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How Technological Advancements and Digitalization Impact Both Organizational Behavior and Work Structures
No full textOrganizations are in a constant state of flux, making transformations an inevitable aspect of their evolution and adaptation (By, 2005; Kotter, 1995). Transformations in organizations take many forms. These include sustainability transformations intended to make organizations more sustainable and fit for the future (Bansal, 2005; Corbett & Mellouli, 2017; Kim et al., 2017; Robertson & Barling, 2013). Additionally, transformations can affect day-to-day work and impact working practices (Orlikowski, 2002; Watson-Manheim et al., 2002, 2012). On the one hand, this enables more flexible working conditions through the introduction of hybrid work, for instance (Halford, 2005). On the other hand, new digital transformations, such as platform work (Deng et al., 2016; Deng & Joshi, 2016; Kittur et al., 2013; Kost et al., 2018), allow organizations to outsource work. Platform work allows users to work completely flexibly and organize their working day according to their needs (Deng et al., 2016; Deng & Joshi, 2016; Kost et al., 2018). A distinction can be made between different types of platforms. There are platforms that require physical labor, such as Uber (Duggan et al., 2020; Möhlmann et al., 2021), where transportation trips can be booked, or DoorDash, where food is delivered (Griesbach et al., 2019). Furthermore, there are entirely virtual online platforms. These include freelancing platforms such as Topcoder or Upwork, where workers advertise their profiles for jobs such as web design (Howcroft & Bergvall-Kåreborn, 2019; Shafiei Gol et al., 2019; Taylor & Joshi, 2019). They are evaluated by their clients and paid according to their work performance. There is also another type of platform with very low entry barriers: micro-task crowdsourcing platforms (Bush & Balven, 2021; Deng et al., 2016; Deng & Joshi, 2016; Wong et al., 2020). Here, people can perform currently posted tasks without prior application and receive a small remuneration (Deng et al., 2016).
Digital transformations in the workplace change work processes and practices in the long term (Carroll et al., 2023). For instance, the introduction of hybrid work allows employees to divide their working time between the office and remote locations (Halford, 2005). Studies have shown that this shift has not negatively impacted employee performance, but has actually improved it (Abdullah et al., 2020; Mann & Holdsworth, 2003; Wessel et al., 2021). Thanks to the gain in flexibility, employees are at least as productive as in mere office work. However, this can also have negative effects, for example on the training of new employees or on maintaining social contacts among colleagues (Hafermalz & Riemer, 2020; Weritz et al., 2022).
Another transformation changing organizations, particularly day-to-day work, is the introduction of artificial intelligence (AI) (Strich et al., 2021). AI encompasses a range of technologies that aim to mimic human cognitive processes or learn independently to solve problems (Asatiani, Malo, et al., 2021; Benbya et al., 2021; Berente et al., 2021). AI differs from previous technologies in terms of its self-learning nature, its (partial) autonomy in decision-making, and its opacity (Asatiani, Malo, et al., 2021; Barredo Arrieta et al., 2020). A special type of AI in use is generative AI (GAI). GAI is a model capable of creating apparently new content such as texts, codes, images, etc. (Brynjolfsson et al., 2023; Susarla et al., 2023). GAI applications like ChatGPT and Bard have quickly gained a large user base due to their easy accessibility, applicability, and versatility (Alavi et al., 2024; Kowalczyk et al., 2023). In addition to private use, GAI is utilized in various work processes across different professions (Benbya et al., 2024; Brynjolfsson et al., 2023), benefiting employees and organizations by improving the quality and efficiency of work (Brynjolfsson et al., 2023; Jia et al., 2024).
In my dissertation, I explore these various types of transformation. Thereby, I contribute to a dynamic field and demonstrate how transformations in organizations can have a lasting impact on work processes. I have approached this multifaceted topic in a total of four studies
Supporting Primary School Programming Education through Formative Feedback
No full textChildren are increasingly surrounded by computer science aspects in their everyday life. Primary school education aims at empowering children to participate in and reflect on their environment. Therefore, computer science related contents such as programming are increasingly introduced into primary school curricula. However, this also involves challenges in particular for teachers, who need to familiarise themselves with the new curriculum. As a result, primary school teachers often struggle to help primary school children with their programming issues. Corrective feedback given during the learning process (i. e. formative feedback) can help by promoting cognitive factors such as content knowledge. This thesis therefore aims to support primary school programming education through formative feedback.
