11.12.2025 | Beitrag auf der ACIS 2025

Die Professur für Anwendungssysteme und E-Business ist mit zwei Beiträgen auf der Australasian Conference on Information Systems (ACIS 2025) vertreten:



Tamino Marahrens präsentierte den Beitrag:
From Data to Dialogue: Connecting Large Language Models with Digital Twins in Industrial Production



Abstract: Modern industrial production systems challenge current digital twin (DT) approaches, which often rely on rigid rules, static dashboards, and task-specific views. These methods lack semantic reasoning, create high cognitive load, and limit flexible interaction, leaving many DT insights unused. Large language models (LLMs) address this gap by enabling semantic interpretation of heterogeneous data, natural language interaction, and domain knowledge integration. Acting as intermediaries, LLMs translate human queries into machine tasks and reframe DT outputs into human-understandable explanations. To support diverse monitoring, simulation, and control needs, we design a multi-agent architecture where specialized LLM agents cooperate, each focused on a functional area. This modular design allows task-specific reasoning and scalable adaptation. Using a design science approach, we derive requirements, build the architecture, and demonstrate it in a simulated scenario, showing benefits in explainability, adaptability, and human-centered interaction.




Leonie Kopahs präsentierte den Beitrag:
Beyond Immersive Experiences: A Statistical Study on VR-Based Education of IS Students



Abstract:The growing use of immersive technologies in higher education raises questions about how Virtual Reality (VR) supports meaningful learning in Information Systems (IS) education. This study examines a VR-based IS tool, assessing how system usability, demographics, and prior VR experience affect perceived learning, and how these perceptions align with objective outcomes. Using a pre–post test with 52 IS students, analyses revealed that usability strongly predicts perceived learning, while demographic factors have no significant effect. Correlations show links between realism/presence and perceived learning, yet subjective and objective results align only weakly. Cluster analysis identified overestimators, underestimators, and calibrated learners, emphasizing diverse engagement patterns. Findings highlight VR’s potential to build technological competence, process understanding, and self-directed learning, but also the need for metacognitive scaffolding and adaptive instruction to bridge the gap between perception and performance, offering exploratory insights into how VR can foster digital competence in IS education.