004 Datenverarbeitung; Informatik
Refine
Year of publication
Document Type
- Article (338)
- Monograph/Edited Volume (166)
- Doctoral Thesis (159)
- Conference Proceeding (54)
- Postprint (50)
- Master's Thesis (10)
- Other (7)
- Preprint (3)
- Part of a Book (2)
- Bachelor Thesis (1)
Language
- English (598)
- German (192)
- Multiple languages (2)
Keywords
- Informatik (21)
- machine learning (19)
- Didaktik (15)
- Hochschuldidaktik (14)
- Ausbildung (13)
- answer set programming (13)
- Cloud Computing (12)
- cloud computing (12)
- Hasso-Plattner-Institut (10)
- maschinelles Lernen (10)
Institute
- Institut für Informatik und Computational Science (271)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (214)
- Hasso-Plattner-Institut für Digital Engineering GmbH (134)
- Extern (65)
- Fachgruppe Betriebswirtschaftslehre (30)
- Mathematisch-Naturwissenschaftliche Fakultät (24)
- Wirtschaftswissenschaften (19)
- Institut für Mathematik (16)
- Bürgerliches Recht (12)
- Institut für Physik und Astronomie (8)
- Digital Engineering Fakultät (7)
- Institut für Umweltwissenschaften und Geographie (6)
- Department Linguistik (5)
- Department Erziehungswissenschaft (4)
- Institut für Biochemie und Biologie (4)
- Department Sport- und Gesundheitswissenschaften (2)
- Sozialwissenschaften (2)
- Öffentliches Recht (2)
- Department Psychologie (1)
- Fachgruppe Politik- & Verwaltungswissenschaft (1)
- Fachgruppe Soziologie (1)
- Fachgruppe Volkswirtschaftslehre (1)
- Institut für Geowissenschaften (1)
- Interdisziplinäres Zentrum für Kognitive Studien (1)
- Kommunalwissenschaftliches Institut (1)
- Lehreinheit für Wirtschafts-Arbeit-Technik (1)
- Potsdam Transfer - Zentrum für Gründung, Innovation, Wissens- und Technologietransfer (1)
- Theodor-Fontane-Archiv (1)
openHPI
(2022)
Anlässlich des 10-jährigen Jubiläums von openHPI informiert dieser technische Bericht über die HPI-MOOC-Plattform einschließlich ihrer Kernfunktionen, Technologie und Architektur.
In einer Einleitung wird die Plattformfamilie mit allen Partnerplattformen vorgestellt; diese belaufen sich inklusive openHPI aktuell auf neun Plattformen. In diesem Abschnitt wird außerdem gezeigt, wie openHPI als Berater und Forschungspartner in verschiedenen Projekten fungiert.
Im zweiten Kapitel werden die Funktionalitäten und gängigen Kursformate der Plattform präsentiert. Die Funktionalitäten sind in Lerner- und Admin-Funktionen unterteilt. Der Bereich Lernerfunktionen bietet detaillierte Informationen zu Leistungsnachweisen, Kursen und den Lernmaterialien, aus denen sich ein Kurs zusammensetzt: Videos, Texte und Quiz. Darüber hinaus können die Lernmaterialien durch externe Übungstools angereichert werden, die über den Standard Learning Tools Interoperability (LTI) mit der HPI MOOC-Plattform kommunizieren. Das Konzept der Peer-Assessments rundet die möglichen Lernmaterialien ab.
Der Abschnitt geht dann weiter auf das Diskussionsforum ein, das einen grundlegenden Unterschied von MOOCs im Vergleich zu traditionellen E-Learning-Angeboten darstellt. Zum Abschluss des Abschnitts folgen eine Beschreibung von Quiz-Recap, Lernzielen, mobilen Anwendungen, spielerischen Lernens und dem Helpdesk.
Der nächste Teil dieses Kapitels beschäftigt sich mit den Admin-Funktionen. Die Funktionalitätsbeschreibung beschränkt sich Neuigkeiten und Ankündigungen, Dashboards und Statistiken, Berichtsfunktionen, Forschungsoptionen mit A/B-Tests, den Kurs-Feed und das TransPipe-Tool zur Unterstützung beim Erstellen von automatischen oder manuellen Untertiteln. Die Plattform unterstützt außerdem eine Vielzahl zusätzlicher Funktionen, doch eine detaillierte Beschreibung dieser Funktionen würde den Rahmen des Berichts sprengen.
Das Kapitel geht dann auf gängige Kursformate und openHPI-Lehrveranstaltungen am HPI ein, bevor es mit einigen Best Practices für die Gestaltung und Durchführung von Kursen schließt.
Zum Abschluss des technischen Berichts gibt das letzte Kapitel eine Zusammenfassung und einen Ausblick auf die Zukunft der digitalen Bildung.
Ein besonderes Merkmal des openHPI-Projekts ist die bewusste Entscheidung, die komplette Anwendung von den physischen Netzwerkkomponenten bis zur Plattformentwicklung eigenständig zu betreiben. Bei der vorliegenden deutschen Variante handelt es sich um eine gekürzte Übersetzung des technischen Berichts 148, bei der kein Einblick in die Technologien und Architektur von openHPI gegeben wird. Interessierte Leser:innen können im technischen Bericht 148 (vollständige englische Version) detaillierte Informationen zum Rechenzentrum und den Geräten, der Cloud-Software und dem openHPI Cloud Service aber auch zu Infrastruktur-Anwendungskomponenten wie Entwicklungstools, Automatisierung, Deployment-Pipeline und Monitoring erhalten. Außerdem finden sich dort weitere Informationen über den Technologiestack und konkrete Implementierungsdetails der Plattform inklusive der serviceorientierten Ruby on Rails-Anwendung, die Kommunikation zwischen den Diensten, öffentliche APIs, sowie Designsystem und -komponenten. Der Abschnitt schließt mit einer Diskussion über die ursprüngliche Microservice-Architektur und die Migration zu einer monolithischen Anwendung.
