaluation; Representation forms; User preferences

Indexed keywords

SYSTEMS ENGINEERING;

BUSINESS PROCESS MODEL; COGNITIVE STYLES; CONCEPTUAL MODEL; MODEL EVALUATION; USER PREFERENCES;

PROCESS ENGINEERING;

EID: 85027933714     PISSN: 09473602     EISSN: 1432010X     Source Type: Journal    
DOI: 10.1007/s00766-014-0210-2     Document Type: Article

References (90)

1. Davies I, Green P, Rosemann M, Indulska M, Gallo S (2006) How do practitioners use conceptual modeling in practice? Data Knowl Eng 58(3):358–380
2. Recker J, Rosemann M, Indulska M, Green P (2009) Business process modeling: a comparative analysis. J Assoc Inf Syst 10(4):333–363
3. Fettke P (2009) How conceptual modeling is used. Commun Assoc Inf Syst 25(43):571–592
4. Kock N, Verville J, Danesh-Pajou A, DeLuca D (2009) Communication flow orientation in business process modeling and its effect on redesign success: results from a field study. Decis Support Syst 46(2):562–575
5. Indulska M, Green P, Recker J, Rosemann M (2009) Business process modeling: perceived benefits. In: Castano S, Dayal U, Laender AHF (eds) Conceptual modeling–ER 2009. Lecture notes in computer science. Springer, Gramado, pp 458–471
6. Wolter C, Meinel C (2010) An approach to capture authorisation requirements in business processes. Requirements Eng 15(4):359–373
7. Phalp KT, Vincent J, Cox K (2007) Improving the quality of use case descriptions: empirical assessment of writing guidelines. Softw Qual J 15(4):383–399
8. Lee J, Wyner GM, Pentland BT (2008) Process grammar as a tool for business process design. MIS Q 32(4):757–778
9. Moody DL (2009) The “Physics” of notations: toward a scientific basis for constructing visual notations in software engineering. IEEE Trans Softw Eng 35(6):756–779
10. Recker J, Safrudin N, Rosemann M (2012) How novices design business processes. Inf Syst 37(6):557–573
11. Boekelder A, Steehouder M (1998) Selecting and switching: some advantages of diagrams over tables and lists for presenting instructions. IEEE Trans Prof Commun 41(4):229–241
12. Coll RA, Coll JH, Thakur G (1994) Graphs and tables: a four-factor experiment. Commun ACM 37(4):76–86
13. Riding R, Cheema I (1991) Cognitive styles—an overview and integration. Educ Psychol: Int J Exp Educ Psychol 11(3):193–215
14. Thomas PR, McKay JB (2010) Cognitive styles and instructional design in university learning. Learn Individ Differ 20(3):197–202
15. Recker J (2010) Opportunities and constraints: the current struggle with BPMN. Bus Process Manag J 16(1):181–201
16. Dehnert J, van der Aalst WMP (2004) Bridging the gap between business models and workflow specifications. Int J Coop Inf Syst 13(3):289–332
17. Bandara W, Gable GG, Rosemann M (2005) Factors and measures of business process modelling: model building through a multiple case study. Eur J Inf Syst 14(4):347–360
18. Reijers HA, Mendling J (2011) A study into the factors that influence the understandability of business process models. IEEE Trans Syst Man Cybern A 41(3):449–462
19. Simon HA (1996) The sciences of the artificial, 3rd edn. MIT Press, Cambridge
20. Kalpic B, Bernus P (2006) Business process modeling through the knowledge management perspective. J Knowl Manag 10(3):40–56
21. Kim H-W, Kim Y-G (1997) Dynamic process modeling for BPR: a computerized simulation approach. Inf Manag 32(1):1–13
22. Ouyang C, van der Aalst WMP, Dumas M, ter Hofstede AHM, Mendling J (2009) From business process models to process-oriented software systems. ACM Trans Softw Eng Methodol 19(1):2–37
23. Dumas M, La Rosa M, Mendling J, Reijers HA (2013) Fundamentals of business process management. Springer, Berlin
24. Burton-Jones A, Meso P (2008) The effects of decomposition quality and multiple forms of information on novices’ understanding of a domain from a conceptual model. J Assoc Inf Syst 9(12):784–802
25. Mendling J, Strembeck M, Recker J (2012) Factors of process model comprehension: findings from a series of experiments. Decis Support Syst 53(1):195–206
26. Campbell DJ (1988) Task complexity: a review and analysis. Acad Manag Rev 13(1):40–52
27. Akin Ö, Akin C (1998) On the process of creativity in puzzles, inventions, and designs. Autom Constr 7(2–3):123–138
28. Kettinger WJ, Teng JTC, Guha S (1997) Business process change: a study of methodologies, techniques, and tools. MIS Q 21(1):55–80
29. Sarkar P, Chakrabarti A (2008) The effect of representation of triggers on design outcomes. Artif Intell Eng Des Anal Manuf 22(2):101–116
30. Gorla N, Pu H-C, Rom WO (1995) Evaluation of process tools in systems analysis. Inf Softw Technol 37(2):119–126
