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What Makes Process Models Understandable

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Need for appropriately qualified process modelers increases with the ... but education seems to be curial. CRICOS No. 00213J. a university for the. world. real ... – PowerPoint PPT presentation

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Title: What Makes Process Models Understandable


1
What Makes Process Models Understandable?
  • Jan Mendling (QUT Brisbane)
  • Hajo Reijers (TU Eindhoven)
  • Jorge Cardoso (Uni Madeira)

2
Quality Issues in Process Modeling
  • Need for appropriately qualified process modelers
    increases with the size of the modeling
    initiative (Rosemann 2006)
  • The cost of errors increases exponentially over
    the development lifecycle (Boehm 1981, Moody
    2005)

3
Agenda
  • What we know about model quality
  • What we dont know about model quality
  • What we learned about understandability
  • What conclusions can we draw

4
Agenda
  • What we know about model quality
  • What we dont know about model quality
  • What we learned about understandability

5
What we know about model quality (I)
  • 1.) Theoretical description of what model
    quality is

Krogstie, Sindre, and Jørgensen (2006)
6
What we know about model quality (II)
  • 2.) Pragmatic definition of modeling guidelines

Becker, Rosemann, v. Uthmann (2006)
7
What we know about model quality (III)
  • 3.) Quality issues in practice

Mendling (2007)
8
Agenda
  • What we know about model quality
  • What we dont know about model quality
  • What we learned about understandability

9
Understandability
10
Understandability (I)
11
Understandability (II)
12
Questionnaire
  • 12 models, 4 models in 3 variants each
  • 8 closed questions per model
  • 73 BPM students

13
Hypotheses
14
Agenda
  • What we know about model quality
  • What we dont know about model quality
  • What we learned about understandability

15
Understandability depends upon model
16
but small changes have huge impact
If T is executed for a case, can U be executed
for the same case?
17
Understandability depends upon reader
18
but education seems to be curial
19
Conclusions
  • Deeper analysis of personal and model factors
  • Investigate further factors
  • Purpose of model
  • Domain knowledge of reader
  • Modeling language
  • Visual layout
  • Modeling education
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