@article{SchobelProbstReichertetal.2020,
  author    = {Schobel, Johannes and Probst, Thomas and Reichert, Manfred and Schlee, Winfried and Schickler, Marc and Kestler, Hans A. and Pryss, R{\"u}diger},
  title     = {Measuring mental effort for creating mobile data collection applications},
  series = {International Journal of Environmental Research and Public Health},
  volume    = {17},
  journal   = {International Journal of Environmental Research and Public Health},
  number    = {5},
  issn      = {1660-4601},
  doi       = {10.3390/ijerph17051649},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203176},
  year      = {2020},
  abstract  = {To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N=80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials.},
  language  = {en}
}
@article{SchicklerReichertGeigeretal.2020,
  author    = {Schickler, Marc and Reichert, Manfred and Geiger, Philip and Winkler, Jens and Funk, Thomas and Weilbach, Micha and Pryss, R{\"u}diger},
  title     = {Flexible development of location-based mobile augmented reality applications with AREA},
  series = {Journal of Ambient Intelligence and Humanized Computing},
  volume    = {11},
  journal   = {Journal of Ambient Intelligence and Humanized Computing},
  issn      = {1868-5137},
  doi       = {10.1007/s12652-020-02094-9},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232773},
  pages     = {5809-5824},
  year      = {2020},
  abstract  = {Mobile applications have garnered a lot of attention in the last years. The computational capabilities of mobile devices are the mainstay to develop completely new application types. The provision of augmented reality experiences on mobile devices paves one alley in this field. For example, in the automotive domain, augmented reality applications are used to experience, inter alia, the interior of a car by moving a mobile device around. The device's camera then detects interior parts and shows additional information to the customer within the camera view. Another application type that is increasingly utilized is related to the combination of serious games with mobile augmented reality functions. Although the latter combination is promising for many scenarios, technically, it is a complex endeavor. In the AREA (Augmented Reality Engine Application) project, a kernel was implemented that enables location-based mobile augmented reality applications. Importantly, this kernel provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. The work at hand shows the flexibility of AREA based on a developed serious game. Furthermore, the algorithm framework and major features of it are presented. As the conclusion of this paper, it is shown that mobile augmented reality applications require high development efforts. Therefore, flexible frameworks like AREA are crucial to develop respective applications in a reasonable time.},
  language  = {en}
}