From Engineering to Shaping: A Multiple Case Study on Advancing Service Systems Engineering through Continuous Value Shaping - Schäfer, Jannika Marie; Rajko, Polina; Angelova, Daniela; Böhmann, Tilo (Proceedings of the 59th Hawaii International Conference on System Sciences (HICSS 2026))
Service systems engineering relies on structured, top-down approaches to designing and innovating service systems. In today’s dynamic environments—shaped by digital transformation, evolving provider–user interactions, and shifting societal demands—these approaches face limitations in enabling continuous, context-sensitive innovation. Continuous Value Shaping emerges as a conceptual extension to service systems engineering, promoting more adaptive and co-evolutionary forms of service system development. This study examines how Continuous Value Shaping manifests through a multiple case study of three public sector projects. We identify distinct manifestations and constellations of the concept’s principles that complement classical SSE practices. As the first empirical exploration of Continuous Value Shaping, the study refines its conceptual foundation and enhances its accessibility for researchers and practitioners. We conclude with seven empirically derived propositions that inform future service systems engineering initiatives and demonstrate how Continuous Value Shaping supports the dynamic alignment of service systems with societal and systemic demands.
Keywords: Continuous Value Shaping; Service Systems Engineering; Service Science; Public Sector; Service Innovation

Application of Novel Exponential (Semi-)Parametric Short and Long Memory GARCH Models under Regulatory Requirements of Basel III - Hanke, Dominik Christian; Uhde, André; Feng, Yuanhua
This paper evaluates the forecasting performance of an expanded class of (semi-)parametric GARCH models belonging to the EGARCH family (EGF), including recently introduced long and short memory specifications and their semiparametric extensions. The semiparametric variants employ a multiplicative volatility decomposition into conditional and slowly varying unconditional components, where the latter is estimated via a data-driven local polynomial smoother to accommodate non-stationarities commonly observed in financial time series. Based on the revised Basel Committee framework for market-risk assessment, all models are capable of producing rolling one-day-ahead forecasts for Value at Risk (VaR) and Expected Shortfall (ES) under a wide range of symmetric and skewed innovation distributions. Their forecasting accuracy is examined using the regulatory traffic light tests for VaR and the recently developed ES-specific traffic light procedure, complemented by the regulatory loss function. In addition, model selection incorporates both a recently proposed corrected firm-oriented loss function that accounts for opportunity costs and the Weighted Absolute Deviation (WAD) criterion. The empirical comparison demonstrates that (semiparametric) long memory GARCH models - particularly those combining fractional dynamics with nonparametric scale adjustments - can serve as valuable alternatives to traditional parametric short memory models, offering more stable volatility estimates and improved tail-risk forecasts for practical risk management applications.
Keywords: semiparametric GARCH extension; data-driven local polynomial smoother; long memory; GARCH models; Value at Risk; Expected Shortfall; traffic light test; backtesting; Basel III; market risk

Comparing the behaviors of some original short and long memory exponential volatility models - Hanke, Dominik Christian; Feng, Yuanhua; Uhde, André
Volatility modeling is utilized across numerous fields including finance, environmental studies, and social sciences. It is particularly relevant in scenarios where understanding and predicting conditional variability is crucial, such as when dealing with incremental or time-dependent data. In this paper, novel short and long memory volatility models of the EGARCH family are introduced and analyzed, which are closely related to the well-established EGARCH model proposed by Nelson (1991) but share desirable theoretical properties in several dimensions. Recently developed members of the so-called EGARCH family, which introduces a modulus-log transformation proposed by John and Draper (1980) and a power transformation for the size and magnitude effect to tackle the problem with near-zero innovations and the asymmetric impact of positive and negative shocks on the volatility, are discussed. After a theoretical discussion of the proposed and related volatility models, the practical performance of the elaborated volatility models is compared to well-established and traditional GARCH approaches. A general QMLE algorithm is proposed to estimate the model parameters. The practical relevance of the advanced models is illustrated through a comparative study. By applying these volatility models to a variety of international stock index returns, this paper identifies market-specific characteristics as well as unique strengths and weaknesses of discussed volatility models. Although the practical performance of the recently introduced models is comparable to those obtained by the traditional EGARCH model, they generally outperform traditional non-exponential volatility models used as benchmarks and thus provide a useful alternative to existing short and long memory volatility models.
Keywords: Modulus Log-GARCH; Modified (FI)EGARCH; Modulus asymmetric (FI)Log-GARCH; (FI)EGARCH; long memory; modulus-log transformation; QMLE; model selection; implementation in R