In order to shed light on different perspectives, both teachers and children participated in the studies in a mixed methods design. Teachers’ challenges and children’s programming issues were explored as a basis for knowing what both target groups struggle with. This was done by conducting content analysis on the challenges and issues collected and using the resulting categories for further quantitative analysis. The effects of different characteristics of feedback on the effectiveness and efficiency of teaching and learning programming were then explained. This was done by asking the teachers and children to explain their ratings and conducting content analysis on their explanations.
The support of primary school programming education through formative feedback builds on the major challenge of teachers’ lack of content knowledge and the corresponding strategies of teacher training and automated feedback. Indeed, automated feedback was found to be mostly helpful for debugging and task creation. In order to provide direct support to children, common programming issues were identified in terms of the understanding of programming concepts and the usage of the programming environment. Effects on children’s learning and their preferences were identified for several feedback characteristics, leading for example to elaborated hints instead of simple direct instructions. Based on these results, a formative feedback approach of hint cards was developed and evaluated. The hint cards approach proved to be a useful example strategy for supporting primary school programming education through formative feedback.Kinder sind in ihrem Alltag zunehmend von informatischen Phänomenen umgeben. Die Grundschulbildung zielt darauf ab, Kinder zu befähigen, an ihrer Umwelt teilzuhaben und sie zu reflektieren. Daher werden informatikbezogene Inhalte wie das Programmieren zunehmend in die Lehrpläne der Grundschulen aufgenommen. Dies bringt jedoch auch Herausforderungen mit sich, insbesondere für die Lehrkräfte, die sich mit dem neuen Lehrplan und Ansätzen vertraut machen müssen. Infolgedessen fällt es Grundschullehrkräften oft schwer, Grundschulkindern bei ihren Programmierproblemen zu helfen. Korrektives Feedback, das während des Lernprozesses gegeben wird (formatives Feedback), kann helfen, indem es kognitive Faktoren wie fachliches Wissen fördert. Ziel dieser Arbeit ist es daher, den Programmierunterricht in der Grundschule durch formatives Feedback zu unterstützen.
Um die unterschiedlichen Perspektiven zu beleuchten, nahmen sowohl Lehrkräfte als auch Kinder an den Studien in einem Mixed Methods-Design teil. Die Herausforderungen der Lehrkräfte und die Schwierigkeiten der Kinder bei der Programmierung wurden exploriert, um zu erfahren, womit beide Zielgruppen Probleme haben. Dazu wurden die gesammelten Herausforderungen und Probleme einer qualitativen Inhaltsanalyse unterzogen und die daraus resultierenden Kategorien für eine weitere quantitative Analyse verwendet. Außerdem wurden die Auswirkungen verschiedener Merkmale des Feedbacks auf die Effektivität und Effizienz des Lehrens und Lernens von Programmierkonzepten erklärt. Dazu erläuterten die Lehrkräfte und Kinder ihre Bewertungen und ihre Erläuterungen wurden einer qualitativen Inhaltsanalyse unterzogen.
Die Unterstützung des Programmierunterrichts in der Grundschule durch formatives Feedback baut auf der großen Herausforderung des fehlenden fachlichen Wissens der Lehrkräfte und den entsprechenden Strategien der Lehrkräftebildung und des automatischen Feedbacks auf. Das automatische Feedback erwies sich beim Debugging und bei der Erstellung von Aufgaben als hilfreich. Um die Kinder direkt zu unterstützen, wurden allgemeine Programmierprobleme in Bezug auf das Verständnis von Programmierkonzepten und die Nutzung der Programmierumgebung ermittelt. Es wurden Auswirkungen auf das Lernen der Kinder und ihre Präferenzen für verschiedene Feedback-Merkmale ermittelt, was beispielsweise in elaborierten Hinweisen anstelle einfacher direkter Anweisungen resultiert. Auf der Grundlage dieser Ergebnisse wurde ein formatives Feedbackkonzept mit Hinweiskärtchen entwickelt und evaluiert. Dieses Konzept erwies sich als nützliche Strategie zur Unterstützung des Programmierunterrichts in der Grundschule durch formatives Feedback
Structure of Artificial Neural Networks : Empirical Investigations
No full textWithin one decade, Deep Learning overtook the dominating solution methods of countless problems of artificial intelligence.
