Much research has been done on the comprehension and development of enterprise process models. In this paper, we follow up on work done previously by others on the effect of ambiguities on model comprehension. Ambiguities might lead to multiple alternative process interpretations by the readers of process models.
In this paper, we will present research on techniques for collecting biometric data to investigate how we work with visual process models, some of which include lexical or visual ambiguities. We report an experiment with data from 26 persons as they interpret both unambiguous and ambiguous process models. The approach, which is based on techniques used in multi-modal learning analytics (MMLA), investigates how the type of ambiguity is correlated with data collected in parallel from EEG, eye-tracking and cameras (tracking facial landmarks).
When working with ambiguous models, we generally find significantly higher memory load, cognitive load, convergent thinking, attention, information processing index, stress and confusion. Visual ambiguous models provide significantly higher numbers on these measures than lexically ambiguous models. In contrast, we find no difference in other cognitive, behavioural, and affective measures such as frustration and boredom.
This work reports early investigations on the impact of ambiguity in process model comprehension. A deeper understanding of how individuals process ambiguous models can inform the design of more precise and effective visual representations, improving the usability of modelling and reducing misinterpretation.