Unterstützung von Verstehen im Fachunterricht. Eine Grounded Theory zum sprach- und fachverbindenden Geschichtsunterricht - Müller, Jennifer
Wie verläuft der Leseprozess im Geschichtsunterricht für Schüler:innen, die neu in das deutsche Bildungssystem einsteigen – und welche Faktoren beeinflussen ihr Verstehen? Diese Studie untersucht an der Schnittstelle von Deutsch als Zweitsprache und Geschichtsdidaktik die Bedingungen des Lesens im Geschichtsunterricht. Im Fokus stehen die Erfahrungen von Seiteneinsteiger:innen sowie die Perspektiven der Lehrkräfte, die im Rahmen einer qualitativ‑explorativen Untersuchung mithilfe von Unterrichtshospitationen, Interviews und Materialanalysen erhoben wurden. Methodisch ist die Arbeit in der Grounded Theory Methodology nach Strauss und Corbin (1996) verankert, anhand derer die komplexen Einflussfaktoren historischer Leseprozesse systematisch herausgearbeitet werden. Die Ergebnisse zeigen drei zentrale Einflussdimensionen: sprachliche, sozial‑affektive und geschichtsspezifische Faktoren. Zudem wird deutlich, dass Unterstützungsmaßnahmen stets zwischen kurzfristiger Hilfe und dem langfristigen Aufbau von Disciplinary Literacy ausbalanciert werden müssen. Ihre Wirksamkeit hängt wesentlich von der bewussten Auswahl und Zugänglichkeit durch die Lehrkraft sowie von den Möglichkeiten der Lernenden ab, Unterstützung gezielt einzufordern. Lernwirksam wird Geschichtsunterricht besonders dann, wenn hohe fachliche Anforderungen mit reflektierter sprachlicher Unterstützung verbunden werden. Die Studie leistet damit einen Beitrag zur Forschung zu sprachbewusstem Fachunterricht und bietet Impulse für eine kritisch‑reflexive Sprachsensibilität in schulischen Bildungsprozessen.
Keywords: Scaffolding; Sprache und Fach; Grounded Theory Methodology; Lesen in der Sekundarstufe I; Sprachsensibler Geschichtsunterricht; Durchgängige Sprachbildung

Social Context in Human-AI Interaction (HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries - Menne, Anna Lena; Schulz, Christian (HCI International 2026 Posters: 28th International Conference on Human-Computer Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part I)
Despite decades of awareness, asymmetries in conceptual resources, data, and governance between users and developers persist. Meanwhile, socially situated ‘end-users’ experience harms, such as hidden labor, reinforced stereotypes, and increased unpredictability, as machine learning advances. However, accurately modeling social context does not constitute design justice. This paper reinterprets Giuseppe Mantovani’s model of social context in human-computer interaction (HCI) to address the relational emergence and political situatedness of social context in human-AI interaction (HAI). Drawing on the concept of a multi-perspectival algorithmic imaginary, we (1) conceptualize context as nested and entangled relations, (2) identify actors, including users, developers, models, and interfaces, and (3) foreground the organization of relations of power. Recognizing that models are performative rather than predictive, we argue that the sociopolitical situatedness of context must be acknowledged alongside its limits. To challenge design authority, we propose that HCI and HAI strategically foster intra-actional negotiability, enabling users to challenge, reinterpret, or modify their relationship with technology through critical (design) practices.
Keywords: Social Context; Situatedness; Imaginaries

Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications? - Peters, Tobias Martin; Scharlau, Ingrid (Frontiers in Psychology)
Due to the application of Artificial Intelligence (AI) in high-risk domains like law or medicine, trustworthy AI and trust in AI are of increasing scientific and public relevance. A typical conception, for example in the context of medical diagnosis, is that a knowledgeable user receives AIgenerated classification as advice. Research to improve such interactions often aims to foster the user’s trust, which in turn should improve the combined human-AI performance. Given that AI models can err, we argue that the possibility to critically review, thus to distrust, an AI decision is an equally interesting target of research. We created two image classification scenarios in which the participants received mock-up AI advice. The quality of the advice decreases for a phase of the experiment. We studied the task performance, trust and distrust of the participants, and tested whether an instruction to remain skeptical and review each piece of advice led to a better performance compared to a neutral condition. Our results indicate that this instruction does not improve but rather worsens the participants’ performance. Repeated single-item self-report of trust and distrust shows an increase in trust and a decrease in distrust after the drop in the AI’s classification quality, with no difference between the two instructions. Furthermore, via a Bayesian Signal Detection Theory analysis, we provide a procedure to assess appropriate reliance in detail, by quantifying whether the problems of under- and over-reliance have been mitigated. We discuss implications of our results for the usage of disclaimers before interacting with AI, as prominently used in current LLM-based chatbots, and for trust and distrust research.
Keywords: trust in AI; trust; distrust; human-AI interaction; Signal Detection Theory; Bayesian parameter estimation; image classification

Long-Term Cycling Stability of Sodium/Sodium Ion Cells Probed by In Situ Solid-State NMR Spectroscopy - Egert, Sonja; Remesh, Renuka; Jusdi, Agatha Clarissa; Sugawara, Yushi; Schutjajew, Konstantin; Oschatz, Martin; Buntkowsky, Gerd; Gutmann, Torsten (Batteries & Supercaps)
Sodium-ion batteries are at the forefront of new, sustainable energy systems required for the global energy transition. 23Na in situ solid-state nuclear magnetic resonance spectroscopy is capable of unraveling structures in working electrochemical cells during the charging and discharging processes. To evaluate its suitability for long-term studies, local sodium environments in sodium/sodium ion cells based on silicon carbonitride and hard carbon materials are tracked for up to 49 cycles (228.5?h). The formation of dendrites as well as the decay of a secondary metallic sodium species is observed, and local structures are analyzed up to the point of capacity degradation and cell failure. Initial points of cell breakdown are reflected in the NMR data by characteristic changes in signal intensities, whereas the degradation of the cells is reflected by a cease to periodic signal intensity fluctuations. Meanwhile, ex situ 23Na NMR spectra of the deactivated cells reveal a complex range of environments for sodium ions.
Keywords: solid-state nmr; hard carbon; in-situ; SiCN; sodium ion batteries

In situ CT unter Temperatur: Thermokammer für thermoplastische FKV-Fügeprozesse - Dargel, Alrik; Köhler, Daniel; Gude, Maik; Kupfer, Robert (Tagungsband 43. Vortrags- und Diskussionstagung Werkstoffprüfung 2025)
Für das Verständnis und die Weiterentwicklung temperaturgestützter mechanischer Fü-geprozesse mit thermoplastischen Faser-Kunststoff-Verbunden (FKV) ist die zerstörungsfreie Analyse der Materialstruktur im Inneren des Fügepunktes während der Entstehung und Belastung erforderlich. Die Kombination aus Prüfung unter Temperatureinfluss und in situ Computertomographie (CT) eröffnet neue Möglichkeiten für die Fügeprozessanalyse. Dazu wurde dazu eine Thermokammer entwickelt und in eine bestehende in situ CT-Anlage integriert. Anwendungsszenarien sind die Herstellung und Prüfung von Fügepunkten unter Temperatur. Die Erwärmung erfolgt über einzeln regelbare Heizzonen, welche eine gezielte Temperaturführung über die gesamte Probengeometrie ermöglichen. Die Temperaturkurve eines Aufheizversuchs, sowie eine Röntgenprojektion einer Probe innerhalb der Thermokammer validie-ren die Konstruktion.
Keywords: in situ CT; Thermokammer; Thermoplastische FKV