31. Friedrich F, Mendling J, Puhlmann F (2011) Process model generation from natural language text. In: Mouratidis H, Rolland C (eds) Advanced information systems engineering–CAiSe 2011. Lecture notes in computer science, vol 6741. Springer, London, pp 482–496
32. Blumberg R, Atre S (2003) The problem with unstructured data. DM Rev 13:42–49
33. Cockburn A (2000) Writing effective use cases. Addison-Wesley Longman Publishing Co., Inc
34. Vessey I, Weber R (1986) Structured tools and conditional logic: an empirical investigation. Commun ACM 29(1):48–57
35. Moody DL (2009) The “Physics” of notations: towards a scientific basis for constructing visual notations in software engineering. IEEE Trans Software Eng 35(5):756–779
36. Curtis B, Sheppard SB, Kruesi-Bailey E, Bailey J, Boehm-Davis DA (1989) Experimental evaluation of software documentation formats. J Syst Softw 9(2):167–207
37. Larkin JH, Simon HA (1987) Why a diagram is (sometimes) worth ten thousand words. Cogn Sci 11(1):65–100
38. Ottensooser A, Fekete A, Reijers HA, Mendling J, Menictas C (2012) Making sense of business process descriptions: an experimental comparison of graphical and textual notations. J Syst Softw 85(3):596–606
39. Masri K, Parker DC, Gemino A (2008) Using iconic graphics in entity-relationship diagrams: the impact on understanding. J Database Manag 19(3):22–41
40. Mendling J, Recker J, Reijers HA (2010) On the usage of labels and icons in business process modeling. Int J Inf Syst Mdel Des 1(2):40–58
41. Malaga RA (2000) The effect of stimulus modes and associative distance in individual creativity support systems. Decis Support Syst 29(2):125–141
42. Zajonc RB, Hazel M (1982) Affective and cognitive factors in preferences. J Consum Res 9(2):123–131
43. Blazhenkova O, Kozhevnikov M (2009) The new object-spatial-verbal cognitive style model: theory and measurement. Appl Cogn Psychol 23(5):638–663
44. Vessey I, Galletta DF (1991) Cognitive fit: an empirical study of information acquisition. Inf Syst Res 2(1):63–84
45. Vessey I (1991) Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decis Sci 22(2):219–240
46. Blazhenkova O, Kozhevnikov M (2008) The new object-spatial-verbal cognitive style model: theory and measurement. Appl Cogn Psychol 23(5):638–663
47. Stebbins RA (2001) Exploratory research in the social sciences. Qualitative research methods, vol 48. Sage, Thousand Oaks
48. Kumar S, Karoli V (2011) Handbook of business research methods. Thakur Publishers
49. Recker J, Reijers HA, van de Wouw SG (2014) Process model comprehension: the effects of cognitive abilities, learning style and strategy. Commun Assoc Inf Syst 34(9):199–222
50. Fromkin HL, Streufert S (1976) Laboratory experimentation. Rand McNally College Publishing Company, Chicago
51. Recker J, Mendling J, Hahn C (2013) How collaborative technology supports cognitive processes in collaborative process modeling: a capabilities-gains-outcome model. Inf Syst 38(8):1031–1045
52. Lichtenstein S, Slovic P (eds) (2006) The construction of preference. Cambridge University Press, New York
53. Recker J (2010) Continued use of process modeling grammars: the impact of individual difference factors. Eur J Inf Syst 19(1):76–92
54. Brehm JW (1956) Post-decision changes in the desirability of alternatives. J Abnorm Soc Psychol 52(3):384–389
55. Ben-Simon A, Budescu DV, Nevo B (1997) A comparative study of measures of partial knowledge in multiple-choice tests. Appl Psychol Meas 21(1):65–88
56. Blajenkova O, Kozhevnikov M, Motes MA (2006) Object-spatial imagery: a new self-report imagery questionnaire. Appl Cogn Psychol 20(2):239–263
57. Kozhevnikov M, Blazhenkova O, Becker M (2010) Trade-off in object versus spatial visualization abilities: restriction in the development of visual-processing resources. Psychon Bull Rev 17(1):29–35
58. Kozhevnikov M, Kozhevnikov M, Yu CJ, Blazhenkova O (2013) Creativity, visualization abilities, and visual cognitive style. Br J Educ Psychol 83(2):196–209
59. Campos A (2014) Gender differences in imagery. Personal Individ Differ 59:107–111
60. Occelli V, Lin JB, Lacey S, Sathian K (2014) Loss of form vision impairs spatial imagery. Front Hum Neurosci 8, Art No 159. doi:10.3389/fnhum.2014.00159
61. Kraemer DJ, Hamilton RH, Messing SB, DeSantis JH, Thompson-Schill SL (2014) Cognitive style, cortical stimulation, and the conversion hypothesis. Front Hum Neurosci 8, Art No 15. doi:10.3389/fnhum.2014.00015
