@inproceedings{61234,
  abstract     = {{The ability to generate explanations that are understood by explainees is the
quintessence of explainable artificial intelligence. Since understanding
depends on the explainee's background and needs, recent research focused on
co-constructive explanation dialogues, where an explainer continuously monitors
the explainee's understanding and adapts their explanations dynamically. We
investigate the ability of large language models (LLMs) to engage as explainers
in co-constructive explanation dialogues. In particular, we present a user
study in which explainees interact with an LLM in two settings, one of which
involves the LLM being instructed to explain a topic co-constructively. We
evaluate the explainees' understanding before and after the dialogue, as well
as their perception of the LLMs' co-constructive behavior. Our results suggest
that LLMs show some co-constructive behaviors, such as asking verification
questions, that foster the explainees' engagement and can improve understanding
of a topic. However, their ability to effectively monitor the current
understanding and scaffold the explanations accordingly remains limited.}},
  author       = {{Fichtel, Leandra and Spliethöver, Maximilian and Hüllermeier, Eyke and Jimenez, Patricia and Klowait, Nils and Kopp, Stefan and Ngonga Ngomo, Axel-Cyrille and Robrecht, Amelie and Scharlau, Ingrid and Terfloth, Lutz and Vollmer, Anna-Lisa and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue}},
  publisher    = {{Association for Computational Linguistics}},
  title        = {{{Investigating Co-Constructive Behavior of Large Language Models in  Explanation Dialogues}}},
  year         = {{2025}},
}

@inproceedings{59856,
  abstract     = {{Recent advances on instruction fine-tuning have led to the development of various prompting techniques for large language models, such as explicit reasoning steps. However, the success of techniques depends on various parameters, such as the task, language model, and context provided. Finding an effective prompt is, therefore, often a trial-and-error process. Most existing approaches to automatic prompting aim to optimize individual techniques instead of compositions of techniques and their dependence on the input. To fill this gap, we propose an adaptive prompting approach that predicts the optimal prompt composition ad-hoc for a given input. We apply our approach to social bias detection, a highly context-dependent task that requires semantic understanding. We evaluate it with three large language models on three datasets, comparing compositions to individual techniques and other baselines. The results underline the importance of finding an effective prompt composition. Our approach robustly ensures high detection performance, and is best in several settings. Moreover, first experiments on other tasks support its generalizability.}},
  author       = {{Spliethöver, Maximilian and Knebler, Tim and Fumagalli, Fabian and Muschalik, Maximilian and Hammer, Barbara and Hüllermeier, Eyke and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)}},
  editor       = {{Chiruzzo, Luis and Ritter, Alan and Wang, Lu}},
  isbn         = {{979-8-89176-189-6}},
  pages        = {{2421–2449}},
  publisher    = {{Association for Computational Linguistics}},
  title        = {{{Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection}}},
  year         = {{2025}},
}

@article{61241,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Given the presence of fake news and pseudoscience (often disguised as physics), the importance of inoculating citizens against this type of misinformation has gained increasing attention in education. This is a goal that all subjects should pursue equally from their respective disciplinary perspectives. &amp;#xD;The paper presents a teaching approach to protect physics students from misinformation and pseudoscience by combining these three common strategies: First, understanding the fundamental principles of the Nature of Science. Second, identifying techniques of Science Denial. And third, applying heuristics for evaluating (supposedly) scientific information. Finally, the paper offers practical suggestions for applying these strategies in a master's-level physics course, using examples from the field of physics.</jats:p>}},
  author       = {{Webersen, Yvonne and Riese, Josef}},
  issn         = {{0143-0807}},
  journal      = {{European Journal of Physics}},
  publisher    = {{IOP Publishing}},
  title        = {{{Protecting physics students from pseudoscience - combining strategies for a comprehensive teaching approach}}},
  doi          = {{10.1088/1361-6404/ae03f6}},
  year         = {{2025}},
}

@article{61245,
  author       = {{Barkhausen, Franziska and Ares Santos, Laura and Schumacher, Stefan and Sperling, Jan}},
  issn         = {{2469-9926}},
  journal      = {{Physical Review A}},
  number       = {{3}},
  publisher    = {{American Physical Society (APS)}},
  title        = {{{Entanglement between dependent degrees of freedom: Quasiparticle correlations}}},
  doi          = {{10.1103/physreva.111.032404}},
  volume       = {{111}},
  year         = {{2025}},
}