The power of combined modalities in interactive robot learning - Beierling, Helen; Beierling, Robin; Vollmer, Anna-Lisa (Frontiers in Robotics and AI)
This study contributes to the evolving field of robot learning in interaction with humans, examining the impact of diverse input modalities on learning outcomes. It introduces the concept of "meta-modalities" which encapsulate additional forms of feedback beyond the traditional preference and scalar feedback mechanisms. Unlike prior research that focused on individual meta-modalities, this work evaluates their combined effect on learning outcomes. Through a study with human participants, we explore user preferences for these modalities and their impact on robot learning performance. Our findings reveal that while individual modalities are perceived differently, their combination significantly improves learning behavior and usability. This research not only provides valuable insights into the optimization of human-robot interactive task learning but also opens new avenues for enhancing the interactive freedom and scaffolding capabilities provided to users in such settings.
Keywords: human-robot interaction; human-in-the-loop learning; reinforcement learning; interactive robot learning; multi-modal feedback; learning from demonstration; preference-based learning; scaffolding in robot learning

Human-Interactive Robot Learning: Definition, Challenges, and Recommendations - Baraka, Kim; Idrees, Ifrah; Faulkner, Taylor Kessler; Biyik, Erdem; Booth, Serena; Chetouani, Mohamed; Grollman, Daniel H.; Saran, Akanksha; Senft, Emmanuel; Tulli, Silvia; Vollmer, Anna-Lisa; Andriella, Antonio; et al. (Transactions on Human-Robot Interaction)
Robot learning from humans has been proposed and researched for several decades as a means to enable robots to learn new skills or adapt existing ones to new situations. Recent advances in artificial intelligence, including learning approaches like reinforcement learning and architectures like transformers and foundation models, combined with access to massive datasets, has created attractive opportunities to apply those data-hungry techniques to this problem. We argue that the focus on massive amounts of pre-collected data, and the resulting learning paradigm, where humans demonstrate and robots learn in isolation, is overshadowing a specialized area of work we term Human-Interactive-Robot-Learning (HIRL). This paradigm, wherein robots and humans interact during the learning process, is at the intersection of multiple fields (artificial intelligence, robotics, human-computer interaction, design and others) and holds unique promise. Using HIRL, robots can achieve greater sample efficiency (as humans can provide task knowledge through interaction), align with human preferences (as humans can guide the robot behavior towards their expectations), and explore more meaningfully and safely (as humans can utilize domain knowledge to guide learning and prevent catastrophic failures). This can result in robotic systems that can more quickly and easily adapt to new tasks in human environments. The objective of this paper is to provide a broad and consistent overview of HIRL research and to guide researchers toward understanding the scope of HIRL, and current open or underexplored challenges related to four themes — namely, human, robot learning, interaction, and broader context. The paper includes concrete use cases to illustrate the interaction between these challenges and inspire further research according to broad recommendations and a call for action for the growing HIRL community
Keywords: Robot learning; Interactive learning systems; Human-robot interaction; Human-in-the-loop machine learning; Teaching and learning

Continuous value shaping: A boundary concept for innovating service innovation approaches - Böhmann, Tilo; Roth, Angela; Satzger, Gerhard; Benz, Carina; Beverungen, Daniel; Boes, Andreas; Breidbach, Christoph; Gersch, Martin; Gudergan, Gerhard; Hogreve, Jens; Kurtz, Christian; Langes, Barbara; et al. (Electronic Markets)
Technological advancements and evolving value orientations reshape future value creation and pose new requirements for service innovation. While a variety of disciplines are developing new approaches to drive service innovation, this is primarily done in isolation and generates only fragmented solutions. Sociological theory has proposed “boundary objects” as an effective umbrella for communication and cooperation among communities. Therefore, we introduce continuous value shaping (CVS) as a boundary object describing service innovation approaches along five principles. We reflect on this concept through the different disciplinary lenses of researchers in service marketing, information systems, service engineering, sociology of work, and innovation management. These perspectives highlight how the CVS principles already connect to discourses within the individual disciplines. However, the CVS concept will not only provide an umbrella to embrace existing activities in different academic disciplines. It also assists to identify research themes that will benefit from uniting the power of these disciplines, and it can serve as an integrating framework to conceptualize complex service innovation approaches. Thus, the CVS concept should guide both researchers and practitioners to develop and implement novel innovation and transformation efforts—in and across organizations.
Keywords: Continuous value shaping (CVS); Service research; Service innovation; Digitalization; Sustainability; Interdisciplinary research