62. Aggarwal I, Woolley AW (2013) Do you see what I see? The effect of members’ cognitive styles on team processes and errors in task execution. Organ Behav Hum Decis Process 122(1):92–99
63. OMG (2010) BPMN 2.0 by example. http://www.omg.org/spec/BPMN/2.0/examples/PDF. Accessed 27 Aug 2014
64. Khatri V, Vessey I, Ramesh V, Clay P, Sung-Jin P (2006) Understanding conceptual schemas: exploring the role of application and is domain knowledge. Inf Syst Res 17(1):81–99
65. Patig S, Casanova-Brito V, Vögeli B (2010) IT requirements of business process management in practice: an empirical study. In: Hull R, Mendling J, Tai S (eds) Business process management: BPM 2010. Lecture notes in computer science, vol 6336. Springer, Hoboken, pp 13–28
66. Reijers HA, Freytag T, Mendling J, Eckleder A (2011) Syntax highlighting in business process models. Decis Support Syst 51(3):339–349
67. zur Muehlen M, Recker J (2008) How much language is enough? Theoretical and practical use of the business process modeling notation. In: Léonard M, Bellahsène Z (eds) Advanced information systems engineering: CAiSE 2008. Lecture notes in computer science. Springer, Montpellier, pp 465–479
68. Saari DG (2000) Mathematical structure of voting paradoxes: II. Positional voting. Econ Theor 15(1):55–102
69. Cook C, Heath F, Thompson RL, Thompson B (2001) Score reliability in Webor internet-based surveys: unnumbered graphic rating scales versus Likert-type scales. Educ Psychol Measur 61(4):697–706
70. Gemino A, Wand Y (2004) A framework for empirical evaluation of conceptual modeling techniques. Requirements Eng 9(4):248–260
71. Compeau DR, Marcolin BL, Kelley H, Higgins CA (2012) Generalizability of information systems research using student subjects: a reflection on our practices and recommendations for future research. Inf Syst Res 23(4):1093–1109
72. Runeson P (2003) Using students as experiment subjects: an analysis on graduate and freshmen student data. In: Linkman S (ed) 7th International conference on empirical assessment & evaluation in software engineering, Staffordshire, England. Keele University, pp 95–102
73. Faul F, Erdfelder E, Lang A-G, Axel B (2007) G*Power 3: a flexible statistical power analysis for the social, behavioral, and biomedical sciences. Behav Res Methods 39(2):175–191
74. Leys C, Ley C, Klein O, Bernard P, Licata L (2013) Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol 49(4):764–766
75. Recker J (2013) Empirical investigation of the usefulness of gateway constructs in process models. Eur J Inf Syst 22(6):673–689
76. Figl K, Mendling J, Strembeck M (2013) The influence of notational deficiencies on process model comprehension. J Assoc Inf Syst 14(6):312–338
77. Reijers HA, Mendling J (2011) A study into the factors that influence the understandability of business process models. IEEE Trans Syst Man Cybern A 41:449–462
78. Stevens JP (2001) Applied multivariate statistics for the social sciences. Applied Multivariate STATS, 4th edn. Lawrence Erlbaum Associates, Hillsdale, New Jersey
79. Tabachnick BG, Fidell LS (2007) Using multivariate statistics. Pearson Education Inc, Boston
80. Kozhevnikov M, Hegarty M, Mayer RE (2002) Revising the visualizer-verbalizer dimension: evidence for two types of visualizers. Cogn Instr 20(1):47–77
81. Glenberg AM, Langston WE (1992) Comprehension of illustrated text: pictures help to build mental models. J Mem Lang 31(2):129–151
82. Cheng PC (2004) Why diagrams are (sometimes) six times easier than words: benefits beyond locational indexing. In: Diagrammatic representation and inference. Springer, pp 242–254
83. Scaife M, Rogers Y (1996) External cognition: how do graphical representations work? Int J Hum-Comput Stud 45(2):185–213
84. Mayer RE (2009) Multimedia learning, 2nd edn. Cambridge University Press, Cambridge
85. Shadish WR, Cook TD, Campbell DT (2002) Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin Company, Boston
86. Recker J, Dreiling A (2011) The effects of content presentation format and user characteristics on novice developers’ understanding of process models. Commun Assoc Inf Syst 28(6):65–84
87. Reijers HA, Mendling J, Dijkman RM (2011) Human and automatic modularizations of process models to enhance their comprehension. Inf Syst 36(5):881–897
88. Fisher RJ (1993) Social desirability bias and the validity of indirect questioning. J Consum Res 20(2):303–315
89. Paivio A, Harshmann R (1983) Factor analysis of a questionnaire on imagery and verbal habits and skills. Can J Psychol 37(4):461–483
90. Byström K, Järvelin K (1995) Task complexity affects information seeking and use. Inf Process Manage 31(2):191–213