Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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Objectives and Key Results verstehen und anwenden
No full textDieses essential gibt eine strukturierte und kompakte Einführung in die Objectives and Key Results-Managementmethode. Es erläutert Herkunft, Definition und Einsatzzweck von Objectives and Key Results (OKR) und beschreibt deren zentrale Bestandteile. Leser:innen erfahren, wie gute Objectives und Key Results formuliert werden und welche Strategien sich zur erfolgreichen Implementierung eignen. Zudem werden praxisrelevante Erfolgs- und Misserfolgsfaktoren analysiert, die den Einsatz von OKR maßgeblich beeinflussen. Ein fundierter Leitfaden für alle, die OKR als Steuerungsinstrument in Organisationen verstehen und wirksam einsetzen möchten
Towards accurate eye tracking: quantifying error in linear pixel-to-degree conversion
No full textEye tracking has become a powerful tool for analyzing cognitive processes in educational research. Educators and researchers can utilize eye tracking to model learners by determining their gaze patterns. In addition, eye tracking can be used directly for teaching by extracting experts' gaze behavior in certain areas and learning from it.
However, eye tracking data is captured in a variety of coordinate systems, which can differ across individual studies. Consequently, algorithms, such as eye movement classifiers, must frequently convert gaze data between different coordinate systems. In particular, the conversion from screen pixels into visual degrees is typically approximated by a linear conversion in current literature and standard practice. However, this approximation introduces inaccuracies, thus potentially obscuring eye movements relevant to educational research.
This paper provides a detailed geometric and analytical examination of the commonly applied linear approximation, quantifying its error in comparison to the exact coordinate conversion from screen pixels to angular degrees. For this purpose, the exact conversion formulas are mathematically derived from geometric optics, enabling researchers and educators to use them in their work. Utilizing these derived transformations can improve the robustness of analyses, for example, when detecting subtle eye movements.
The present work supports educational research using eye tracking to achieve more insightful findings that may have previously been obscured by measurement inaccuracies. Thereby, we provide an important contribution toward more reliable and valid research and educational practices in eye tracking
When algorithms design: a comparative study pits an AI-generated application against a manual application in a competition of user experience and user-friendliness
No full textThe rapid growth of artificial intelligence has enabled automated website creation, including design, content, and SEO. This study compares an AI-generated application with a manually designed one in terms of usability and user experience. Forty-two participants evaluated efficiency, effectiveness, satisfaction, emotional responses, and behavioural patterns. The manual application outperformed the AI-generated one in most datasets, particularly in clarity, supportiveness, and comprehensibility, while speed, learnability, activation, creativity, and security showed no significant differences. Users reported more positive emotions and confident interactions with the manual application, whereas the AI application elicited uncertainty and frustration. These behavioural differences were also reflected in processing times and task completion rates, suggesting that AI-generated solutions currently struggle to meet established UX standards. Nevertheless, the AI builder demonstrated potential for rapid prototyping and low-effort website creation, offering advantages for users with limited technical skills or resources. The findings highlight both the opportunities and limitations of current AI-based web design tools and underline the importance of human-centered design expertise in achieving high-quality user experiences. Despite existing shortcomings, AI-supported tools may become increasingly viable as technology advances
Navigating the DiGA Jungle: A Taxonomy and Archetypal Framework of the German Digital Therapeutics Landscape
No full textDigital therapeutics (DTx) are patient-facing apps designed to support individuals in their daily lives. Therefore, they have thepotential to revolutionize healthcare by empowering and engaging patients to become active players in their own care. Despitethe increasing adoption of DTx in national healthcare systems, research on their design remains limited. The present studyintroduces “DiGATax”, a taxonomy designed to categorize and analyze DTx, including perspectives on content, interventiondelivery logic and technology, as well as the patient’s interface, consolidating and expanding upon prior taxonomic work.Based on n = 44 applications retrieved from the German DiGA directory that demonstrated positive health outcomes, thetaxonomy is supported by empirical evidence. Additionally, the study contributes by presenting an archetype frameworkof DTx derived from a taxonomy-based cluster analysis. Further analyses offer insights into specific combinations of DTxcharacteristics across archetypes, the user interface as a key factor in their acceptance, and potential links between DTxdesign and health-related and user engagement outcomes. By offering new insights into DTx design, this study contributestowards more organized research and reporting, ultimately paving the way for the development of effective solutions. It alsomarks a further step towards Meta-DTx, which aim to align patient care for multimorbid patients under one umbrella
