Eye Tracking Experiments on Process Model Comprehension: Lessons Learned

For documenting business processes, there exists a plethora of process modeling languages. In this context, graphical process models are used to enhance the process comprehensibility of the stakeholders involved. The large number of available modeling languages, however, aggravates process model comprehension and increases the knowledge gap between domain and modeling experts. Upon this, one major challenge is to identify factors fostering the comprehension of process models. This paper discusses the experiences we gathered with the use of eye tracking in experiments on process model comprehension and the lessons learned in this context. The objective of the experiments was to study the comprehension of process models expressed in terms of four different modeling languages (i.e., BPMN, eGantt, EPC, and Petri Net). This paper further provides recommendations along nine identified categories that can foster related experiments on process model comprehension.