@article{61445, abstract = {{ABSTRACT In recent years, there has been an increasing awareness of the importance of incorporating diversity into research projects, focusing on both how they are conducted and their content. Funding organizations have started to require that research applicants pay attention to inclusion and diversity by considering gender dimensions and other diversity factors in their project plans and ensuring gender equality during execution. Based on an extensive literature research and expert discussions on how to develop and implement diversity strategies in large collaborative research projects, we argue that there is a lack of practical advice in existing literature. Drawing from our own experiences in conceptualizing and implementing a Diversity Program across four universities in Germany, we propose a framework for effectively integrating diversity into collaborative research initiatives across various academic fields.}}, author = {{Lorke, Mariya and Amelung, Rena and Kuchling, Peter and Paaßen, Benjamin and Pein-Hackelbusch, Miriam and Schloots, Franziska Margarete and Schulz, Klara and Nauerth, Annette}}, journal = {{Diversity & Inclusion Research}}, keywords = {{collaborative research projects, diversity strategy, gender equality}}, number = {{4}}, pages = {{e70040}}, title = {{{Development and Implementation of Diversity Programs in Large Collaborative Research Projects: An Example From Germany}}}, doi = {{https://doi.org/10.1002/dvr2.70040}}, volume = {{2}}, year = {{2025}}, } @inproceedings{62818, author = {{Radtke, Sabine}}, editor = {{Belalcazar, Catalina}}, keywords = {{Sports Coaching, Diversity, Intersectionality}}, location = {{Athens}}, number = {{S1}}, pages = {{S4}}, publisher = {{Human Kinetics}}, title = {{{Ethical dilemmas in coaching: Diversity and inclusion and the role of the coach}}}, doi = {{https://doi.org/10.1123/iscj.2025-0112}}, volume = {{12}}, year = {{2025}}, } @article{65163, abstract = {{Dieser Beitrag untersucht aktuelle pädagogische und hermeneutische Ansätze der jüdischen, christlichen und muslimischen Religionspädagogik in Kindertora, Kinderbibel und Kinderkoran. Er betont die Notwendigkeit für Lehrkräfte, sich mit den spezifischen pädagogischen und hermeneutischen Ansätzen der drei monotheistischen Religionen vertraut zu machen, um die didaktischen Heiligen Schriften im Unterricht angemessen nutzen zu können. Beispiele aus dem aktuellen Religionsunterricht zeigen Missverständnisse und Überraschungen auf, die durch unzureichendes Wissen entstehen. Der Artikel hebt die Bedeutung einer jüdischen Identitätsbildung, einer christlichen diversitätssensiblen Perspektive und von muslimischen normativen Diskursen in den verschiedenen Religionspädagogiken hervor und diskutiert die Herausforderungen und Chancen, die mit der Nutzung didaktisierter Heiliger Schriften verbunden sind. }}, author = {{Keuchen, Marion}}, journal = {{TheoWeb. Zeitschrift für Religionspädagogik}}, keywords = {{Heilige Schriften, interreligiöses Lernen, Schrifthermeneutik, Identität, diversitätssensible Religionspädagogik, jüdische Religionspädagogik, muslimische Religionspädagogik, christliche Religionspädagogik, Holy scriptures, interreligious learning, hermeneutics of scripture, identity, diversity-sensitive religious education, Jewish religious education, Muslim religious education, Christian religious education}}, pages = {{224--237}}, title = {{{Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse}}}, doi = {{10.23770/tw0360}}, volume = {{2}}, year = {{2024}}, } @inproceedings{48872, abstract = {{Quality diversity (QD) is a branch of evolutionary computation that gained increasing interest in recent years. The Map-Elites QD approach defines a feature space, i.e., a partition of the search space, and stores the best solution for each cell of this space. We study a simple QD algorithm in the context of pseudo-Boolean optimisation on the "number of ones" feature space, where the ith cell stores the best solution amongst those with a number of ones in [(i - 1)k, ik - 1]. Here k is a granularity parameter 1 {$\leq$} k {$\leq$} n+1. We give a tight bound on the expected time until all cells are covered for arbitrary fitness functions and for all k and analyse the expected optimisation time of QD on OneMax and other problems whose structure aligns favourably with the feature space. On combinatorial problems we show that QD finds a (1 - 1/e)-approximation when maximising any monotone sub-modular function with a single uniform cardinality constraint efficiently. Defining the feature space as the number of connected components of a connected graph, we show that QD finds a minimum spanning tree in expected polynomial time.}}, author = {{Bossek, Jakob and Sudholt, Dirk}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{9798400701191}}, keywords = {{quality diversity, runtime analysis}}, pages = {{1546–1554}}, publisher = {{Association for Computing Machinery}}, title = {{{Runtime Analysis of Quality Diversity Algorithms}}}, doi = {{10.1145/3583131.3590383}}, year = {{2023}}, } @inbook{54428, abstract = {{The article shows using the examples of the novels GRM. Brainfuck by Sibylle Berg and Quality-Land by Marc-Uwe Kling how concepts of diversity can turn into normative ideas about groups. Diversity as a positively valued descriptive category of societies aims to influence ideas about the normality of language and the cultural composition of societies. However, algorithmic systems based on artificial intelligence in particular can contribute to the separation of constructed groups. Quite contrary to the goals of an open and pluralistic society, ruptures in social groups can be strengthened in this way.}}, author = {{Schulte Eickholt, Swen}}, booktitle = {{Germanistik im Wandel 1. Neue Einsichten und Perspektiven in der Literaturwissenschaft}}, editor = {{Cosan, Leyla and Bazarkaya, Onur Kemal and Tekin, Habib}}, keywords = {{diversity, normality, contemporary literature, algorithm, distopia, Diversität, Normalität, Gegenwartsliteratur, Algorithmus, Dystopie}}, pages = {{65--75}}, publisher = {{Logos}}, title = {{{Normative Diversität? Nahe Zukunft bei Sibylle Berg und Marc-Uwe Kling}}}, year = {{2023}}, } @inproceedings{48861, abstract = {{Generating instances of different properties is key to algorithm selection methods that differentiate between the performance of different solvers for a given combinatorial optimization problem. A wide range of methods using evolutionary computation techniques has been introduced in recent years. With this paper, we contribute to this area of research by providing a new approach based on quality diversity (QD) that is able to explore the whole feature space. QD algorithms allow to create solutions of high quality within a given feature space by splitting it up into boxes and improving solution quality within each box. We use our QD approach for the generation of TSP instances to visualize and analyze the variety of instances differentiating various TSP solvers and compare it to instances generated by established approaches from the literature.}}, author = {{Bossek, Jakob and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-9237-2}}, keywords = {{instance features, instance generation, quality diversity, TSP}}, pages = {{186–194}}, publisher = {{Association for Computing Machinery}}, title = {{{Exploring the Feature Space of TSP Instances Using Quality Diversity}}}, doi = {{10.1145/3512290.3528851}}, year = {{2022}}, } @inproceedings{48894, abstract = {{Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.}}, author = {{Nikfarjam, Adel and Neumann, Aneta and Bossek, Jakob and Neumann, Frank}}, booktitle = {{Parallel Problem Solving from Nature (PPSN XVII)}}, editor = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\v sar, Tea}}, isbn = {{978-3-031-14714-2}}, keywords = {{Co-evolutionary algorithms, Evolutionary diversity optimisation, Quality diversity, Traveling thief problem}}, pages = {{237–249}}, publisher = {{Springer International Publishing}}, title = {{{Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem}}}, doi = {{10.1007/978-3-031-14714-2_17}}, year = {{2022}}, } @article{36545, abstract = {{Due to the Corona crisis, German Higher Education Institutions had to close their campuses in March and lecturers had to teach online. To understand how the Corona crisis affected students, first this article explains the structural and social inequalities in the German higher education system, using Tinto's (1975; 1997) student engagement theory. Second, the concept of Bergman-Rosamond et al. (2020) is used to analyze the challenges that Corona has raised for students, including current surveys. We found that the closure of the social space campus (and the Corona crisis as a whole) particularly hit hard those students who had previously been affected by (intersectional) inequality. Therefore, to lessen the specific challenges associated with the ad hoc transition to digital studying, the creation of a digital community of learning can help. We demonstrate how such a community can be created by the example seminar, "Digital practices: an autoethnographic observation". During the seminar, students recorded their digital technology use in a journal, and we analyzed the diary entries using the collaborate autoethnography method. The seminar example shows that this method is well suited for the development of a community of learning as it not only places students in the spotlight but as students work together on a topic they get to know each other, and a basis of trust is created through peer-feedback. Therefore, it was important to have a digital space (in this case Mahara) where the exchange could take place. The continuous insight into the students’ "learning status" enabled the lecturer to promote the learning and provide individual assistance for the students.