"Deep" refers to the deep architectures with operations in manifolds of which there are no immediate observations.
For these deep architectures some kind of structure is pre-defined -- but what is this structure?
With a formal definition for structures of neural networks, neural architecture search problems and solution methods can be formulated under a common framework.
Both practical and theoretical questions arise from closing the gap between applied neural architecture search and learning theory.
Does structure make a difference or can it be chosen arbitrarily?
This work is concerned with deep structures of artificial neural networks and examines automatic construction methods under empirical principles to shed light on to the so called ``black-box models''.
Our contributions include a formulation of graph-induced neural networks that is used to pose optimisation problems for neural architecture.
We analyse structural properties for different neural network objectives such as correctness, robustness or energy consumption and discuss how structure affects them.
Selected automation methods for neural architecture optimisation problems are discussed and empirically analysed.
With the insights gained from formalising graph-induced neural networks, analysing structural properties and comparing the applicability of neural architecture search methods qualitatively and quantitatively we advance these methods in two ways.
First, new predictive models are presented for replacing computationally expensive evaluation schemes, and second, new generative models for informed sampling during neural architecture search are analysed and discussed
Gestufte Standards für die Lehrkräftebildung : Kompetenzerwerb unter dem Anspruch von Digitalisierung und Bildung für nachhaltige Entwicklung
No full textINHALTSVERZEICHNIS
Vorwort zur dritten Auflage (1)
Jutta Mägdefrau, Sabrina Kufner, Andreas Eberth & Hannes Birnkammerer:
Gestufte Standards für die Lehrkräftebildung - Kompetenzerwerb unter dem Anspruch von Digitalisierung und Bildung für nachhaltige Entwicklung (4)
1. Intention, Genese und Weiterentwicklung der Passauer Lehrkräftebildungsstandards
2. Integration der Bildung für Nachhaltige Entwicklung in die Standards
3. Einsatz der Standards in der Praxis
Autorengruppe Passauer Lehrerbildungsstandards:
Gestufte Standards für die Lehrkräftebildung (nach Dimensionen) (17)
Dimension 1: Gestaltung der Rolle als Lehrkraft
Dimension 2: Schule als Lern- und Lebensraum
Dimension 2.1: Schule als Organisation
Dimension 2.2: Schulalltag und Schulleben
Dimension 2.3: Unterrichtsbeobachtung und -evaluation
Dimension 2.4: Entwicklung von Schule
Dimension 3: Unterrichtsplanung, -durchführung und -analyse
Dimension 3.1: Struktur von Unterricht
Dimension 3.2: Lehrformen und -theorien
Dimension 3.3: Lernumgebungen gestalten
Dimension 3.4: Zeitmanagement
Dimension 3.5: Planungsmittel
Dimension 3.6: Medieneinsatz
Dimension 3.7: Sozialformen und Methoden
Dimension 3.8: Umgang mit Vielfalt
Dimension 4: Klassenführung
Dimension 5: Lernprozess- und Lernproduktdiagnostik
Dimension 6: Beratung
Gestufte Standards für die Lehrkräftebildung (nach Phasen) (37)
Pädagogisch-Didaktisches Praktikum
Studienbegleitendes Fachdidaktisches Praktikum
Referendariat
Professionelle Lehrkraft
Autor:innengruppe "Standards für die Lehrkräftebildung" (59
Towards Fast and Adaptive Byzantine State Machine Replication for Planetary-Scale Systems
No full textState machine replication (SMR) is a classical approach for building resilient distributed systems. In Byzantine fault-tolerant (BFT) systems, no concrete assumptions are made about the behavior of faulty replicas. With the advancement of distributed ledger technologies (DLT), planetary-scale BFT SMR ist becoming practical and necessary as it can serve as a consensus primitive to keep the ledger consistent. In our view, the alignment of BFT SMR to DLT brings new challenges, for instance the scalability aspect, where recent research works less frequently address latency improvements than throughput improvements. Further challenges include the geographic dispersion of replicas within a planetary-scale system and the need of a BFT SMR protocol to react to environmental changes during runtime.