In Situ Alloying of Ti-6Al-7Nb with Copper Using Laser Powder Bed Fusion - Steinmeier, Paul; Hoyer, Kay-Peter; Lopes Dias, Nelson Filipe; Zielke, Reiner; Tillmann, Wolfgang; Schaper, Mirko (Crystals)
Titanium alloys are widely employed for biomedical implants due to their high strength, biocompatibility, and corrosion resistance, yet their lack of intrinsic antibacterial activity remains a major limitation. Incorporating copper, an antibacterial and β-stabilising element, offers a promising strategy to enhance implant performance. This study investigates Ti-6Al-7Nb modified with 1–9 wt.% Cu via in situ alloying during metal-based laser powder bed fusion (PBF-LB/M), with the aim of assessing processability, microstructural evolution, and mechanical properties. Highly dense samples (>99.9%) were produced across all Cu levels, though chemical homogeneity strongly depended on processing parameters. Increasing Cu content promoted β-phase stabilisation, Ti2Cu precipitation, and pronounced grain refinement. Hardness and yield strength increased nearly linearly with Cu addition, while ductility decreased sharply at ≥5 wt.% Cu due to intermetallic formation, hot cracking, and brittle fracture. These results illustrate both the opportunities and constraints of rapid alloy screening via PBF-LB/M. Overall, moderate Cu additions of 1–3 wt.% provide the most favourable balance between mechanical performance, manufacturability, and potential antibacterial functionality. These findings provide a clear guideline for the design of Cu-functionalised titanium implants and demonstrate the efficiency of in situ alloy screening for accelerated materials development.
Keywords: Biomaterial; In Situ Alloying; Titanium; Additive Manufacturing

Bridging the gap between data-driven and theory-driven modelling – leveraging causal machine learning for integrative modelling of dynamical systems - Zapata Gonzalez, David Ricardo; Meyer, Marcel; Müller, Oliver
Classical machine learning techniques often struggle with overfitting and unreliable predictions when exposed to novel conditions. Introducing causality into the modelling process offers a promising way to mitigate these challenges by enhancing predictive robustness. However, constructing an initial causal graph manually using domain knowledge is time-consuming, particularly in complex time series with numerous variables. To address this, causal discovery algorithms can provide a preliminary causal structure that domain experts can refine. This study investigates causal feature selection with domain knowledge using a data center system as an example. We use simulated time-series data to compare different causal feature selection with traditional machine-learning feature selection methods. Our results show that predictions based on causal features are more robust compared to those derived from traditional methods. These findings underscore the potential of combining causal discovery algorithms with human expertise to improve machine learning applications.
Keywords: Causal Machine Learning; Causality in Time Series; Causal Discovery; Human-Machine Collaboration

Maghemite nanoparticles synthesis via spray flame synthesis and particle characterization by hole in a tube sampling and scanning mobility particle sizing (HIAT-SMPS) (Applications in Energy and Combustion Science)
In order to standardize spray flame synthesis (SFS) studies, intensive work has been done in recent years on the design of burner types. Thus, in 2019, the so-called SpraySyn1 burner was introduced (SS1), which was subsequently characterized in numerical and experimental studies. Based on this research, a modification of the nozzle design was proposed, which has now been considered in the successor model, SpraySyn2 (SS2). As little is known about the effect of the nozzle adaptation on the particle formation, we operated both burners under identical operating conditions to produce maghemite. The final powder comparison showed that SS2 yielded considerable higher specific surface areas (associated with smaller primary particle sizes), lower polydispersity, and higher phase purity. To obtain further information on the size distributions of aggregates and agglomerates generated by SS2, aerosol samples were extracted by hole in a tube (HIAT) sampling and characterized by scanning mobility particle sizing (SMPS). Samples were extracted along the centerline at different heights above the burner (HAB) above the visible flame tip (>7 cm), and quenching experiments were performed to extract the aerosol samples at different dilution rates. Thereby, it was demonstrated that performing detailed quenching experiments is crucial for obtaining representative HIAT-SMPS data. In particular, agglomerates/aggregate sizes were overestimated by up to ~70 % if samples were not sufficiently diluted. If sufficient dilution was applied, distribution widths and mean particle mobility diameters were determined with high accuracy (sample standard derivation <5 %). Our data suggested the evolution of primary particle sizes was mostly completed <7 cm HAB and it was shown aggregates/agglomerates present above the visible flame were compact in structure (non- fractal). The mean diameter of the particle ensemble grew along the centerline from 6.9 nm (7 cm) to 11.4 nm (15 cm), while distribution widths grew from 1.42 to 1.52.
Keywords: Flame Spray Pyrolysis; SpraySyn2; Spray flame synthesis; Maghemite nanoparticles; Gas to particle-conversion; Hole in a tube sampling

