Self-Regulation and Entrepreneurial Learning - Fust, Alexander; Jenert, Tobias
Research on entrepreneurial learning often stresses the role of experience and previous knowledge. We aim to advance this perspective by pointing out the prerequisites and limitations of experience-based forms of learning and by adapting findings from educational psychology to the entrepreneurial context. Developing a model of self-regulated entrepreneurial learning (SREL) we pursue a more process oriented view of entrepreneurial learning in order to explain how learning unfolds in contexts of uncertainty and novelty when relevant experience and knowledge are scarce. The model comprises a planning, a performance and a review phase in order to support entrepreneurs in their learning process. It is suggested how SREL is related to self-efficacy, emotions and cognitive biases.
Keywords: Unternehmertum; lernen

The crucial first year: The development of students' motivation at a Business School-a Mixed Methods Study - Brahm, Taiga; Jenert, Tobias
The transition from school to university can be overwhelming for some students. While students' motivation is considered a strong predictor of performance, the development of motivation during students' transition from high school to university has rarely been investigated. Additionally, little is known about the relation of motivational aspects with other influences on study performance. The present mixed methods study addresses this research gap and examines the development of economics students' study motivation. The longitudinal mixed-method study included three waves of data collected using quantitative surveys and a series of five interviews conducted with 14 first-year students over eight months. Regarding students' development over time, the quantitative analysis showed a gradual decline in students' motivation. However, in the interviews, certain events during the first year were identified as critical incidents demotivating students. These insights into the development of students' motivation at a business school show that concrete incidents influence students' motivational development; thus, they could be transformed by structural changes.
Keywords: motivation; business school; higher education; latent growth curve model; longitudinal study; mixed methods; interview; students

Transition within higher education institutions (HEI): Differences in learning culture (LC) between first-year, bachelor, and master students at a business school - Gebhardt, Anja; Jenert, Tobias
Tertiary education comprises at least two phases, undergraduate and graduate studies. Often, the first year is regarded another, crucial phase where students familiarize with the study environment. It can be hypothesized that students' individual perceptions of learning and studying as well as the pedagogies they experience differ depending on their current study phase. Yet, differences between the phases in HE have rarely been investigated. To capture differences in student experiences in HE comprehensively, Jenert and Gebhardt (2010) have developed a framework describing Learning Culture in HEI. LC comprises a number of constructs on the three levels of the individual student, pedagogical interactions and the organization. The study first aims to quantitatively describe differences in LC between the phases of HE within a university. Based on this analysis, a second goal is to develop a deeper understanding of how students manage the transitions between different phases by applying qualitative research methods.
Keywords: Higher Education; Transitions; Bachelor; Master

Wie kann über DBR die wissenschaftliche und praktische Relevanz der Forschung gesichert werden? - Brahm, Taiga; Jenert, Tobias
Auseinandersetzungen über Forschungsmethodologien haben in den Bildungswissenschaften lange Tradition. Sie werden häufig unversöhnlich und mit Profilierung der Gegensätze geführt. Für uns hängt die Sinnhaftigkeit einer Forschungskonzeption von der Problemstellung und dem Erkenntnisinteresse ab. Dies gilt auch für Design-Based Research (DBR). Dieser Ansatz entstand als Reaktion auf die Kritik an mangelnder praktischer Anwendung von Befunden aus der empirisch-analytischen Lehr-Lernforschung. Als Ergebnis werden Theorien angestrebt, die für die Praxis einen Nutzen bieten und zugleich über die Anwendung in einer singulären Situation hinausgehen. Wir wollen folgenden Fragen nachgehen: Wo liegen die Gemeinsamkeiten, wo die Spezifika von DBR gegenüber bestehenden Methodologien? Wie wird der Generalisierungsanspruch von Theorien innerhalb von DBR verstanden und umgesetzt? Für welche Erkenntnisinteressen eignet sich DBR? Welche Methoden sind für DBR sinnvoll und können wie angewendet werden?
Keywords: design-based research; gestatlungsbasierte Forschung; Erziehungswissenschaft; Design; Mixed Methods

Combination of Service Matching Steps in Consideration of Efficiency and Fuzziness - Gao, Yuan