This thesis has the objective to improve BFT SMR for planetary-scale systems by lowering the protocol latency observed by clients and by making the BFT SMR system adaptive, i.e., enabling replicas to react to perceived changes such as changing network characteristics or faulty replicas.
As a first contribution of this thesis, we discover that fast, consensus-free (read-only) operations is a flawed optimization in seminal BFT SMR frameworks, such as PBFT and BFT-SMaRt. We explain how the read-only optimization can violate the protocol's liveness by showing an attack and then present a solution that makes the overall, optimized protocol both live and linearizable.
The second contribution is Adaptive Wide-Area Replication (AWARE), which enables a geo-replicated system to adapt to its environment, thus improving the geographical scalability of consensus if replicas are dispersed across the world. Essentially, AWARE is an automated and dynamic voting-weight tuning and leader positioning scheme, which supports the emergence of fast consensus quorums in the system and builds upon previous work, the WHEAT protocol. AWARE combines reliable self-monitoring with a consensus latency prediction model, thus striving to minimize the system’s consensus latency at runtime, which subsequently results in latency improvements observed by clients scattered across the globe, which we validate through experiments.
The third contribution presents FlashConsensus, a protocol derived from AWARE, that also adjusts the resilience threshold. The core idea is the tentative use of a lower resilience threshold which leads to smaller consensus quorums and thus consensus acceleration in common-case scenarios where we expect only few faulty replicas. FlashConsensus achieves threat-level awareness through the incorporation of two modes of operation and BFT forensic support and guarantees liveness and linearizability under optimal resilience. Moreover, FlashConsensus allows for client-side speculation by using incremental consistency guarantees to further lower request latency.
Additionally, we investigate on the question whether we can reason about the performance of large-scale systems utilizing simulations. We discover, that we can faithfully forecast the performance of BFT protocols by plugging real protocol implementations into a high-performance network simulator. For instance, simulation results reveal that, using 51 replicas scattered across the planet, FlashConsensus can finalize operations in less than 0.4 s, which is half of the time required for a PBFT-like protocol in the same network, and matching the latency of this protocol running on the best possible internet links (transmitting at 67% of the speed of light).Die Zustandsmaschinenreplikation (ZMR) ist ein klassischer Ansatz für zuverlässige verteilte Systeme. In Byzantinischen fehlertoleranten (BFT) Systemen werden keine konkreten Annahmen über das Verhalten von fehlerhaften Replikaten gemacht. Mit dem Voranschreiten der sog. „Distributed Ledger Technologien“ (DLT) wird planetare BFT ZMR praktikabel und notwendig, da sie als Konsensusprimitiv dienen kann, um die Konsistenz einer Blockchain aufrechtzuerhalten. Unserer Ansicht nach bringt die Ausrichtung von BFT ZMR an DLT neue Herausforderungen mit sich, z.B. den Skalierbarkeitsaspekt, bei dem jüngste Forschungsarbeiten seltener Latenzverbesserungen als Durchsatzverbesserungen untersuchen. Weitere Herausforderungen umfassen die geografische Verteilung von Replikaten innerhalb eines planetaren Systems sowie die Notwendigkeit eines BFT ZMR Protokolls während der Laufzeit auf Veränderungen zu reagieren.
Diese Dissertation verfolgt das Ziel, die BFT ZMR für planetare Systeme durch Senkung der von Clients beobachteten Protokolllatenz zu verbessern und die BFT ZMR-Systeme anpassungsfähig zu machen, indem Replikate auf wahrgenommene Änderungen wie sich ändernde Netzwerkcharakteristiken oder fehlerhafte Replikate reagieren können.