The Value of Reputation Systems in Business Contexts–A Qualitative Study Taking the View of Buyers - Hemmrich, Simon; Schäfer, Jannika Marie; Hansmeier, Philipp; Beverungen, Daniel (Proceedings of the 57th Hawaii International Conference on System Sciences)
Reputation systems for companies to rate each other's performance are largely unexplored in research and hardly available in practice. However, these systems are relevant for prospective buyers to find a trustworthy seller. This observation applies especially to short-lived business relationships where fulfilling the performance promise is subject to a high degree of uncertainty. This paper explores the value of a reputation system for a business-to-business (B2B) context and focuses on three novel solutions for designing reputation systems. These solutions include selling ratings, conducting ratings as payments, and employing a counter-rating mechanism. We interview buyers to fathom the added value of these solutions in different contexts. Our findings suggest that such a system is useful for companies acting in less transparent markets and also helps when companies already have a good market overview. Depending on the market conditions and business context, the perceived value of the proposed system varies.
Keywords: Electronic Marketing; business-to-business; new design approach; reputation systems; value for buyers.

MINTfluencerinnen auf Instagram. Sozialmediale Sichtbarkeit junger Frauen in MINT-Berufen - Pätz, Ricarda (Gender(ed) thoughts)
Der Neologismus ‚MINTfluencer:in‘ beschreibt reichweitenstarke Profile in sozialen Netzwerken von Frauen in technischen und naturwissenschaftlichen Berufen. Die qualitative Inhaltsanalyse untersucht die unterrepräsentierten Gruppen ‚Scientist Mom‘ und ‚Trans* Scientist‘ auf Instagram aus gendermedialer Perspektive. Es werden Erkenntnisse über das Verhältnis von Wissenschaftskommunikation, Berufsrepräsentation sowie Geschlecht generiert und mit dekonstruktivistischen, intersektionalen Theorien und Heteronormativitätskritik verknüpft. Die Betrachtung der Selbstinszenierung berufstätiger Mütter und transsexueller Wissenschaftler:innen als MINTfluencer:innen erforscht, inwiefern ihr Auftreten als feministische Transformation im Kontext weiblicher Berufsausübung und Sichtbarkeit in männlich dominierten Berufen gesehen werden kann.
Keywords: MINTfluencerin; Frauen in MINT; Wissenschaftskommunikation; Instagram; qualitative Inhaltsanalyse; Gender Media Studies; Gender Science Studies

