@phdthesis{Abel2020, author = {Abel, Johannes}, title = {Politischer Radikalismus innerhalb des Social Web. Eine Analyse g{\"a}ngiger Narrative und diskursiver Strategien rechter Akteure}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8803}, school = {Universit{\"a}t Passau}, pages = {177, XXXIII Seiten}, year = {2020}, abstract = {Ziel der Arbeit ist es, Narrative und diskursive Strategien von politisch rechten Akteuren zu erforschen und aus einer p{\"a}dagogischen Sicht zu bewerten. Der Fokus der Untersuchung wird hierbei auf Kommunikation innerhalb des Social Web gelegt. Zur Bew{\"a}ltigung des Forschungsvorhabens wird als Methode eine Diskursanalyse angewendet. Die Analyse kommt zu dem Ergebnis, dass sowohl die erzeugten Narrative als auch die verwendeten diskursiven Strategien in allen untersuchten diskursiven Arenen starke {\"A}hnlichkeiten aufweisen - unabh{\"a}ngig davon, ob die Arena vorrangig rechtsextreme, rechtsradikale oder rechtspopulistische Tendenzen besitzt. Dies legt den Verdacht nahe, dass ein Großteil der politisch rechte Akteure immer wiederkehrende Narrative verbreiten und diese mit den stets gleichen diskursiven Strategien untermauern, eine klare diskursive Grenze zwischen Rechtsextremismus, Rechtsradikalismus und Rechtspopulismus scheint es nicht zu geben. Dadurch besteht die Gefahr, dass Rechtsextreme Gedanken zunehmend in die Mitte der Gesellschaft vordringen k{\"o}nnen.}, language = {de} } @phdthesis{Alhamzeh2023, author = {Alhamzeh, Alaa}, title = {Language Reasoning by means of Argument Mining and Argument Quality}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-12699}, school = {Universit{\"a}t Passau}, pages = {ix, 154 Seiten}, year = {2023}, abstract = {Understanding of financial data has always been a point of interest for market participants to make better informed decisions. Recently, different cutting edge technologies have been addressed in the Financial Technology (FinTech) domain, including numeracy understanding, opinion mining and financial ocument processing. In this thesis, we are interested in analyzing the arguments of financial experts with the goal of supporting investment decisions. Although various business studies confirm the crucial role of argumentation in financial communications, no work has addressed this problem as a computational argumentation task. In other words, the automatic analysis of arguments. In this regard, this thesis presents contributions in the three essential axes of theory, data, and evaluation to fill the gap between argument mining and financial text. First, we propose a method for determining the structure of the arguments stated by company representatives during the public announcement of their quarterly results and future estimations through earnings conference calls. The proposed scheme is derived from argumentation theory at the micro-structure level of discourse. We further conducted the corresponding annotation study and published the first financial dataset annotated with arguments: FinArg. Moreover, we investigate the question of evaluating the quality of arguments in this financial genre of text. To tackle this challenge, we suggest using two levels of quality metrics, considering both the Natural Language Processing (NLP) literature of argument quality assessment and the financial era peculiarities. Hence, we have also enriched the FinArg data with our quality dimensions to produce the FinArgQuality dataset. In terms of evaluation, we validate the principle of ensemble learning on the argument identification and argument unit classification tasks. We show that combining a traditional machine learning model along with a deep learning one, via an integration model (stacking), improves the overall performance, especially in small dataset settings. In addition, despite the fact that argument mining is mainly a domain dependent task, to this date, the number of studies that tackle the generalization of argument mining models is still relatively small. Therefore, using our stacking approach and in comparison to the transfer learning model of DistilBert, we address and analyze three real-world scenarios concerning the model robustness over completely unseen domains and unseen topics. Furthermore, with the aim of the automatic assessment of argument strength, we have investigated and compared different (refined) versions of Bert-based models that incorporate external knowledge in the decision layer. Consequently, our method outperforms the baseline model by 13 ± 2\% in terms of F1-score through integrating Bert with encoded categorical features. Beyond our theoretical and methodological proposals, our model of argument quality assessment, annotated corpora, and evaluation approaches are publicly available, and can serve as strong baselines for future work in both FinNLP and computational argumentation domains. Hence, directly exploiting this thesis, we proposed to the community, a new task/challenge related to the analysis of financial arguments: FinArg-1, within the framework of the NTCIR-17 conference. We also used our proposals to react to the Touch{\´e} challenge at the CLEF 2021 conference. Our contribution was selected among the «Best of Labs».