}}, author = {{Steinhardt, Isabel}}, journal = {{ISA Pedagogy Series}}, keywords = {{Intersectionality, inequality, gender, diversity, higher-education, crisis}}, number = {{1}}, pages = {{42--59}}, publisher = {{International Sociology Association}}, title = {{{Students in the spotlight: Using collaborative autoethnography to build a community of learning in the Corona crisis}}}, volume = {{1}}, year = {{2021}}, } @inproceedings{48853, abstract = {{In practise, it is often desirable to provide the decision-maker with a rich set of diverse solutions of decent quality instead of just a single solution. In this paper we study evolutionary diversity optimization for the knapsack problem (KP). Our goal is to evolve a population of solutions that all have a profit of at least (1 - {$ϵ$}) {$\cdot$} OPT, where OPT is the value of an optimal solution. Furthermore, they should differ in structure with respect to an entropy-based diversity measure. To this end we propose a simple ({$\mu$} + 1)-EA with initial approximate solutions calculated by a well-known FPTAS for the KP. We investigate the effect of different standard mutation operators and introduce biased mutation and crossover which puts strong probability on flipping bits of low and/or high frequency within the population. An experimental study on different instances and settings shows that the proposed mutation operators in most cases perform slightly inferior in the long term, but show strong benefits if the number of function evaluations is severely limited.}}, author = {{Bossek, Jakob and Neumann, Aneta and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-8350-9}}, keywords = {{evolutionary algorithms, evolutionary diversity optimization, knapsack problem, tailored operators}}, pages = {{556–564}}, publisher = {{Association for Computing Machinery}}, title = {{{Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms}}}, doi = {{10.1145/3449639.3459364}}, year = {{2021}}, } @inproceedings{48860, abstract = {{In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization. Theoretical insights into the working principles of baseline evolutionary algorithms for diversity optimization are still rare. In this paper we study the well-known Minimum Spanning Tree problem (MST) in the context of diversity optimization where population diversity is measured by the sum of pairwise edge overlaps. Theoretical results provide insights into the fitness landscape of the MST diversity optimization problem pointing out that even for a population of {$\mu$} = 2 fitness plateaus (of constant length) can be reached, but nevertheless diverse sets can be calculated in polynomial time. We supplement our theoretical results with a series of experiments for the unconstrained and constraint case where all solutions need to fulfill a minimal quality threshold. Our results show that a simple ({$\mu$} + 1)-EA can effectively compute a diversified population of spanning trees of high quality.}}, author = {{Bossek, Jakob and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-8350-9}}, keywords = {{evolutionary algorithms, evolutionary diversity optimization, minimum spanning tree, runtime analysis}}, pages = {{198–206}}, publisher = {{Association for Computing Machinery}}, title = {{{Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem}}}, doi = {{10.1145/3449639.3459363}}, year = {{2021}}, } @inproceedings{48893, abstract = {{Computing diverse sets of high-quality solutions has gained increasing attention among the evolutionary computation community in recent years. It allows practitioners to choose from a set of high-quality alternatives. In this paper, we employ a population diversity measure, called the high-order entropy measure, in an evolutionary algorithm to compute a diverse set of high-quality solutions for the Traveling Salesperson Problem. In contrast to previous studies, our approach allows diversifying segments of tours containing several edges based on the entropy measure. We examine the resulting evolutionary diversity optimisation approach precisely in terms of the final set of solutions and theoretical properties. Experimental results show significant improvements compared to a recently proposed edge-based diversity optimisation approach when working with a large population of solutions or long segments.