Cloud Computing Reduces Uncertainties in Quality-of-Service Matching! - Becker, Matthias; Platenius, Marie Christin; Becker, Steffen (Proceedings of the 2nd International Workshop on Cloud Service Brokerage (CSB))
Cloud computing resulted in a continuously growing number of provided software services to be used by consumers. Brokers discover services that fit best to consumers' requirements by matching Qualityof-Service (QoS) properties. In order to negotiate Service-Level Agreements (SLAs), a provider has to determine the provided QoS based on QoS analyses. However, the risk for the provider to violate the SLA is high as the service's actual quality can deviate from the specified QoS due to uncertainties that occur during the provider's quality analysis. In this paper, we discuss current software engineering paradigms like cloud computing and service-oriented computing with respect to the amount of uncertainty they induce into service matching and SLA negotiations. As a result, we explain, why cloud computing reduces such uncertainties.

Certification for Configurable Program Analysis - Jakobs, Marie-Christine; Wehrheim, Heike (Proceedings of the 21st International Symposium on Model Checking of Software (SPIN))
Configurable program analysis (CPA) is a generic concept for the formalization of different software analysis techniques in a single framework. With the tool CPAchecker, this framework allows for an easy configuration and subsequent automatic execution of analysis procedures ranging from data-flow analysis to model checking. The focus of the tool CPAchecker is thus on analysis. In this paper, we study configurability from the point of view of software certification. Certification aims at providing (via a prior analysis) a certificate of correctness for a program which is (a) tamper-proof and (b) more efficient to check for validity than a full analysis. Here, we will show how, given an analysis instance of a CPA, to construct a corresponding sound certification instance, thereby arriving at configurable program certification. We report on experiments with certification based on different analysis techniques, and in particular explain which characteristics of an underlying analysis allow us to design an efficient (in the above (b) sense) certification procedure.

Verändern Medien die Lernkultur? Mögliche Rollen von Technologie zwischen virtuellen und physischen Lernräumen - Jenert, Tobias (Lernumgebungen an der Hochschule. Auf dem Weg zum Campus von morgen)

Budget-restricted utility games with ordered strategic decisions - Drees, Maximilian; Riechers, Sören; Skopalik, Alexander (Proceedings of the 7th International Symposium on Algorithmic Game Theory (SAGT))
We introduce the concept of budget games. Players choose a set of tasks and each task has a certain demand on every resource in the game. Each resource has a budget. If the budget is not enough to satisfy the sum of all demands, it has to be shared between the tasks. We study strategic budget games, where the budget is shared proportionally. We also consider a variant in which the order of the strategic decisions influences the distribution of the budgets. The complexity of the optimal solution as well as existence, complexity and quality of equilibria are analysed. Finally, we show that the time an ordered budget game needs to convergence towards an equilibrium may be exponential.

Brief Announcement: A Model for Multilevel Network Games - Abshoff, Sebastian; Cord-Landwehr, Andreas; Jung, Daniel; Skopalik, Alexander (Proceedings of the 7th International Symposium on Algorithmic Game Theory (SAGT))
Today's networks, like the Internet, do not consist of one but a mixture of several interconnected networks. Each has individual qualities and hence the performance of a network node results from the networks' interplay.We introduce a new game theoretic model capturing the interplay between a high-speed backbone network and a low-speed general purpose network. In our model, n nodes are connected by a static network and each node can decide individually to become a gateway node. A gateway node pays a fixed price for its connection to the high-speed network, but can utilize the high-speed network to gain communication distance 0 to all other gateways. Communication distances in the low-speed network are given by the hop distances. The effective communication distance between any two nodes then is given by the shortest path, which is possibly improved by using gateways as shortcuts.Every node v has the objective to minimize its communication costs, given by the sum (SUM-game) or maximum (MAX-game) of the effective communication distances from v to all other nodes plus a fixed price α > 0, if it decides to be a gateway. For both games and different ranges of α, we study the existence of equilibria, the price of anarchy, and convergence properties of best-response dynamics.

Bounding the Potential Function in Congestion Games and Approximate Pure Nash Equilibria - Feldotto, Matthias; Gairing, Martin; Skopalik, Alexander (Proceedings of the 10th International Conference on Web and Internet Economics (WINE))
In this paper we study the potential function in congestion games. We consider both games with non-decreasing cost functions as well as games with non-increasing utility functions. We show that the value of the potential function $Φ(\sf s)$ of any outcome $\sf s$ of a congestion game approximates the optimum potential value $Φ(\sf s^*)$ by a factor $Ψ_{\mathcal{F}}$ which only depends on the set of cost/utility functions $\mathcal{F}$, and an additive term which is bounded by the sum of the total possible improvements of the players in the outcome $\sf s$. The significance of this result is twofold. On the one hand it provides Price-of-Anarchy-like results with respect to the potential function. On the other hand, we show that these approximations can be used to compute $(1+ε)·Ψ_{\mathcal{F}}$-approximate pure Nash equilibria for congestion games with non-decreasing cost functions. For the special case of polynomial cost functions, this significantly improves the guarantees from Caragiannis et al. [FOCS 2011]. Moreover, our machinery provides the first guarantees for general latency functions.

Viel Neues und doch keine Innovation!?: Fünf Thesen, warum es die Lehrentwicklung an Hochschulen schwer ha - Jenert, Tobias

Change Management in Higher Education Institutions - Brahm, Taiga; Jenert, Tobias

Automated Service Composition: Adaption of the ASTRO Approach - Heldt, Waleri

Approximate pure Nash equilibria in weighted congestion games - Hansknecht, Christoph; Klimm, Max; Skopalik, Alexander (Proceedings of the 17th. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX))
We study the existence of approximate pure Nash equilibria in weighted congestion games and develop techniques to obtain approximate potential functions that prove the existence of alpha-approximate pure Nash equilibria and the convergence of alpha-improvement steps. Specifically, we show how to obtain upper bounds for approximation factor alpha for a given class of cost functions. For example for concave cost functions the factor is at most 3/2, for quadratic cost functions it is at most 4/3, and for polynomial cost functions of maximal degree d it is at at most d + 1. For games with two players we obtain tight bounds which are as small as for example 1.054 in the case of quadratic cost functions.

Approximate pure Nash equilibria in Social Context Congestion Games - Gairing, Martin; Kotsialou, Grammateia; Skopalik, Alexander (Proceedings of the 10th International Conference on Web and Internet Economics (WINE))
We study the existence of approximate pure Nash equilibriain social context congestion games. For any given set of allowed costfunctions F, we provide a threshold value μ(F), and show that for theclass of social context congestion games with cost functions from F, α-Nash dynamics are guaranteed to converge to α-approximate pure Nashequilibrium if and only if α > μ(F).Interestingly, μ(F) is related and always upper bounded by Roughgarden’sanarchy value [19].

Applying Reinforcement Learning for Resolving Ambiguity in Service Composition - Jungmann, Alexander; Mohr, Felix; Kleinjohann, Bernd (Proceedings of the 7th International Conference on Service Oriented Computing and Applications (SOCA))
Automatically composing service-based software solutionsis still a challenging task. Functional as well as nonfunctionalproperties have to be considered in order to satisfyindividual user requests. Regarding non-functional properties,the composition process can be modeled as optimization problemand solved accordingly. Functional properties, in turn, can bedescribed by means of a formal specification language. Statespacebased planning approaches can then be applied to solvethe underlying composition problem. However, depending on theexpressiveness of the applied formalism and the completenessof the functional descriptions, formally equivalent services maystill differ with respect to their implemented functionality. As aconsequence, the most appropriate solution for a desired functionalitycan hardly be determined without considering additionalinformation. In this paper, we demonstrate how to overcome thislack of information by means of Reinforcement Learning. Inorder to resolve ambiguity, we expand state-space based servicecomposition by a recommendation mechanism that supportsdecision-making beyond formal specifications. The recommendationmechanism adjusts its recommendation strategy basedon feedback from previous composition runs. Image processingserves as case study. Experimental results show the benefit of ourproposed solution.

Anticipatory Power Cycling of Mobile Network Equipment for High-Demand Multimedia Traffic - Dreimann, Philipp

Algorithmic Aspects of Resource Management in the Cloud - Kniesburges, Sebastian; Markarian, Christine; Meyer auf der Heide, Friedhelm; Scheideler, Christian (Proceedings of the 21st International Colloquium on Structural Information and Communication Complexity (SIROCCO))
In this survey article, we discuss two algorithmic research areas that emerge from problems that arise when resources are offered in the cloud. The first area, online leasing, captures problems arising from the fact that resources in the cloud are not bought, but leased by cloud vendors. The second area, Distributed Storage Systems, deals with problems arising from so-called cloud federations, i.e., when several cloud providers are needed to fulfill a given task.

Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models - Beran, Jan; Feng, Yuanhua; Ghosh, Sucharita (Statistical Papers)