}, language = {en} } @phdthesis{Ali2011, author = {Ali, Rashid}, title = {Weyl Gr{\"o}bner Basis Cryptosystems}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus-23195}, school = {Universit{\"a}t Passau}, year = {2011}, abstract = {In this thesis, we shall consider a certain class of algebraic cryptosystems called Gr{\"o}bner Basis Cryptosystems. In 1994, Koblitz introduced the Polly Cracker cryptosystem that is based on the theory of Gr{\"o}bner basis in commutative polynomials rings. The security of this cryptosystem relies on the fact that the computation of Gr{\"o}bner basis is, in general, EXPSPACE-hard. Cryptanalysis of these commutative Polly Cracker type cryptosystems is possible by using attacks that do not require the computation of Gr{\"o}bner basis for breaking the system, for example, the attacks based on linear algebra. To secure these (commutative) Gr{\"o}bner basis cryptosystems against various attacks, among others, Ackermann and Kreuzer introduced a general class of Gr{\"o}bner Basis Cryptosystems that are based on the difficulty of computing module Gr{\"o}bner bases over general non-commutative rings. The objective of this research is to describe a special class of such cryptosystems by introducing the Weyl Gr{\"o}bner Basis Cryptosystems. We divide this class of cryptosystems in two parts namely the (left) Weyl Gr{\"o}bner Basis Cryptosystems and Two-Sided Weyl Gr{\"o}bner Basis Cryptosystems. We suggest to use Gr{\"o}bner bases for left and two-sided ideals in Weyl algebras to construct specific instances of such cryptosystems. We analyse the resistance of these cryptosystems to the standard attacks and provide computational evidence that secure Weyl Gr{\"o}bner Basis Cryptosystems can be built using left (resp. two-sided) Gr{\"o}bner bases in Weyl algebras.}, subject = {Gr{\"o}bner-Basis}, language = {en} } @phdthesis{Alsarem2016, author = {Alsarem, Mazen}, title = {Semantic Snippets via Query-Biased Ranking of Linked Data Entities}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-3959}, school = {Universit{\"a}t Passau}, pages = {148 S.}, year = {2016}, abstract = {In our knowledge-driven society, the acquisition and the transfer of knowledge play a principal role. Web search engines are somehow tools for knowledge acquisition and transfer from the web to the user. The search engine results page (SERP) consists mainly of a list of links and snippets (excerpts from the results). The snippets are used to express, as efficiently as possible, the way a web page may be relevant to the query. As an extension of the existing web, the semantic web or "web 3.0" is designed to convert the presently available web of unstructured documents into a web of data consumable by both human and machines. The resulting web of data and the current web of documents coexist and interconnect via multiple mechanisms, such as the embedded structured data, or the automatic annotation. In this thesis, we introduce a new interactive artifact for the SERP: the "Semantic Snippet". Semantic Snippets rely on the coexistence of the two webs to facilitate the transfer of knowledge to the user thanks to a semantic contextualization of the user's information need. It makes apparent the relationships between the information need and the most relevant entities present in the web page. The generation of semantic snippets is mainly based on the automatic annotation of the LOD1's entities in web pages. The annotated entities have different level of impor- tance, usefulness and relevance. Even with state of the art solutions for the automatic annotations of LOD entities within web pages, there is still a lot of noise in the form of erroneous or off-topic annotations. Therefore, we propose a query-biased algorithm (LDRANK) for the ranking of these entities. LDRANK adopts a strategy based on the linear consensual combination of several sources of prior knowledge (any form of con- textual knowledge, like the textual descriptions for the nodes of the graph) to modify a PageRank-like algorithm. For generating semantic snippets, we use LDRANK to find the more relevant entities in the web page. Then, we use a supervised learning algorithm to link each selected entity to excerpts from the web page that highlight the relationship between the entity and the original information need. In order to evaluate our semantic snippets, we integrate them in ENsEN (Enhanced Search Engine), a software system that enhances the SERP with semantic snippets. Finally, we use crowdsourcing to evaluate the usefulness and the efficiency of ENsEN.