Assessment of technologies and economics for carbon dioxide removal from a portfolio perspective
No full textCarbon dioxide removal (CDR) is essential to achieve ambitious climate goals limiting global warming to less than 1.5◦C, and likely for achieving the 1.5◦C target. This study addresses the need for diverse CDR portfolios and introduces the LUT-CDR tool, which assesses CDR technology portfolios aligned with hypothetical societal preferences. Six scenarios are described, considering global deployment limitations, techno-economic factors, area requirements, technology readiness, and storage security for various CDR options. The results suggest the feasibility of large-scale CDR, potentially removing 500–1750 GtCO2 by 2100 to meet the set climate targets. For a 1.0◦C climate goal, CDR portfolios necessitate 12.0–37.5% more primary energy compared to a scenario without CDR. Remarkably, funding a 1.0◦C target requires only 0.42–0.65% of the projected global gross domestic product. Bioenergy carbon capture and sequestration and rainfall-based afforestation play limited roles, while secure sequestration of captured CO2 via direct air capture, electricity-based carbon sequestration, and desalination-based afforestation emerge as more promising options. The study offers crucial techno-economic
parameters for implementing CDR options in future energy-industry-CDR system analyses and demonstrates the tool’s flexibility through alternative assumptions. It also discusses limitations, sensitivities, potential tradeoffs, and outlines options for future research in the area of large-scale CDR
Factors Influencing Cloud Computing Adoption in Small and Medium-Sized Enterprises: A Systematic Review
No full textThis paper investigates the factors influencing cloud computing adoption in small and medium-sized enterprises (SMEs) through a systematic literature review. The analysis identified twelve key factors influencing the adoption of cloud computing in SMEs. Based on the Technology-Organisation-Environment (TOE) model and the Technology Acceptance Model (TAM), a conceptual framework was developed for future research. The most important factors are cost, organisational readiness, compatibility, relative advantage and top management support. Other influential factors include security, perceived usefulness, firm size, government support, perceived ease of use, vendor support and competitive pressure. The majority of studies were conducted in Asian countries, including developing countries, limiting the generalisability of the findings to SMEs in more developed economies. This research highlights the need for cloud computing solutions that not only reduce costs and ensure high levels of security and privacy, but are also easy to use and integrate. Further research is recommended to explore these factors within SMEs in more developed economies
Investigation of Cognitive-Motor Interference in Dual Tasking
No full textThe transferability of the results to the overall population is limited due to the small sample size, unequal gender distribution, and a low average age. The researchers suspect a subconscious prioritization of the Cognitive Task during Dual Tasking through a division of limited attention resources of the central nervous system.
In general, the findings of this study are closely aligned with the key points of the Central Capacity Sharing Model [1] and the Bottleneck Theory [2]. For future research, it is essential to consider a larger sample size, a more balanced gender distribution, and the inclusion of diverse age groups in order to achieve more reliable results
Morphological effects of input data quantity in AI-powered dental crown design
No full textOBJECTIVES: This retrospective in vitro study evaluated the impact of input data quantity on the morphology of dental crowns generated by AI-based software. The hypothesis suggests that increased input data quantity improves the quality of generated occlusal surfaces.
METHODS: A dataset comprising n=30 patients (11 males, 19 females; age: 22-31 years) was analyzed. Input data was categorized into full dentition (full), quadrant data (quad), and adjacent teeth (adj). AI-based software (Dentbird Crown, Imageworks Inc.) generated crowns for a single lower first molar (36/46). Metrics were proposed to assess the morphology and occlusal relationships of the crowns, with the original tooth as reference.
STATISTICS: Friedman Chi-Square tests, Wilcoxon signed rank tests, Kendall correlation and Fligner-Killeen tests (α = 0.05).