}}, author = {{Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-8350-9}}, keywords = {{evolutionary algorithms, evolutionary diversity optimisation, high-order entropy, traveling salesperson problem}}, pages = {{600–608}}, publisher = {{Association for Computing Machinery}}, title = {{{Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem}}}, doi = {{10.1145/3449639.3459384}}, year = {{2021}}, } @inproceedings{48891, abstract = {{Submodular functions allow to model many real-world optimisation problems. This paper introduces approaches for computing diverse sets of high quality solutions for submodular optimisation problems with uniform and knapsack constraints. We first present diversifying greedy sampling approaches and analyse them with respect to the diversity measured by entropy and the approximation quality of the obtained solutions. Afterwards, we introduce an evolutionary diversity optimisation (EDO) approach to further improve diversity of the set of solutions. We carry out experimental investigations on popular submodular benchmark problems and analyse trade-offs in terms of solution quality and diversity of the resulting solution sets.}}, author = {{Neumann, Aneta and Bossek, Jakob and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-8350-9}}, keywords = {{evolutionary algorithms, evolutionary diversity optimisation, sub-modular functions}}, pages = {{261–269}}, publisher = {{Association for Computing Machinery}}, title = {{{Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions}}}, doi = {{10.1145/3449639.3459385}}, year = {{2021}}, } @inbook{48892, abstract = {{Evolutionary algorithms based on edge assembly crossover (EAX) constitute some of the best performing incomplete solvers for the well-known traveling salesperson problem (TSP). Often, it is desirable to compute not just a single solution for a given problem, but a diverse set of high quality solutions from which a decision maker can choose one for implementation. Currently, there are only a few approaches for computing a diverse solution set for the TSP. Furthermore, almost all of them assume that the optimal solution is known. In this paper, we introduce evolutionary diversity optimisation (EDO) approaches for the TSP that find a diverse set of tours when the optimal tour is known or unknown. We show how to adopt EAX to not only find a high-quality solution but also to maximise the diversity of the population. The resulting EAX-based EDO approach, termed EAX-EDO is capable of obtaining diverse high-quality tours when the optimal solution for the TSP is known or unknown. A comparison to existing approaches shows that they are clearly outperformed by EAX-EDO.}}, author = {{Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}}, booktitle = {{Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms}}, isbn = {{978-1-4503-8352-3}}, keywords = {{edge assembly crossover (EAX), evolutionary algorithms, evolutionary diversity optimisation (EDO), traveling salesperson problem (TSP)}}, pages = {{1–11}}, publisher = {{Association for Computing Machinery}}, title = {{{Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation}}}, year = {{2021}}, } @inproceedings{48879, abstract = {{Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this area of research by examining evolutionary diversity optimisation approaches for the classical Traveling Salesperson Problem (TSP). We study the impact of using different diversity measures for a given set of tours and the ability of evolutionary algorithms to obtain a diverse set of high quality solutions when adopting these measures. Our studies show that a large variety of diverse high quality tours can be achieved by using our approaches. Furthermore, we compare our approaches in terms of theoretical properties and the final set of tours obtained by the evolutionary diversity optimisation algorithm.}}, author = {{Do, Anh Viet and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-7128-5}}, keywords = {{diversity maximisation, evolutionary algorithms, travelling salesperson problem}}, pages = {{681–689}}, publisher = {{Association for Computing Machinery}}, title = {{{Evolving Diverse Sets of Tours for the Travelling Salesperson Problem}}}, doi = {{10.1145/3377930.3389844}}, year = {{2020}}, } @article{15493, author = {{Hagengruber, Ruth Edith}}, issn = {{0930-6633}}, journal = {{Konsens}}, keywords = {{Interview, Europe, Women, Diversity}}, pages = {{43--44}}, publisher = {{Deutscher Akademikerinnenbund}}, title = {{{Frauen aus der Mitte Deutschlands}}}, year = {{2019}}, } @article{4690, author = {{Gorbacheva, Elena and Stein, Armin and Schmiedel, Theresa and Müller, Oliver}}, issn = {{18670202}}, journal = {{Business and Information Systems Engineering}}, keywords = {{BPM workforce, Business process management, Competences, Gender diversity, Latent semantic analysis, Skills, Text mining}}, number = {{3}}, pages = {{213----231}}, title = {{{The Role of Gender in Business Process Management Competence Supply}}}, doi = {{10.1007/s12599-016-0428-2}}, year = {{2016}}, }