}, subject = {World Wide Web 3.0}, language = {en} } @phdthesis{Alshawish2021, author = {Alshawish, Ali}, title = {Risk-based Security Management in Critical Infrastructure Organizations}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-10026}, school = {Universit{\"a}t Passau}, pages = {xii, 181 Seiten}, year = {2021}, abstract = {Critical infrastructure and contemporary business organizations are experiencing an ongoing paradigm shift of business towards more collaboration and agility. On the one hand, this shift seeks to enhance business efficiency, coordinate large-scale distribution operations, and manage complex supply chains. But, on the other hand, it makes traditional security practices such as firewalls and other perimeter defenses insufficient. Therefore, concerns over risks like terrorism, crime, and business revenue loss increasingly impose the need for enhancing and managing security within the boundaries of these systems so that unwanted incidents (e.g., potential intrusions) can still be detected with higher probabilities. To this end, critical infrastructure organizations step up their efforts to investigate new possibilities for actively engaging in situational awareness practices to ensure a high level of persistent monitoring as well as on-site observation. Compliance with security standards is necessary to ensure that organizations meet regulatory requirements mostly shaped by a set of best practices. Nevertheless, it does not necessarily result in a coherent security strategy that considers the different aims and practical constraints of each organization. In this regard, there is an increasingly growing demand for risk-based security management approaches that enable critical infrastructures to focus their efforts on mitigating the risks to which they are exposed. Broadly speaking, security management involves the identification, assessment, and evaluation of long-term (or overall) objectives and interests as well as the means of achieving them. Due to the critical role of such systems, their decision-makers tend to enhance the system resilience against very unpleasant outcomes and severe consequences. That is, they seek to avoid decision options associated with likely extreme risks in the first place. Practically speaking, this risk attitude can significantly influence the decision-making process in such critical organizations. Towards incorporating the aversion to extreme risks into security management decisions, this thesis investigates thoroughly the capabilities of a recently emerged theory of games with payoffs that are probability distributions. Unlike traditional optimization techniques, this theory provides an alternative decision technique that is more robust to extreme risks and uncertainty. Furthermore, this thesis proposes a new method that gives a decision maker more control over the decision-making process through defining loss regions with different importance levels according to people's risk attitudes. In this way, the static decision analysis used in the distribution-valued games is transformed into a dynamic process to adapt to different subjective risk attitudes or account for future changes in the decision caused by a learning process or other changes in the context. Throughout their different parts, this thesis shows how theoretical models, simulation, and risk assessment models can be combined into practical solutions. In this context, it deals with three facets of security management: allocating limited security resources, prioritizing security actions, and tweaking decision making. Finally, the author discusses experiences and limitations distilled from this research and from investigating the new theory of games, which can be taken into account in future approaches.}, subject = {Spieltheorie}, language = {en} } @phdthesis{Alyousef2021, author = {Alyousef, Ammar}, title = {E-Mobility Management: Towards a Grid-friendly Smart Charging Solution}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-9302}, school = {Universit{\"a}t Passau}, pages = {xvii, 159 Seiten}, year = {2021}, abstract = {Replacing fossil-fueled vehicles with Electric Vehicles (EVs) poses new challenges for power distribution networks. Specifically speaking, the electrification of the mobility sector relies on the ability to process and analyze information on when, where, for how long, or how fast charging processes will take place. Nevertheless, such kind of information is typically difficult to acquire or insufficiently predictable due to the dynamic nature of the system. Also, the increasing adoption rate of the renewable energy sources, specifically the domestic Photovoltaic (PV) systems, and the potentially associated grid defection scenarios will significantly impact the cost and efforts required to operate the grid in terms of power quality and demand-supply aspects. However, such emerging requirements have arguably not been taken into account when the distribution grid was built originally. Besides, expanding the distribution and transmission capacity is a very costly and lengthy process. Therefore, any proposed solution should be cost-effective as well as