@article{61246,
  abstract     = {{<jats:title>Abstract</jats:title>
          <jats:p>The time-dependent one-dimensional nonlinear Schrödinger equation (NLSE) is solved numerically by a hybrid pseudospectral-variational quantum algorithm that connects a pseudospectral step for the Hamiltonian term with a variational step for the nonlinear term. The Hamiltonian term is treated as an integrating factor by forward and backward Fourier transforms, which are here carried out classically. This split allows us to avoid higher-order time integration schemes, to apply a first-order explicit time stepping for the remaining nonlinear NLSE term in a variational algorithm block, and thus to avoid numerical instabilities. We demonstrate that the analytical solution is reproduced with a small root mean square error for a long time interval over which a nonlinear soliton propagates significantly forward in space while keeping its shape. We analyze the accuracy and complexity of the quantum algorithm, the expressibility of the ansatz circuit and compare it with classical approaches. Furthermore, we investigate the influence of algorithm parameters on the accuracy of the results, including the temporal step width and the depth of the quantum circuit.</jats:p>}},
  author       = {{Köcher, Nikolas and Rose, Hendrik and Bharadwaj, Sachin S. and Schumacher, Jörg and Schumacher, Stefan}},
  issn         = {{2045-2322}},
  journal      = {{Scientific Reports}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Numerical solution of nonlinear Schrödinger equation by a hybrid pseudospectral-variational quantum algorithm}}},
  doi          = {{10.1038/s41598-025-05660-3}},
  volume       = {{15}},
  year         = {{2025}},
}

@article{61249,
  author       = {{Ai, Qiang and Wingenbach, Jan and Yang, Xinmiao and Wei, Jing and Hatzopoulos, Zaharias and Savvidis, Pavlos G. and Schumacher, Stefan and Ma, Xuekai and Gao, Tingge}},
  issn         = {{2331-7019}},
  journal      = {{Physical Review Applied}},
  number       = {{2}},
  publisher    = {{American Physical Society (APS)}},
  title        = {{{Optically and remotely controlling localization of exciton-polariton condensates in a potential lattice}}},
  doi          = {{10.1103/physrevapplied.23.024029}},
  volume       = {{23}},
  year         = {{2025}},
}

@article{61262,
  abstract     = {{There is currently a shortage of teachers in schools, which means that an increasing number of people 
without full qualifications are being employed. In the form of part-time work, students also take on jobs at 
schools that differ from those that are part of a long-term school internship in the teacher education pro
gramme, as the long-term internship aims to professionalize prospective teachers, while part-time work is 
intended to alleviate any shortages. One condition for long-term internships to contribute to the profes
sionalization of prospective teachers is the support of students by mentors and, associated with this, the 
intentional design and reflection of learning opportunities during the internship, which is not associated 
with meeting the needs of schools. It can be concluded that students who work in schools in the form of a 
part-time job alongside their long-term internship are confronted with a wide variety of role expectations 
and tasks, which can have an influence on their experience of stress, among other things. Based on a survey 
of students (n = 134), this article examines the extent to which students combine their long-term internship 
with part-time work, what tasks they have during this part-time work at school, how they are supported and 
to what extent they experience stress. }},
  author       = {{Beckmann, Timo and Caruso, Carina and Homann, Hanna}},
  journal      = {{Lehrerbildung auf dem Prüfstand}},
  number       = {{1}},
  pages        = {{5--22}},
  title        = {{{Nebentätigkeiten von Lehramtsstudierenden während des Langzeitpraktikums: Lerngelegenheiten oder Belastungen?}}},
  doi          = {{https://doi.org/10.62350/AWPI4210}},
  volume       = {{18}},
  year         = {{2025}},
}

@book{61178,
  editor       = {{Ilinykh, Nikolai and Robrecht, Amelie and Kopp, Stefan and Buschmeier, Hendrik}},
  issn         = {{2308-2275}},
  location     = {{Bielefeld, Germany}},
  pages        = {{271+viii}},
  title        = {{{SemDial 2025 – Bialogue. Proceedings of the 29th Workshop on the Semantics and Pragmatics of Dialogue}}},
  year         = {{2025}},
}

@inproceedings{61225,
  author       = {{Lenke, Michael and Lehner, Lukas and Landman, Martina}},
  booktitle    = {{2025 IEEE Global Engineering Education Conference (EDUCON)}},
  publisher    = {{IEEE}},
  title        = {{{“I'm Actually More Interested in AI Than in Computer Science” - 12-Year-Olds Describing Their First Encounter with AI}}},
  doi          = {{10.1109/educon62633.2025.11016657}},
  year         = {{2025}},
}

@inproceedings{61224,
  author       = {{Lenke, Michael and Schulte, Carsten}},
  booktitle    = {{2025 IEEE Global Engineering Education Conference (EDUCON)}},
  publisher    = {{IEEE}},
  title        = {{{Enhancing AI Interaction through Co-Construction: A Multi-Faceted Workshop Framework}}},
  doi          = {{10.1109/educon62633.2025.11016326}},
  year         = {{2025}},
}

@inbook{61275,
  author       = {{Hagengruber, Ruth Edith}},
  booktitle    = {{The Routledge Companion to Philosophy of Time}},
  editor       = {{Emery, Nina}},
  isbn         = {{9781003495611}},
  publisher    = {{Routledge}},
  title        = {{{Émilie Du Châtelet on Time}}},
  doi          = {{10.4324/9781003495611-9}},
  year         = {{2025}},
}

@inproceedings{61243,
  author       = {{Fisher, Josephine Beryl and Terfloth, Lutz}},
  booktitle    = {{ Proceedings of the 29th Workshop on the Semantics and Pragmatics of Dialogue (SemDial 2025)}},
  title        = {{{The Dual Nature as a Local Context to Explore Verbal Behaviour in Game Explanations}}},
  year         = {{2025}},
}