As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach.
We consider the subset selection problem for function f with constraint bound B that changes over time. Within the area of submodular optimization, various greedy approaches are commonly used. For dynamic environments we observe that the adaptive variants of these greedy approaches are not able to maintain their approximation quality. Investigating the recently introduced POMC Pareto optimization approach, we show that this algorithm efficiently computes a phi=(alpha(f)/2)(1 - 1/e(alpha)f)-approximation, where alpha(f) is the submodularity ratio of f, for each possible constraint bound b <= B. Furthermore, we show that POMC is able to adapt its set of solutions quickly in the case that B increases. Our experimental investigations for the influence maximization in social networks show the advantage of POMC over generalized greedy algorithms. We also consider EAMC, a new evolutionary algorithm with polynomial expected time guarantee to maintain phi approximation ratio, and NSGA-II with two different population sizes as advanced multi-objective optimization algorithm, to demonstrate their challenges in optimizing the maximum coverage problem. Our empirical analysis shows that, within the same number of evaluations, POMC is able to perform as good as NSGA-II under linear constraint, while EAMC performs significantly worse than all considered algorithms in most cases.
Coming back for more
(2022)
Recent spikes in social networking site (SNS) usage times have launched investigations into reasons for excessive SNS usage. Extending research on social factors (i.e., fear of missing out), this study considers the News Feed setup. More specifically, we suggest that the order of the News Feed (chronological vs. algorithmically assembled posts) affects usage behaviors. Against the background of the variable reward schedule, this study hypothesizes that the different orders exert serendipity differently. Serendipity, termed as unexpected lucky encounters with information, resembles variable rewards. Studies have evidenced a relation between variable rewards and excessive behaviors. Similarly, we hypothesize that order-induced serendipitous encounters affect SNS usage times and explore this link in a two-wave survey with an experimental setup (users using either chronological or algorithmic News Feeds). While theoretically extending explanations for increased SNS usage times by considering the News Feed order, practically the study will offer recommendations for relevant stakeholders.
Phone surveys have increasingly become important data collection tools in developing countries, particularly in the context of sudden contact restrictions due to the COVID-19 pandemic. So far, there is limited evidence regarding the potential of the messenger service WhatsApp for remote data collection despite its large global coverage and expanding membership. WhatsApp may offer advantages in terms of reducing panel attrition and cutting survey costs. WhatsApp may offer additional benefits to migration scholars interested in cross-border migration behavior which is notoriously difficult to measure using conventional face-to-face surveys. In this field experiment, we compared the response rates between WhatsApp and interactive voice response (IVR) modes using a sample of 8446 contacts in Senegal and Guinea. At 12%, WhatsApp survey response rates were nearly eight percentage points lower than IVR survey response rates. However, WhatsApp offers higher survey completion rates, substantially lower costs and does not introduce more sample selection bias compared to IVR. We discuss the potential of WhatsApp surveys in low-income contexts and provide practical recommendations for field implementation.
These days design thinking is no longer a “new approach”. Among practitioners, as well as academics, interest in the topic has gathered pace over the last two decades. However, opinions are divided over the longevity of the phenomenon: whether design thinking is merely “old wine in new bottles,” a passing trend, or still evolving as it is being spread to an increasing number of organizations and industries. Despite its growing relevance and the diffusion of design thinking, knowledge on the actual status quo in organizations remains scarce. With a new study, the research team of Prof. Uebernickel and Stefanie Gerken investigates temporal developments and changes in design thinking practices in organizations over the past six years comparing the results of the 2015 “Parts without a whole” study with current practices and future developments. Companies of all sizes and from different parts of the world participated in the survey. The findings from qualitative interviews with experts, i.e., people who have years of knowledge with design thinking, were cross-checked with the results from an exploratory analysis of the survey data. This analysis uncovers significant variances and similarities in how design thinking is interpreted and applied in businesses.
Modeling and Formal Analysis of Meta-Ecosystems with Dynamic Structure using Graph Transformation
(2022)
The dynamics of ecosystems is of crucial importance. Various model-based approaches exist to understand and analyze their internal effects. In this paper, we model the space structure dynamics and ecological dynamics of meta-ecosystems using the formal technique of Graph Transformation (short GT). We build GT models to describe how a meta-ecosystem (modeled as a graph) can evolve over time (modeled by GT rules) and to analyze these GT models with respect to qualitative properties such as the existence of structural stabilities. As a case study, we build three GT models describing the space structure dynamics and ecological dynamics of three different savanna meta-ecosystems. The first GT model considers a savanna meta-ecosystem that is limited in space to two ecosystem patches, whereas the other two GT models consider two savanna meta-ecosystems that are unlimited in the number of ecosystem patches and only differ in one GT rule describing how the space structure of the meta-ecosystem grows. In the first two GT models, the space structure dynamics and ecological dynamics of the meta-ecosystem shows two main structural stabilities: the first one based on grassland-savanna-woodland transitions and the second one based on grassland-desert transitions. The transition between these two structural stabilities is driven by high-intensity fires affecting the tree components. In the third GT model, the GT rule for savanna regeneration induces desertification and therefore a collapse of the meta-ecosystem. We believe that GT models provide a complementary avenue to that of existing approaches to rigorously study ecological phenomena.
The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor's influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn.