@inproceedings{NeumannBuettnerHernandezAcostaetal.2024, author = {Neumann, Paul and B{\"u}ttner, Sebastian Thomas and Hern{\´a}ndez Acosta, Luca and Reinhardt, Delphine and Prilla, Michael}, title = {"I Don't Want Parents to Watch My Lessons" - Privacy Trade-offs in the Use of Telepresence Robots in Schools for Children with Long-term Illnesses}, series = {MuC '24: Proceedings of Mensch und Computer 2024, Karlsruhe Germany September 1-4, 2024}, booktitle = {MuC '24: Proceedings of Mensch und Computer 2024, Karlsruhe Germany September 1-4, 2024}, publisher = {ACM Digital Library}, isbn = {979-8-4007-0998-2}, doi = {10.1145/3670653.3677509}, pages = {448 -- 454}, year = {2024}, abstract = {Abstract Telepresence robots offer great opportunities for children with long-term illnesses to continue attending school. Consequently, they are already used if children are absent for long periods. When designing such systems, the privacy of various stakeholders must be considered. However, conflicts often arise because the privacy requirements of different user groups cannot be fulfilled simultaneously. In this paper, we analyze the corresponding trade-offs that have to be made when designing telepresence robots under conflicting privacy requirements. We analyzed previous literature and held three workshops with different user groups (children, parents, teachers, head teachers, media educators, and supporting personnel) with and without experience with telepresence robots in schools. Based on the literature and the workshop results, we present four major privacy trade-offs we identified and discuss design approaches for them. With this work, we contribute to the design research on telepresence robots in schools by revealing the major privacy-related conflicts and potential design approaches to overcome the conflicts.}, language = {en} } @inproceedings{GuemuesGutzmannBuettneretal.2024, author = {G{\"u}m{\"u}s, Esra and Gutzmann, Jan Christoph and B{\"u}ttner, Sebastian Thomas and Prilla, Michael}, title = {The Impact of Smart-glass-based Video Tutorials on Knowledge Transfer in Practice}, series = {MuC '24: Proceedings of Mensch und Computer 2024, Karlsruhe Germany September 1-4, 2024}, booktitle = {MuC '24: Proceedings of Mensch und Computer 2024, Karlsruhe Germany September 1-4, 2024}, publisher = {ACM Digital Library}, isbn = {979-8-4007-0998-2}, doi = {10.1145/3670653.3670673}, pages = {219 -- 230}, year = {2024}, abstract = {Abstract Video tutorials are an effective method of knowledge transfer and learning. However, they are often time-consuming to create and difficult to access during work. This paper introduces an approach that simplifies the creation of video tutorials in the workplace and promotes their use during work. By utilizing smart glasses, practitioners can record video tutorials during their daily work processes and utilize them for knowledge transfer to other employees without much additional effort. This offers the advantage of directly and easily sharing expertise in the workplace without being constrained by time or location. Given the intended simplicity of this approach, the question arises whether it creates video tutorials that help people in their learning. The paper presents a study that compares the effectiveness of knowledge transfer using these video tutorials against traditional personal training methods in the workplace. With 18 participants from the nursing and production sectors, we observed the training and learning outcomes of using video tutorials on smart glasses over multiple sessions, comparing them with personal training, which is considered the standard for practical onboarding. The study results indicate that learning with video tutorials does not significantly differ in terms of learning outcomes from traditional personal training methods. Overall, this study highlights the potential of video tutorials with smart glasses for knowledge transfer in workplaces, while also identifying challenges and opportunities for optimizing onboarding processes for employees.}, language = {en} } @article{AlhajiBuettnerKumaretal.2023, author = {Alhaji, Basel and B{\"u}ttner, Sebastian Thomas and Kumar, Shushanth Sanjay and Prilla, Michael}, title = {Trust dynamics in human interaction with an industrial robot}, series = {Behaviour \& Information Technology}, volume = {2025}, journal = {Behaviour \& Information Technology}, number = {Vol. 44, No. 2}, publisher = {Taylor \& Francis}, doi = {10.1080/0144929X.2024.2316284}, pages = {266 -- 288}, year = {2023}, abstract = {ABSTRACT Trust is important for collaboration. In hybrid teams of humans and robots, trust enables smooth collaboration and reduces risks. Just as collaboration between humans and robots differs from interpersonal collaboration, so does the nature of trust in human-robot interaction (HRI). Therefore, further investigations on trust formation and dissolution in HRI, factors affecting it, and means for keeping trust on an appropriate level are needed. However, our knowledge of interpersonal trust and trust in autonomous agents cannot be transferred directly to HRI. In this paper, we present a study with 32 participants on trust formation and dissolution as well as forecasting to influence trust in an industry robot. Results show differences in dynamics and factors of trust formation and dissolution. Additionally, we find that the effect of forecasting on trust depends on task success. These findings support the design of trustful human-robot interaction and corresponding robotic team members.}, language = {en} }