Als erster Beitrag dieser Dissertation zeigen wir, dass schnelle, konsensusfreie (nur-lesende) Operationen in grundlegenden BFT ZMR Protokollen, wie PBFT und BFT-SMaRt, eine fehlerhafte Optimierung sind. Wir erklären, wie die nur-lesende Optimierung die Liveness (Verfügbarkeit von Operationen) des Protokolls verletzen kann, indem wir einen Angriff präsentieren und dann eine Lösung vorschlagen, die das insgesamt optimierte Protokoll sowohl live (verfügbar) als auch linearisierbar („linearizable“ -- streng konsistent) macht.
Der zweite Beitrag ist Adaptive Wide-Area Replication (AWARE), mit der ein geo-repliziertes System sich an seine Umgebung anpassen kann und damit die geografische Skalierbarkeit des Konsensus verbessert, wenn Replikate auf der ganzen Welt verteilt sind. Im Wesentlichen ist AWARE ein automatisches und dynamisches Stimmgewichtseinstellungs- und Anführerpositionierungs-schema, das die Entstehung schneller Konsensusquoren im System unterstützt und auf früheren Arbeiten, wie dem WHEAT-Protokoll, aufbaut. AWARE kombiniert zuverlässige Selbstüberwachung mit einem Konsensuslatenzvorhersagemodell und strebt danach, die Konsensuslatenz des Systems zur Laufzeit zu minimieren, was letztendlich zu Latenzgewinnen führt, die von Clients auf der ganzen Welt beobachtbar sind, was wir durch Experimente bestätigen.
Der dritte Beitrag stellt FlashConsensus vor, ein Protokoll, das aus AWARE abgeleitet ist und auch die Resilienzschwelle anpasst. Die Kernidee ist die vorübergehende Verwendung einer niedrigeren Resilienzschwelle, die zu kleineren Konsensusquoren und damit zu einer Beschleunigung des Konsensus in häufigen Fällen führt, in denen nur wenige fehlerhafte Replikate erwartet werden. FlashConsensus erkennt und reagiert auf Bedrohungen durch die Einbeziehung von zwei Betriebsarten und BFT-Forensikunterstützung und garantiert Liveness sowie Konsistenz unter optimaler Resilienz.
Darüber hinaus ermöglicht es die Spekulation auf Clientseite durch die Verwendung inkrementeller Konsistenzgarantien, um die Clientlatenz weiter zu senken. Zusätzlich werden wir uns mit der Frage beschäftigen, ob wir die Performanz von groß-skalierten Systemen mittels Simulationen beurteilen können. Wir stellen fest, dass wir die Performanz von BFT Protokollen durch das Einstöpseln von echten Protokollimplementierungen in einen hochleistungsfähigen Netzwerksimulator zuverlässig vorhersagen können. Beispielsweise zeigen Simulationen, dass FlashConsensus mit 51 Replikaten, die auf der ganzen Welt verteilt sind, Operationen in weniger als 0,4 s linearisierbar verarbeiten kann, was die Hälfte der Zeit ist, die für ein PBFT-ähnliches Protokoll im gleichen Netzwerk erforderlich ist und ähnlich schnell ist wie dieses Protokoll mit bestmöglichen Internetverbindungen (Übertragung mit 67% der Lichtgeschwindigkeit)
Machine learning methods for credit card fraud detection : a survey
No full textThe widespread adoption of online payments has been accompanied by a significant increase in fraudulent activities, resulting in billions of dollars in financial losses. As payment providers aim to tackle this with various preventive mechanisms, fraudsters also continuously evolve their methods to remain indistinguishable from genuine actors. This necessitates sophisticated fraud detection tools to supplement these security mechanisms. As the volume of transactions taking place per day is in the millions, relying solely on human investigation is expensive and ultimately unfeasible, leading to an emergence of research into data driven or statistical methods for fraud detection. Over the last decade, this research has evolved to tackle the various particularities of the domain. These include the skewed nature of the data, the evolving user and fraud behavior, and the learning representations of the context in which a transaction takes place. This work aims to provide the community with an in-depth overview of the different directions in which recent research on online fraud detection has focused. We develop a taxonomy of the domain based on these directions and organize our analysis accordingly. For each area, we focus on significant methodological advancements and highlight limitations or gaps in the current state-of-the-art solutions. Through our analysis, it emerges that one of the primary limiting factors that many researchers face is the lack of availability of high-quality credit card data. Therefore, we provide a first step in addressing this issue in the form of a data generation framework using generative adversarial networks (GANs). We hope that this survey serves as a foundation for researchers who want to address the multi-faceted problem of credit card fraud detection