environment-, grid- and user-friendly. To this end, the advancements in Information and Communications Technology (ICT) are increasingly adopted and applied. This thesis addresses the rapidly growing EV sector and deals with the problems to overcome potential power quality degradation caused by the challenges mentioned above. Since time switch and radio ripple control as existing solutions in Germany are costly and neither very effective nor scalable as it requires hardware retrofitting of existing public Charging Stations (CSs), the primary focus of this work is the development of an appropriate, standards-based, scalable, and smart charging solution of EVs. Such a solution can, in turn, boost the usage of renewable energy by ensuring that the existing grid infrastructure can operate within its permissible limits while maintaining acceptable levels of power quality. This work introduces a new definition of the concept, "grid-friendly EV charging", where the power demand of a CS is adjusted depending on the real-time status of a power grid. In this regard, the conflicting concerns of stakeholders in an EV ecosystem are considered. For example, a Distribution System Operator (DSO) does not want to reveal a lot of technical details about the power grid or its status. Similarly, a Charging Service Provider (CSP) wants to keep its clients happy without sharing the details of its business model with others, namely, DSOs. For that sake, a distributed smart charging architecture is proposed in this thesis. It is event-driven and responds in nearly real-time to unforeseen and critical grid situations such as high/low voltage, congestion, phase unbalance, and harmonics. In that regard, the publish/subscribe messaging pattern, used as a part of the architecture, enables an efficient and well-performing communication scheme among the different components. Moreover, an indication mechanism about the different issues in a power grid is developed; it adopts the traffic light model. It works as a black box to separate smart controllers for each CS and configured only by the CSP. Smart chargers enable a smooth adjustment of the charging power to avoid drastic changes in the grid state. To that end, two types of intelligent controllers are developed and tested. While the first controller is inspired by the fuzzy logic, the second one is inspired by the slow-start mechanism used in TCP to control congestion in computer networks. A simulative approach is applied to evaluate the solution, thereby, a topology of a real low voltage grid with realistic load and generation profiles is used. Furthermore, a set of metrics is defined regarding the main concerns of stakeholders: voltage, overloading, fairness, the satisfaction of EV users and grid operator, as well as the grid-friendly behavior of a CS/ EV user. The evaluation shows that the solution is able to guarantee a safe operation of the grid. The proposed system can ensure a grid-friendly charging by sacrificing of a small portion of user satisfaction, that sacrifice of a user is awarded via a points-based reward system. Last but not least, the proposed distributed controllers are compared to two other controllers: (1) a decentralized controller based only on sensing the local voltage and (2) a very strict centralized controller focusing on grid-friendliness. The latter ensures proportional fairness among users regarding the objective function of the optimization problem solved in each simulation step. The distributed controllers are superior to the decentralized controller in terms of grid friendly and fairness and converge in general to the centralized one.}, subject = {Elektromobilit{\"a}t}, language = {en} } @article{AnagnostopoulosTeymuriSeratietal.2023, author = {Anagnostopoulos, Nikolaos Athanasios and Teymuri, Benyamin and Serati, Reza and Rasti, Mehdi}, title = {LP-MAB: Improving the Energy Efficiency of LoRaWAN Using a Reinforcement-Learning-Based Adaptive Configuration Algorithm}, series = {Sensors}, volume = {23}, journal = {Sensors}, number = {4}, editor = {Xie, Bin and Wang, Ning and Gu, Yi and Stefanidis, Angelos}, publisher = {MDPI}, address = {Basel, Switzerland}, issn = {1424-8220}, doi = {10.3390/s23042363}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-11853}, pages = {22 Seiten}, year = {2023}, abstract = {In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications' range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To evaluate the efficiency of the LoRa Wide-Area Network (LoRaWAN), three criteria can be considered, namely, the Packet Delivery Rate (PDR), Energy Consumption (EC), and coverage area. A set of transmission parameters have to be configured to establish a communication link. These parameters can affect the data rate, noise resistance, receiver sensitivity, and EC. The Adaptive Data Rate (ADR) algorithm is a mechanism to configure the transmission parameters of EDs aiming to improve the PDR. Therefore, we introduce a new algorithm using the Multi-Armed Bandit (MAB) technique, to configure the EDs' transmission parameters in a centralized manner on the Network Server (NS) side, while improving the EC, too. The performance of the proposed algorithm, the Low-Power Multi-Armed Bandit (LP-MAB), is evaluated through simulation results and is compared with other approaches in different scenarios. The simulation results indicate that the LP-MAB's EC outperforms other algorithms while maintaining a relatively high PDR in various circumstances.