This document summarizes a study that tested the understandability of hybrid process models using DCR graphs. The study collected data such as eye tracking and questionnaires from participants to analyze how attention was distributed across different artifacts (the graph, text, law, and simulation). Results showed that subjects' attention was distributed differently, with some focusing more on the graph, some more on the simulation, and some more on the law text. Process mining was used to analyze reading patterns. Future work will analyze comprehension accuracy and the cognitive processes and emotions involved. The goal is to effectively integrate hybrid technologies into knowledge work processes in public administrations.

1. Testing the Understandability of
Hybrid Process Models Using DCR
Graphs
Ecoknow workshop, June 15th 2018. Tallinn, Estonia
Authors:
Amine ABBAD ANDALOUSSI
Tijs SLAATS
Andrea BURATTIN
Thomas T. HILDEBRANDT
Barbara WEBER

2. 2
Hybrid DCR Graphs
DCR graph – declarative
process model
Textual annotation
Simulation tool
• Integrate hybrid technologies in public administrations as part of the
effective digitalization of knowledge work processes

3. Multi-modal Data Collection
3
Think aloud
User interactions
Eye tracking Galvanic Skin Response (GSR)
Questionnaires User Interactions

4. Research Questions
• RQ1: How is the subjects’ attention
distributed over the different
artifacts provided by the hybrid
representation of DCR graphs?
4
Distribution of attention (RQ1) Usage of artifacts (RQ2)
Comprehension accuracy (RQ3) Mental effort and emotions (RQ4)

5. Exploratory Study Design
5
Section §45 of the ``Consolidation Act on Social Services”.
• Model questions
• Simulation questions
• Law questions

6. RQ1: Analysis of Attention Distribution (Measures)
• A fixation represents the time-span when the eye remains still at
specific position of the stimulus
6
Total Fixation Duration Fixation Count
• Fixation-based measures

7. RQ1: Analysis of Attention Distribution (Measures)
• The fixations-based measures can be used to investigate the distribution of
attention on different areas of interest
7

8. RQ1: Analysis of Attention Distribution (Measures)
• Analysis of AOIs transition
8
Example of subjects’ reading pattern*
*Process map obtained using process mining tool Disco

9. RQ1: Analysis of Attention Distribution (Results)
9
• Between artifact Total fixation duration measure
Graph Law Text Simulation
Fixation count measure
Graph Law Text Simulation
Subjective artifact questionnaire
Graph Law Text Simulation

10. 10
• Between subjects
Total Fixation Duration Proportions Fixation Count Proportions
Subject Graph Law Text Simulation Graph Law Text Simulation
P01 0.529 0.414 0.057 0.528 0.420 0.051
P02 0.389 0.186 0.425 0.403 0.147 0.451
P03 0.695 0.221 0.084 0.663 0.245 0.092
P05 0.258 0.484 0.258 0.273 0.437 0.289
P06 0.484 0.052 0.464 0.476 0.046 0.477
P07 0.611 0.341 0.048 0.620 0.322 0.058
P08 0.384 0.330 0.286 0.358 0.327 0.314
P09 0.644 0.202 0.154 0.618 0.216 0.166
P10 0.647 0.299 0.055 0.674 0.268 0.059
RQ1: Analysis of Attention Distribution (Results)

11. 11
• Between profiles
12
2 32 1
4
2
2
graph
19
law text
3
simulation
4
Reading pattern of graph profile subjects
RQ1: Analysis of Attention Distribution (Results)

12. 12
• Between profiles
Reading pattern of simulation profile subjects
7
26 722
6
8
3
3
graph
40
simulation
33
law text
9
RQ1: Analysis of Attention Distribution (Results)

13. 13
• Between profiles
Reading pattern of law profile subjects
10
9 8
2
1
1
graph
20
law text
10
RQ1: Analysis of Attention Distribution (Results)

14. Conclusion
• Provide early insights about subjects’ attention distribution and
reading patterns
• Propose process mining to analyze the reading patterns
14
Future Work
• Analyze the verbal data to identify the typical challenges faced by
the participants, and the most reoccurring ones
• Analyze comprehension accuracy
• Investigate the underlying cognitive process and emotional
reactions

15. Thanks for your attention!
“…not even the most brilliant solution to a problem would be of
any use if no one could understand it.”
Odd Ivar Lindland