The Consequences of Evidence- Versus Non-Evidence-Based Understandings of the “Truth”: How Russian Speakers in Germany Negotiate Trust in Their Transnational News Environments
No full textExtant research on migrants’ media use and trust has delivered mixed evidence on whether, and in which ways, migrants stay loyal to their homeland news media and/or develop trust in host-society media, particularly when the narratives of the two types of media clash. To advance this strand of research, this study scrutinizes how an audience group with migration background, who lived the first part of their lives under authoritarian rule but then relocated to a democracy, negotiates trust in their multilingual, transnational news environments. Specifically, we conducted semi-structured interviews with forty-two Russian-speaking first-generation migrants living in Germany in 2021. As we find, distinct understandings of the concept of “truth” played a pivotal role in how our participants negotiated trust in their transnational news environments. We distinguish broadly two understandings of “truth”: (1) “truth” as a category grounded in factual evidence and (2) “truth” as a non-evidence based category grounded in values, emotions, or identities. Illustrative for the second understanding, some participants felt a strong moral obligation to believe Kremlin-sponsored media as they perceived these organizations as representing their homeland, independently of whether their news coverage was factually accurate or not. The two understandings of “truth” also affected how and where participants sought for what they considered the “truth.” In the “Discussion” section, we argue that particularly the non-evidence-based truth-understandings formulated by our participants, and the ensuing truth-seeking strategies are conducive to the reach and persuasive impact of Kremlin-sponsored content among Russian speakers living abroad
Zeitgemässe Methoden der Kinder- und Jugendmedienforschung
No full textMedienPädagogik : Zeitschrift für Theorie und Praxis in der Medienbildung
Themenheft 60: Zeitgemässe Methoden der Kinder- und Jugendmedienforschung
Inhalte:
Malin Fecke, Ada Fehr, Daniela Schlütz
Die Mobile Experience Sampling Methode (MESM) in der Kinder- und Jugendmedienforschung
André Weßel
‹Jeden Abend Instagram, TikTok, YouTube› - Das digitale Medientagebuch als qualitative Forschungsmethode zur Untersuchung des Medienhandelns junger Menschen
Thorsten Naab, Ruth Wendt, Alexandra Langmeyer-Tornier
Messung mütterlicher Medienerziehung für interaktive und nicht-interaktive Medien
Thorsten Naab, Moritz Abraham
Wie ein Spielzeug zum Helfer in Kinderbefragungen werden kann
Sophie Mayen, Anne Reinhardt , Claudia Wilhelm
Instrumente zur Messung von jugendlicher Mediennutzung
Paulina Domdey, Katrin Potzel
Medientagebücher als Teil sequenzieller Triangulation in der qualitativen Forschung
Franziska Koschei, Lena Schmidt, Susanne Eggert, Andreas Dertinger, Michaela Kramer, Rudolf Kammerl
Forschung mit Grundschüler:innen
Jan Pfetsch, Felix Paschel, Cora Bieß, Ingrid Stapf
Forschungsethik und Kinderrecht
Analysing Equilibrium States for Population Diversity
No full textPopulation diversity is crucial in evolutionary algorithms as it helps with global exploration and facilitates the use of crossover. Despite many runtime analyses showing advantages of population diversity, we have no clear picture of how diversity evolves over time. We study how the population diversity of (μ+1)algorithms, measured by the sum of pairwise Hamming distances, evolves in a fitness-neutral environment. We give an exact formula for the drift of population diversity and show that it is driven towards an equilibrium state. Moreover, we bound the expected time for getting close to the equilibrium state. We find that these dynamics, including the location of the equilibrium, are unaffected by surprisingly many algorithmic choices. All unbiased mutation operators with the same expected number of bit flips have the same effect on the expected diversity. Many crossover operators have no effect at all, including all binary unbiased, respectful operators. We review crossover operators from the literature and identify crossovers that are neutral towards the evolution of diversity and crossovers that are not