}, language = {en} } @phdthesis{Anderl2014, author = {Anderl, Eva}, title = {Three Essays on Analyzing and Managing Online Consumer Behavior}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus-27453}, school = {Universit{\"a}t Passau}, year = {2014}, abstract = {Over the last two decades, the Internet has fundamentally changed the ways firms and consumers interact. The ongoing evolution of the Internet-enabled market environment entails new challenges for marketing research and practice, including the emergence of innovative business models, a proliferation of marketing channels, and an unknown wealth of data. This dissertation addresses these issues in three individual essays. Study 1 focuses on business models offering services for free, which have become increasingly prevalent in the online sector. Offering services for free raises new questions for service providers as well as marketing researchers: How do customers of free e-services contribute value without paying? What are the nature and dynamics of nonmonetary value contributions by nonpaying customers? Based on a literature review and depth interviews with senior executives of free e-service providers, Study 1 presents a comprehensive overview of nonmonetary value contributions in the free e-service sector, including not only word of mouth, co-production, and network effects but also attention and data as two new dimensions, which have been disregarded in marketing research. By putting their findings in the context of existing literature on customer value and customer engagement, the authors do not only shed light on the complex processes of value creation in the emerging e-service industry but also advance marketing and service research in general. Studies 2 and 3 investigate the analysis of online multichannel consumer behavior in times of big data. Firms can choose from a plethora of channels to reach consumers on the Internet, such that consumers often use a number of different channels along the customer journey. While the unprecedented availability of individual-level data enables new insights into multichannel consumer behavior, it also makes high demands on the efficiency and scalability of research approaches. Study 2 addresses the challenge of attributing credit to different channels along the customer journey. Because advertisers often do not know to what degree each channel actually contributes to their marketing success, this attribution challenge is of great managerial interest, yet academic approaches to it have not found wide application in practice. To increase practical acceptance, Study 2 introduces a graph-based framework to analyze multichannel online customer path data as first- and higher-order Markov walks. According to a comprehensive set of criteria for attribution models, embracing both scientific rigor and practical applicability, four model variations are evaluated on four, large, real-world data sets from different industries. Results indicate substantial differences to existing heuristics such as "last click wins" and demonstrate that insights into channel effectiveness cannot be generalized from single data sets. The proposed framework offers support to practitioners by facilitating objective budget allocation and improving team decisions and allows for future applications such as real-time bidding. Study 3 investigates how channel usage along the customer journey facilitates inferences on underlying purchase decision processes. To handle increasing complexity and sparse data in online multichannel environments, the author presents a new categorization of online channels and tests the approach on two large clickstream data sets using a proportional hazard model with time-varying covariates. By categorizing channels along the dimensions of contact origin and branded versus generic usage, Study 3 finds meaningful interaction effects between contacts across channel types, corresponding to the theory of choice sets. Including interactions based on the proposed categorization significantly improves model fit and outperforms alternative specifications. The results will help retailers gain a better understanding of customers' decision-making progress in an online multichannel environment and help them develop individualized targeting approaches for real-time bidding. Using a variety of methods including qualitative interviews, Markov graphs, and survival models, this dissertation does not only advance knowledge on analyzing and managing online consumer behavior but also adds new perspectives to marketing and service research in general.