TY - JOUR A1 - Seeber, Isabella A1 - Fleischmann, Carolin A1 - Cardon, Peter A1 - Aritz, Jolanta T1 - Fostering Psychological Safety in Global Virtual Teams: The Role of Team-Based Interventions and Digital Reminder Nudges JF - Group Decision and Negotiation N2 - Psychological safety (PS), the feeling of being comfortable to express one’s ideas or opinions in teams, is a key determinant of successful global virtual teams (GVT). Even though considerable knowledge exists about its antecedents, it is unknown how team-based interventions (TBI) and technology-based interventions (digital reminder nudges, DRN) foster PS among team members. Based on a survey involving 235 participants, our data show that TBI and DRN foster psychological safety in GVT. However, only the effect of TBI on psychological safety can be explained with a higher-quality coordination process. It remains unclear what causal mechanism explains the effect of DRN. These findings contribute to the literature on PS by showing that TBI facilitate effective coordination processes and to the literature on digital nudges by demonstrating that technology-based reminders drive PS. KW - Artificial Intelligence KW - Collaboration KW - Digital nudging KW - Global virtual teams KW - Psychological safety KW - Team intervention Y1 - 2024 U6 - https://doi.org/10.1007/s10726-024-09899-5 ER - TY - CHAP A1 - Suhonen, Sami ED - Schäfle, Claudia ED - Stanzel, Silke ED - Junker, Elmar ED - Lux, Christine T1 - Navigating the AI Era: Analyzing the Impact of Artificial Intelligence on Learning and Teaching Engineering Physics T2 - Proceedings of the 12th International Conference on Physics Teaching in Engineering Education PTEE 2024 N2 - This paper delves into the impact of artificial intelligence (AI) on learning and teaching engineering physics, focusing on the use of AI chatbots. The study explores various issues encountered by educators when students utilize AI to solve physics problems, highlighting potential pitfalls and opportunities. Through testing AI chatbots' capabilities in physics learning, the paper evaluates their effectiveness in providing accurate and insightful responses. Results indicate that while AI, especially ChatGPT 4, shows promise in aiding students' understanding of physics concepts, there are limitations and challenges to consider, such as over-reliance on technology and the potential for AI to produce misleading solutions. The implications and discussions underscore the need for a balanced approach in integrating AI into education, emphasizing authentic understanding over merely obtaining correct answers. Using AI in creating teaching materials is not evaluated here. T3 - Proceedings of the 12th International Conference on Physics Teaching in Engineering Education PTEE 2024 - 1 KW - Artificial Intelligence KW - physics teaching KW - physics learning Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-25848 SP - 76 EP - 83 ER - TY - CHAP A1 - Mucha, Henrik A1 - Mevißen, Dennis A1 - Robert, Sebastian A1 - Jacobi, Ricarda A1 - Meyer, Kirsten A1 - Heusler, Winfried A1 - Arztmann, Daniel T1 - Co-Design Futures for AI and Space: A Workbook Sprint T2 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI EA '20). Association for Computing Machinery, New York, NY, USA N2 - Artificial Intelligence (AI) is continuously moving into our surroundings. In its various forms, it has the potential to disrupt most aspects of human life. Yet, the discourse around AI has long been by experts and for experts. In this paper, we argue for a participatory approach towards designing human-AI interactions. We outline how we used design methodology to organise an interdisciplinary workshop with a diverse group of students – a workbook sprint with 45 participants from four different programs and 13 countries – to develop speculative design futures in five focus areas. We then provide insights into our findings and share our lessons learned regarding our workshop topic – AI and Space – our process, and our research. We learned that involving non-experts in complex technical discourses – such as AI – through the structural rigour of design methodology is a viable approach. We then conclude by laying out how others might use our findings and initiate their own workbook sprint to explore complex technologies in a human-centred way. KW - Artificial Intelligence Y1 - 2021 UR - https://doi.org/10.1145/3334480.3375203 SP - 1 EP - 8 ER -