@article{61285,
  author       = {{Herzig, Bardo}},
  issn         = {{1862-5231}},
  journal      = {{Erziehungswissenschaft. Mitteilungen der Deutschen Gesellschaft für Erziehungswissenschaft. Erziehungswissenschaft nach ChatGPT}},
  number       = {{70, Jg.36/2025}},
  pages        = {{13--18}},
  publisher    = {{Barbara Budrich}},
  title        = {{{Die (produktive) Rolle von generativer KI im erziehungswissenschaftlichen Diskurs}}},
  year         = {{2025}},
}

@unpublished{61294,
  abstract     = {{Human-AI collaboration is increasingly promoted to improve high-stakes decision-making, yet its benefits have not been fully realized. Application-grounded evaluations are needed to better evaluate methods for improving collaboration but often require domain experts, making studies costly and limiting their generalizability. Current evaluation methods are constrained by limited public datasets and reliance on proxy tasks. To address these challenges, we propose an application-grounded framework for large-scale, online evaluations of vision-based decision-making tasks. The framework introduces Blockies, a parametric approach for generating datasets of simulated diagnostic tasks, offering control over the traits and biases in the data used to train real-world models. These tasks are designed to be easy to learn but difficult to master, enabling participation by non-experts. The framework also incorporates storytelling and monetary incentives to manipulate perceived task stakes. An initial empirical study demonstrated that the high-stakes condition significantly reduced healthy distrust of AI, despite longer decision-making times. These findings underscore the importance of perceived stakes in fostering healthy distrust and demonstrate the framework's potential for scalable evaluation of high-stakes Human-AI collaboration. }},
  author       = {{Johnson, David S.}},
  title        = {{{Higher Stakes, Healthier Trust? An Application-Grounded Approach to Assessing Healthy Trust in High-Stakes Human-AI Collaboration}}},
  year         = {{2025}},
}

@article{61189,
  author       = {{Herzig, Bardo}},
  issn         = {{1433-4674}},
  journal      = {{SchulVerwaltung Bayern }},
  number       = {{7-8}},
  pages        = {{213--215}},
  publisher    = {{Carl Link}},
  title        = {{{Künstliche Intelligenz und professionsbezogene Aufgaben von Lehrkräften}}},
  year         = {{2025}},
}

@inproceedings{60027,
  author       = {{Hellmich, Frank and Hoya, Fabian Karl and Schulze, Jan Roland and Blumberg, Eva}},
  publisher    = {{Pädagogische Hochschule Vorarlberg}},
  title        = {{{Team-Teaching angehender Lehrkräfte und Kompetenzen von Kindern im inklusiven naturwissenschaftlichen Sachunterricht. Vortrag auf der Tagung der Kommission „Grundschulforschung und Pädagogik der Primarstufe“, Sektion Schulpädagogik, Deutsche Gesellschaft für Erziehungswissenschaft (DGfE). Thema: „Bildung ohne Grenzen denken. Visionen der Grundschulbildung im europäischen Raum" }}},
  year         = {{2025}},
}

@inproceedings{60028,
  author       = {{Löper, Marwin Felix and Hellmich, Frank}},
  publisher    = {{Pädagogische Hochschule Vorarlberg}},
  title        = {{{Einstellungen und prosoziales Verhalten von Grundschulkindern gegenüber Peers mit emotional-sozialem Förderbedarf im inklusiven Unterricht. Vortrag auf der Tagung der Kommission „Grundschulforschung und Pädagogik der Primarstufe“, Sektion Schulpädagogik, Deutsche Gesellschaft für Erziehungswissenschaft (DGfE). Thema: „Bildung ohne Grenzen denken. Visionen der Grundschulbildung im europäischen Raum"}}},
  year         = {{2025}},
}

@inproceedings{59251,
  author       = {{Finke, Pauline and Schulze, Jan Roland and Hellmich, Frank}},
  publisher    = {{University of Belgrade}},
  title        = {{{Exploring primary school teachers’ and special education teachers’ self-efficacy beliefs concerning inclusive education: A qualitative study. Paper. ECER 2025 (European Conference on Educational Research). “Charting the Way Forward: Education, Research, Potentials and Perspectives“ }}},
  year         = {{2025}},
}

@inproceedings{59249,
  author       = {{Finke, Nils and Knickenberg, Margarita and Hellmich, Frank}},
  publisher    = {{BelgradeUniversity of Belgrade}},
  title        = {{{The role of teacher feedback for primary school students’ motivation and mathematical competencies. Paper. ECER 2025 (European Conference on Educational Research). “Charting the Way Forward: Education, Research, Potentials and Perspectives“ }}},
  year         = {{2025}},
}

@inproceedings{59252,
  author       = {{Schulze, Jan Roland and Hellmich, Frank}},
  publisher    = {{University of Belgrade}},
  title        = {{{Pre-service teachers’ professional self-concept development concerning team-teaching in primary schools. Paper. ECER 2025 (European Conference on Educational Research). “Charting the Way Forward: Education, Research, Potentials and Perspectives“ }}},
  year         = {{2025}},
}