}, subject = {Internet}, language = {en} } @phdthesis{Ansah2021, author = {Ansah, Frimpong}, title = {Performance and optimization technologies for software defined industrial networks}, publisher = {Universit{\"a}t Passau}, address = {Passau}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-9002}, school = {Universit{\"a}t Passau}, pages = {xxi, 173 Seiten}, year = {2021}, abstract = {The concept of programmable networks is radically changing the way communication infrastructures are designed, integrated, and operated. Currently, the topic is spearheaded by concepts such as software-defined networking, forwarding and control element separation, and network function virtualization. Notably, software-defined networking has attracted significant attention in telecommunication and data centers and thus already in some production-grade networks. Despite the prevalence of software-defined networking in these domains, industrial networks are yet to see its benefits to encourage adoption. However, the misconceptions around the concept itself, the role of virtualization, and algorithms pose a significant obstacle. Furthermore, the desire to accommodate new services in the automation industry results in a pattern of constantly increasing complexity of industrial networks, which is compounded by the requirement to provide stringent deterministic service guarantees considering characteristically different applications and thus posing a significant challenge for management, configuration, and maintenance as existing solutions are architecturally inflexible. Therefore, the first contribution of this thesis addresses the misconceptions around software-defined networking by providing a comparative analysis of programmable network concepts, detailing where software-defined networks compare with other concepts and how its principles can be leveraged to evolve industrial networks. Armed with the fundamental principles of programmable networks, the second contribution identifies virtualization technologies and proposes novel algorithms to provide varied quality of service guarantees on converged time-sensitive Ethernet networks using software-defined networking concepts. Finally, a performance analysis of a software-defined hybrid deployment solution for control and management of time-sensitive Ethernet networks that integrates proposed novel algorithms is presented as an industrial use-case that enables industrial operators to harness the full potential of time-sensitive networks.}, language = {en} } @phdthesis{Apfler2018, author = {Apfler, Sabine}, title = {Erwerb mathematischer Kompetenzen in der Regelvolksschule}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-5593}, school = {Universit{\"a}t Passau}, pages = {447 Seiten}, year = {2018}, abstract = {Durch die Einf{\"u}hrung der Bildungsstandards{\"u}berpr{\"u}fungen erh{\"a}lt die Frage nach der Kompetenzentwicklung von Kindern einen zentralen Stellenwert in Bildungsangelegenheiten. Lehrkr{\"a}fte stehen dadurch vor der Aufgabe, ihren Unterricht diesbez{\"u}glich zu ver{\"a}ndern und L{\"o}sungen zu finden. Die Frage, ob der Einsatz der Montessorip{\"a}dagogik die Entwicklung mathematischer Kompetenzen positiv beeinflusst, wurde im Rahmen einer Dissertation diskutiert und empirisch erforscht werden. Der Arbeit liegt folgende Fragestellung zugrunde: Kann die Montessorip{\"a}dagogik dazu beitragen, dass Sch{\"u}lerinnen und Sch{\"u}ler in {\"o}sterreichischen Regelvolksschulen ein hohes Kompetenzniveau in Mathematik erreichen? Wie unterscheidet sich die Kompetenzentwicklung in Klassen, die von Lehrpersonen mit beziehungsweise ohne Montessoriausbildung unterrichtet werden? Bei der vorliegenden Studie handelt es sich um eine L{\"a}ngsschnittuntersuchung mit zwei Testzeitpunkten. Im Sinne einer summativen Evaluation wurden zu Beginn der Untersuchung die Basiskompetenzen mit dem „Entwicklungsorientierten Test zur Erfassung mathematischer Basiskompetenzen ab Schuleintritt (MBK 1+)" analysiert. Am Ende der dritten Schulstufe wurde eine abschließende Bewertung im Rahmen der IKM-Testung des BIFIE vorgenommen, um die Wirksamkeit des Einsatzes der Montessorimethode zu ermitteln. Untersucht wurden 14 Volksschulklassen, die entweder einer Untersuchungsgruppe oder einer Kontrollgruppe zugeordnet wurden. Die Klassen der Untersuchungsgruppe wurden von Lehrpersonen mit Montessori-Diplomausbildung unterrichtet, die Klassen der Kontrollgruppe von Lehrpersonen, die keine Montessoriausbildung absolviert haben. An der Studie nahmen 248 Sch{\"u}lerinnen und Sch{\"u}ler teil. Der Untersuchungszeitraum erstreckte sich {\"u}ber insgesamt drei Schuljahre. Die Ergebnisse der Studie zeigen Tendenzen, dass sich der Einsatz der Montessorip{\"a}dagogik positiv auf die Kompetenzentwicklung der Kinder im Bereich der Mathematik auswirkt.}, subject = {{\"O}sterreich}, language = {de} }