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DELFI 2022 Workshops

https://dl.gi.de/handle/20.500.12116/39864
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Auflistung DELFI 2022 Workshops nach Autor:in "Das, Sanghamitra"

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  • Konferenzbeitrag
    High Accuracy GPS Antennas in Educational Location-based Augmented Reality
    (Proceedings of DELFI Workshops 2022, 2022) Osipova, Margarita; Das, Sanghamitra; Riyad, Peter; Söbke, Heinrich; Wolf, Mario; Wehking, Florian
    In location-based augmented reality (AR), the augmentations depend on the geolocation. Location-based AR might be used in higher education for enabling authentic learning experiences. However, the positioning accuracy achievable with GPS receivers built into off-the-shelf mobile devices has been shown in previous studies to be suboptimal for a subset of learning scenarios. Accordingly, in this comparative study, we investigated whether high accuracy GPS antennas are capable of achieving higher positioning accuracy, which also may improve the learning experience. Specifically, a mobile geographical information system (GIS) client (AugView) was used to visual-ize pipes and manholes in the underground. Participants were tasked with recording a local sewer system using the GIS client and subsequently visualizing the network using the GIS client’s AR mode. The experimental group (N=8) used an external GPS antenna, while the control group (N=8) relied on the standard GPS receivers of the mobile device. Usability was assessed using the Post-Study System Usability Questionnaire, learning outcomes were measured using pre- and post-test. In addition, semi-structured interviews were conducted with all participants. As a result, usability and learning outcomes were found to be better for the experimental group, but deficits in accuracy of the visualizations were also found with the GPS antenna. In particular, the time delay that must be waited until a high accuracy is achieved in case of non-uniform motion has to be noted. However, this time delay can be compensated for with appropriate learning scenarios design. In summary, high accuracy GPS antennas seem being beneficial to learning scenarios but require careful context-spe-cific prior evaluation.