Bestimmt unbestimmt? - Eine quantitativ-explorative Studie zu Aufgabenprofilen von Fachkräften für das Multiprofessionelle Team (MPT) an inklusiven Gesamt-und Sekundarschulen in NRW. - Meusel, Sarah; Müller, Lukas; Jesuthasan, Jonitta (Zeitschrift für Inklusion)
Der Beitrag untersucht den Einsatz von Fachkräften für das Multiprofessionelle Team im Gemeinsamen Lernen (MPT). Diese meist sozialpädagogisch ausgebildeten Fachkräfte sind dezidiert für die Unterstützung der Inklusion an Grund-, Sekundar-und Gesamtschulen angestellt. Erste Befunde (Grüter et al.,2022) und ministeriale Aufgabenbeschreibung (Ministerium für Schule und Bildung des Landes Nordrhein-Westfalen [MSB NRW], 2022) deuten auf ein offenes, wenig definiertes Tätigkeitsspektrum hin. Mögliche Aufgabengebiete der MPT überschneiden sich mit denen der (sonderpädagogischen) Lehrkräfte, der Schulsozialarbeiter*innen und –im Hinblick auf die Unterstützung im Unterricht ohne Unterrichtsverantwortung –mit denen der Schulbegleitungen (Lübeck, 2019).Die Überlappungen legen nahe, dass auch für die MPT das „Zuständigkeitsdiffusitätsproblem“ (Kunze 2016, S.265) gilt und die multiprofessionelle Teamarbeit entsprechend beeinflusst. Da es bislang keine Daten darüber gibt, wie sich die Berufsrolle von MPT-Kräften in der Breite ausgestaltet, eruiert der Beitrag in einer quantitativen Studie ebendiese Frage. Zusätzlich werden die Fragenfokussiert, über welche Qualifikationen und Vorerfahrungen MPT-Kräfte verfügen und mit welchen Akteur*innen MPT-Kräfte in welcher Form kooperieren. Die Untersuchung bezieht sich auf den Einsatz von MPT an Gesamt-und Sekundarschulen in NRW. Insgesamt wurden 109 MPT-Kräfte in Form eines Online-Fragebogens befragt. Anhand der Ergebnisse konnte ein breites Einsatzgebiet mit vereinzelten Aufgabenschwerpunkten (v.a. im Bereich der sonderpädagogisch orientierten Kleingruppenförderung) der MPT-Kräfteidentifiziert werden. Schnittmengen zu Aufgabenschwerpunkten anderer Berufsgruppen werden unter Berücksichtigung der multiprofessionellen Kooperation hinsichtlich der Frage diskutiert, ob der Einsatz von MPT-Kräften inklusive Zielstellungen eher befördert oder im Sinne einer Deprofessionalisierung sonderpädagogischer Förderung eher entgegensteht.
Keywords: Deprofessionalisierung; Kooperation; Fachkräfte für das Multiprofessionelle Team(MPT); Aufgabenprofile in der inklusiven Schule

How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals? - Hoffmann, Max; Schlüter, Sarah (Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024))
In our paper, we present a study in which we investigate which strategies pre-service teachers (PSTs) use to find and, if necessary, reject possible candidates for congruence theorems for quadrilaterals. This study was conducted before the PTSs attended a university geometry course. In this way, statements about learning prerequisites can be made. For the study, we analyzed group discussions of PSTs to identify typical approaches and evaluate them from a mathematical perspective. The results can be considered for the further development of courses for PSTs and generate hypotheses for further research.
Keywords: Teachers’ and students’ practices at university level; Transition to; across and from university mathematics; Teaching and learning of specific topics in university mathematics; Congruence; Quadrilaterals

Zu den Unwägbarkeiten des Erbes - Unzuverlässiges Postmemory-Erzählen in den Gesellschaftsromanen 'Das flüssige Land' von Raphaela Edelbauer und in 'Dunkelblum' von Eva Menasse - Müller, Inez (Von neuen Blicken auf die frühe Nachkriegszeit)
Keywords: postmemory; unrelieable telling; war crimes in Austria in the context of the Second World War; Eva Menasse; Raphaela Edelbauer

ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification - Qudus, Umair; Röder, Michael; Vollmers, Daniel; Ngonga Ngomo, Axel-Cyrille (Proceedings of the 33rd ACM International Conference on Information and Knowledge Management)
Detecting the veracity of a statement automatically is a challenge the world is grappling with due to the vast amount of data spread across the web. Verifying a given claim typically entails validating it within the framework of supporting evidence like a retrieved piece of text. Classifying the stance of the text with respect to the claim is called stance classification. Despite advancements in automated fact-checking, most systems still rely on a substantial quantity of labeled training data, which can be costly. In this work, we avoid the costly training or fine-tuning of models by reusing pre-trained large language models together with few-shot in-context learning. Since we do not train any model, our approach ExPrompt is lightweight, demands fewer resources than other stance classification methods and can serve as a modern baseline for future developments. At the same time, our evaluation shows that our approach is able to outperform former state-of-the-art stance classification approaches regarding accuracy by at least 2 percent. Our scripts and data used in this paper are available at https://github.com/dice-group/ExPrompt.
Keywords: Stance Classification; Few-shot in-context learning; Pre-trained large language models