Digital Library of Gesellschaft für Informatik e.V.
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The Sound of Synthetic: A Scoping Review of Human Perception in Detecting Synthetic Voices
No full textThis scoping review synthesizes existing literature on how humans perceive and detect synthetic voices, emphasizing the auditory cues listeners rely on and the factors influencing their accuracy. By highlighting both the positive and negative implications of this technology, we analyze the studies with a focus on the misuse of synthetic voice. Research suggests that detection capabilities are often unreliable, with individuals relying on cues such as intuition/gut feeling, liveliness, emotions, linguistic features, and environmental features. This review examines how studies have explored these issues, analyzing human detection accuracy, detection cues, and empirical findings across human-computer interaction and artificial intelligence research. By mapping current research trends, this study identifies gaps in understanding human synthetic voice detection and proposes directions for future research
Quick, Tangible, Playful: Reducing Barriers to Feedback
No full textOften, we as researchers and practitioners want to get feedback on an activity. This is a surprisingly complex task, because we need to convince people to give feedback and use the time they spend interacting with us wisely. A common solution is to offer an online survey and to provide access to the survey using a QR code. This makes feedback much easier to collect and analyse. But it is not clear how many potential participants we lose by offering just a QR code option. We studied this question by comparing three feedback options at two exhibitions staged by the University of Lapland Design team. The options were tangible feedback, a paper survey, and a QR code survey. We found that most participants engaged with the tangible options, followed by paper. Only one person per exhibition used the QR code. We discuss implications for analogue versus digital feedback
Unfolding IoT Adoption: A Status Quo Bias Perspective
No full textInternet of Things (IoT) solutions are still far from using their enormous potential, partly because misconceptions lead employees to avoid using IoT solutions and stick to established working routines. To shed light on the non-rational perspective of users, which allows for inference on the emergence of cognitive misconceptions, 489 respondents' perceptions of benefits and costs of IoT solutions were analyzed. Using the perspective of “status quo bias”, the qualitative analysis reveals that the perceptions of experienced and inexperienced users partly overlap on benefits such as the reduction of errors and relief of personnel. However, the perceptions also diverge in part, as inexperienced users consider IoT solutions to be gimmicky, fostering mistrust. In addition, inexperienced users overestimate learning phases for interacting with IoT solutions, leading to loss aversion and consequently to cognitive misperceptions. Hence, the study examines the gap between experienced and inexperienced users as a neglected aspect in IoT adoption. Further, identifying relevant drivers for the implementation of IoT solutions at the individual level helps to extend the hitherto technical view of IoT solutions towards a multi-layer approach that includes a holistic, behavioral perspective
Projektmanagement und Vorgehensmodelle 2025 - Post-Agilität, Resilienz, Transformation - Komplettband
No full textEine skalierbare Plattform zur intermodalen Erreichbarkeitsanalyse im öffentlichen Verkehr unter Einbeziehung von Shared Mobility
No full textDie Integration fahrplan- und nachfragebasierter Mobilitätsangebote stellt eine zentrale Herausforderung für die Analyse und Planung intermodaler Verkehrssysteme dar. Dieser Beitrag präsentiert eine skalierbare Plattform, die Daten aus dem öffentlichen Verkehr, wie Bus und Bahn, mit modernen Shared-Mobility-Diensten, wie Leihfahrrädern, Carsharing und E‑Scootern, verbindet. Ziel ist die Entwicklung einer holistischen Datenarchitektur, die eine umfassende Analyse der Erreichbarkeit ermöglicht. Erreichbarkeit beschreibt in diesem Kontext, wie gut Personen von einem bestimmten Ort aus innerhalb einer festgelegten Zeitspanne andere Orte erreichen können. Der Ansatz umfasst die Transformation von Fahrplandaten in ein Property-Graph-Modell sowie die flexible Integration nachfragebasierter Datenformate in ein dokumentbasiertes Modell. Eine auf Isochronen basierende Metrik wird entwickelt, um regionale und überregionale Erreichbarkeiten zu bewerten. Anhand von Anwendungsfällen, darunter Infrastrukturänderungen und What-if-Analysen, wird gezeigt, wie datengetriebene Entscheidungen zur Verbesserung der Mobilität getroffen werden können. The integration of timetable-based and demand-based mobility services is a key challenge for the analysis and planning of intermodal transportation systems. This paper presents a scalable platform that combines data from public transportation, such as buses and trains, with modern shared mobility services, such as rental bikes, car sharing, and e‑scooters. The aim is to develop a holistic data architecture that enables a comprehensive analysis of reachability. In this context, reachability describes how well people can reach other places from a specific location within a specified period of time. The approach includes the transformation of timetable data into a property graph model and the flexible integration of demand-based data formats into a document-based model. An isochrone-based metric will be developed to assess regional and interregional reachability. Use cases, including infrastructure changes and what-if analyses, demonstrate how data-driven decisions can be made in order to improve mobility
Empowering Communities through IoT2: A Citizen Science Approach to Flood Monitoring and AI-supported Resource Optimization - Digital Resilience, Maker Education, and Energy-Aware IoT Development
No full textThis paper presents an integrated educational and technical framework for strengthening climate resilience and digital empowerment through citizen-driven environmental sensing and
algorithmic literacy. The IoT²-Werkstatt4 is an open platform that enables students, teachers and
communities to build and program IoT-based monitoring devices using open, visual and AI-supported tools. As a central use case, we examine a co-developed flood monitoring project carried
out as part of the project “DigiSelfTrans”5. The platform fosters technical and civic empowerment
in STEM education (Science, Technology, Engineering, Mathematics), particularly in rural areas. This paper outlines the conceptual foundations and implementation strategy of the IoT²-Werkstatt, presents selected outcomes (e.g. Energy savings for field devices), and discusses practical barriers such as system maintenance and equitable participation. It contributes to emerging hybrid models of sustainability education and participatory technology
Erfahrungsbasiertes Lernen mit VR: Ein immersives Lernszenario zum Wasserkreislauf: Ein forschungsbasierter VR-Ansatz für naturwissenschaftliches Lernen auf der Primastufe
No full textHow to Mitigate Technical Debt in Startups: Extending the Entrepreneurial Software Engineering Model
No full textSeveral software startups fail due to the competitive environment, time constraints, limited financial ressources, and other aspects. To overcome some of these issues, in particular regarding time and finance, startups try to release their software product as quickly as possible. For this, they often cut corners on different aspects of the product, unconsciously accepting technical debt. We argue that startups are often not aware of long-term effects of technical debt and, hence, unconciously accept software- and process-related shortcomings when developing the product. In order to raise the awareness for technical debt and to help startups avoid it, we extend the Entrepreneurial Software Engineering Model grounded in insights from literature. For each software development phase in startups, our extension puts special emphasis on technical debt, e.g., by integrating aspects such as architecture testing and specific quality gates that are often not part of software processes in early stage startups