Auflistung nach Autor:in "Pammer-Schindler, Viktoria"
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- ZeitschriftenartikelAI Literacy für EntscheidungsträgerInnen im strategischen Management(Wirtschaftsinformatik & Management: Vol. 14, No. 2, 2022) Pammer-Schindler, Viktoria; Lindstaedt, Stefanie
- KonferenzbeitragBeyond Textbooks: A Study on Supporting Learning of Molecule Naming in a Virtual Reality Environment(Proceedings of Mensch und Computer 2024, 2024) Disch, Leonie; Überreiter, Sebastian; Pammer-Schindler, ViktoriaVirtual reality (VR) applications promise to enhance learning experiences, with literature emphasizing game-based components, immersiveness, and exploration of inaccessible scenarios. However, effective learning through VR applications depends on technology design. This within-subjects study investigates a VR application targeted to learning molecule naming, following design principles for VR and knowledge construction. Our results show that participants (n=20) had a positive direct learning effect, as they scored significantly better in a knowledge test on molecule naming directly after the intervention compared to before. Further, a sustainable learning effect could be shown, as scores in the knowledge test after three weeks were significantly better than those before the intervention but did not differ from those directly after the intervention. Our contribution is demonstrating design guidelines for learning and knowledge construction in VR, specifically for chemistry, and showing that following such guidelines leads to an application that effectively supports learning.
- KonferenzbeitragA Cautionary Tale About AI-Generated Goal Suggestions(Mensch und Computer 2022 - Tagungsband, 2022) Lieder, Falk; Chen, Pin-Zhen; Consul, Saksham; Stojcheski, Jugoslav; Pammer-Schindler, ViktoriaSetting the right goals and prioritizing them might be the most crucial and the most challenging type of decisions people make for themselves, their teams, and their organizations. In this article, we explore whether it might be possible to leverage artificial intelligence (AI) to help people set better goals and which potential problems might arise from such applications. We devised the first prototype of an AI-powered digital goal-setting assistant and a rigorous empirical paradigm for assessing the quality of AI-generated goal suggestions. Our empirical paradigm compares the AI-generated goal suggestions against randomly-generated goal suggestions and unassisted goal-setting on a battery of self-report measures of important goal characteristics, motivation, and usability in a large-scale repeated-measures online experiment. The results of an online experiment with 259 participants revealed that our intuitively compelling goal suggestion algorithm was actively harmful to the quality of the people’s goals and their motivation to pursue them. These surprising findings highlight three crucial problems to be tackled by future work on leveraging AI to help people set better goals: i) aligning the objective function of the AI algorithms with the design goals, ii) helping people quantify how valuable different goals are to them, and iii) preserving the user’s sense of autonomy.
- KonferenzbeitragCollaborating in a Research and Development Project: Knowledge Protection Practices applied in a Co-opetitive Setting(WM 2019 - Wissensmanagement in digitalen Arbeitswelten: Aktuelle Ansätze und Perspektiven - Knowledge Management in Digital Workplace Environments: State of the Art and Outlook, 2020) Kaiser, Rene; Thalmann, Stefan; Pammer-Schindler, Viktoria; Fessl, AngelaOrganisations participate in collaborative projects that include competitors for a number of strategic reasons, even whilst knowing that this requires them to consider both knowledge sharing and knowledge protection throughout collaboration. In this paper, we investigated which knowledge protection practices representatives of organizations employ in a collaborative research and innovation project that can be characterized as a co-opetitive setting. We conducted a series of 30 interviews and report the following seven practices in structured form: restrictive partner selection in operative project tasks, communication through a gatekeeper, to limit access to a central platform, to hide details of machine data dumps, to have data not leave a factory for analysis, a generic model enabling to hide usage parameters, and to apply legal measures. When connecting each practice to a priori literature, we find three practices focussing on collaborative data analytics tasks had not yet been covered so far.
- ZeitschriftenartikelDecision making support in security forces command centers at open air music festivals: Localization of resources and sharing information(it - Information Technology: Vol. 60, No. 4, 2018) Köfler, Armin; Pammer-Schindler, Viktoria; Almer, Alexander; Schnabel, ThomasWe describe a case study on decision making in command centers of security forces at major open air music festivals. Our goal was to assess current modus operandi and to identify design implications. We have carried out two expert interviews, two field observations and four group discussions with experts based on a fully functional prototype as IT artifact to concretize discussions. Key insights are that in this case localization of relevant resources is the most important aspect of situation awareness, and that state of current knowledge needs to be clearly shared within the command center.
- ZeitschriftenartikelDigital und/oder analog? Zusammenarbeit am Arbeitsplatz aus der Perspektive österreichischer Unternehmen(Wirtschaftsinformatik & Management: Vol. 13, No. 1, 2021) Rauter, Romana; Lerch, Anita; Lederer-Hutsteiner, Thomas; Klinger, Sabine; Mayr, Andrea; Gutounig, Robert; Pammer-Schindler, Viktoria
- KonferenzbeitragHow Do Professionals in SMEs Engage With AI and Regulation? An Interview Study in Austria(Proceedings of Mensch und Computer 2024, 2024) Wolf-Brenner, Christof; Pammer-Schindler, Viktoria; Breitfuss, GertAs Artificial Intelligence (AI) technology is becoming more widespread, small to medium sized enterprises (SMEs) are beginning to use it extensively. This paper presents the results of an interview study with eight CEOs or co-founders of SMEs. We explore the practical applications of AI technologies within these SMEs and their anticipation of forthcoming European AI regulations, specifically the AI Act. Additionally, we also investigate attitudes and dispositions towards voluntary codes of conduct as outlined within it. This study aims to shed light on the operational, regulatory, and ethical dimensions of AI integration within SMEs. It reveals that SMEs favor third-party AI systems, particularly those based on Large Language Models (LLMs), due to their convenience and minimal integration effort. Additionally, SMEs are keenly aware of their need for external support to navigate upcoming AI regulations, emphasizing the importance of tailored interventions to ensure compliance and optimal use of AI technologies. Lastly, SMEs view voluntary codes of conduct as outlined in the AI Act as a testament to a company’s commitment to go beyond mere legal compliance, thus reinforcing trust. Based on our findings, we propose three design implications for the HCI community: convenient AI integration, post-adoptive regulatory support, and proactive ethical design.
- KonferenzbeitragWhat do Construction Workers Know about Artificial Intelligence? An Exploratory Case Study in an Austrian SME(Mensch und Computer 2022 - Tagungsband, 2022) Maitz, Katharina; Fessl, Angela; Pammer-Schindler, Viktoria; Kaiser, Rene; Lindstaedt, StefanieArtificial intelligence (AI) is by now used in many different work settings, including construction industry. As new technologies change business and work processes, one important aspect is to understand how potentially affected workers perceive and understand the existing and upcoming AI in their work environment. In this work, we present the results of an exploratory case study with 20 construction workers in a small Austrian company about their knowledge of and attitudes toward AI. Our results show that construction workers’ understanding of AI as a concept is rather superficial, diffuse, and vague, often linked to physical and tangible entities such as robots, and often based on inappropriate sources of information which can lead to misconceptions about AI and AI anxiety. Learning opportunities for promoting (future) construction workers’ AI literacy should be accessible and understandable for learners at various educational levels and encompass aspects such as i) conveying the basics of digitalization, automation, and AI to enable a clear distinction of these concepts, ii) building on the learners’ actual experience realm, i.e., taking into account their focus on physical, tangible, and visible entities, and iii) reducing AI anxiety by elaborating on the limits of AI.