RESULTS: Full and quad groups provided consistent reconstruction quality with no significant differences in morphology and occlusal relationships. The adj group showed significant (p<0.05) morphological deviations and higher reconstruction failure rates compared to the full and quad groups. Correlations (median: 0.19; min-max range: 0.01-0.54) indicate that the proposed metrics capture distinct morphological and functional crown aspects.
CONCLUSION: The software reliably reconstructed crowns with at least quadrant-level input data. Performance declined with reduced input. Full-jaw scans did not enhance accuracy compared to quadrant data.
CLINICAL SIGNIFICANCE: Increased input data quantity can improve the accuracy of AI-based restorations. As a result, prosthodontists benefit from predictable, accurate restoration proposals that reduce the need for digital chairside adjustments as well as manual modifications after fabrication. This streamlines clinical workflows and enhances the quality of restorations. Quadrant-level data has proven sufficient to generate high-quality reconstructions. Further input data did not significantly improve the accuracy of the reconstructions. The proposed metrics enable quantitative assessments of morphological and functional restoration quality, supporting reliable AI-driven workflows
Klimapolitik als neuer Grund für verschärfte globale Armut und Ungleichheiten? – Immanente Zielkonflikte der Agenda 2030
No full textMit der 2015 verabschiedeten sogenannten Agenda 2030 haben sich die 193 Mitglieder der Vereinten Nationen auf 17 globale Ziele verpflichtet, die der Öffentlichkeit unter dem Schlagwort UN-Nachhaltigkeitsziele bekannt sind. Dabei wird im öffentlichen Diskurs kaum registriert, dass die Ziele durchaus in Konflikt zueinander geraten können. So kann die Bekämpfung des Klimawandels zu neuer Armut und Ungleichheit führen. Der Beitrag beleuchtet diese Zusammenhänge, indem mehrere Ebenen der Widersprüchlichkeit herausgearbeitet werden
Nachhaltigkeit im Reallabor Hochschule: eine Social Marketing-Kampagne zur Mitarbeitendensensibilisierung an der OTH Regensburg
No full textNachhaltigkeit als gesellschaftliche Transformationsaufgabe bringt auch für öffentliche Hochschulen neue Verantwortung mit sich. Auch an der Ostbayerischen Technischen Hochschule Regensburg (OTHR) ist Nachhaltigkeit und Klimagerechtigkeit deshalb ein hochschulweites Strategiethema. Im vorliegenden Beitrag wird die Umsetzung und Evaluation einer Social Marketing-Kampagne vorgestellt, durch die Mitarbeitende der OTHR für nachhaltiges Verhalten am Arbeitsplatz sensibilisiert werden sollten. Basierend auf dem Konzept der Reallabor-Forschung sollte durch die Maßnahme gleichzeitig die Partizipation und Mitsprache der Mitarbeitenden gestärkt werden, indem sie Anregungen zur Weiterentwicklung von Maßnahmen zu Nachhaltigkeit auf dem Campus einbringen konnten. Die Kampagne umfasste Poster und Aufkleber mit Hinweisen zu nachhaltigem Handeln am Arbeitsplatz, die Evaluation erfolgte mittels einer standardisierten Online-Befragung der Mitarbeitenden (n = 140) und einer Fokusgruppendiskussion. Die Ergebnisse der Evaluation zeigen unter anderem eine große Akzeptanz von Hinweisen zu Nachhaltigkeit am Arbeitsplatz (83 %), eine hohe Wirksamkeitserwartung bezüglich des eigenen Beitrags zu Nachhaltigkeit (97 %) und selbstberichtete Veränderungen bei Motivation und Verhalten bei ca. einem Drittel der Befragten. Die qualitativen Daten zeigen, dass sich die Mitarbeitenden eine Ausweitung der Maßnahmen zu Nachhaltigkeit an der Hochschule wünschen, an Online-Kommunikation und Schulungen zum Thema interessiert sind und eine stärkere Bewerbung bestehender Aktivitäten und konkretes Feedback auf das eigene nachhaltige Verhalten wünschen (z. B. Höhe der CO2-Einsparung)