@article{WinterPryssProbstetal.2020,
  author    = {Winter, Michael and Pryss, R{\"u}diger and Probst, Thomas and Reichert, Manfred},
  title     = {Towards the applicability of measuring the electrodermal activity in the context of process model comprehension: feasibility study},
  series = {Sensors},
  volume    = {20},
  journal   = {Sensors},
  number    = {16},
  issn      = {1424-8220},
  doi       = {10.3390/s20164561},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-211276},
  year      = {2020},
  abstract  = {Process model comprehension is essential in order to understand the five Ws (i.e., who, what, where, when, and why) pertaining to the processes of organizations. However, research in this context showed that a proper comprehension of process models often poses a challenge in practice. For this reason, a vast body of research exists studying the factors having an influence on process model comprehension. In order to point research towards a neuro-centric perspective in this context, the paper at hand evaluates the appropriateness of measuring the electrodermal activity (EDA) during the comprehension of process models. Therefore, a preliminary test run and a feasibility study were conducted relying on an EDA and physical activity sensor to record the EDA during process model comprehension. The insights obtained from the feasibility study demonstrated that process model comprehension leads to an increased activity in the EDA. Furthermore, EDA-related results indicated significantly that participants were confronted with a higher cognitive load during the comprehension of complex process models. In addition, the experiences and limitations we learned in measuring the EDA during the comprehension of process models are discussed in this paper. In conclusion, the feasibility study demonstrated that the measurement of the EDA could be an appropriate method to obtain new insights into process model comprehension.},
  language  = {en}
}
@article{WinterPryssProbstetal.2021,
  author    = {Winter, Michael and Pryss, R{\"u}diger and Probst, Thomas and Reichert, Manfred},
  title     = {Applying Eye Movement Modeling Examples to guide novices' attention in the comprehension of process models},
  series = {Brain Sciences},
  volume    = {11},
  journal   = {Brain Sciences},
  number    = {1},
  issn      = {2076-3425},
  doi       = {10.3390/brainsci11010072},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-222966},
  year      = {2021},
  abstract  = {Process models are crucial artifacts in many domains, and hence, their proper comprehension is of importance. Process models mediate a plethora of aspects that are needed to be comprehended correctly. Novices especially face difficulties in the comprehension of process models, since the correct comprehension of such models requires process modeling expertise and visual observation capabilities to interpret these models correctly. Research from other domains demonstrated that the visual observation capabilities of experts can be conveyed to novices. In order to evaluate the latter in the context of process model comprehension, this paper presents the results from ongoing research, in which gaze data from experts are used as Eye Movement Modeling Examples (EMMEs) to convey visual observation capabilities to novices. Compared to prior results, the application of EMMEs improves process model comprehension significantly for novices. Novices achieved in some cases similar performances in process model comprehension to experts. The study's insights highlight the positive effect of EMMEs on fostering the comprehension of process models.},
  language  = {en}
}
@article{KirikkayisGallikWinteretal.2023,
  author    = {Kirikkayis, Yusuf and Gallik, Florian and Winter, Michael and Reichert, Manfred},
  title     = {BPMNE4IoT: a framework for modeling, executing and monitoring IoT-driven processes},
  series = {Future Internet},
  volume    = {15},
  journal   = {Future Internet},
  number    = {3},
  issn      = {1999-5903},
  doi       = {10.3390/fi15030090},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304097},
  year      = {2023},
  abstract  = {The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we present BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes.},
  language  = {en}
}