@article{66698,
  author       = {{Dehn, Freya}},
  journal      = {{die hochschullehre}},
  number       = {{3}},
  pages        = {{18--33}},
  title        = {{{Professionalisierung angehender Lehrpersonen für Sprachbildung mittels Unterrichtsvideos. Eine qualitative Inhaltsanalyse von Studierendentexten}}},
  volume       = {{12}},
  year         = {{2026}},
}

@techreport{66700,
  author       = {{Minova, Milena and Maahs, Ina-Maria and Dehn, Freya and Drews, Kathrin and Vieth, Brenda and Böttger, Lydia and Heine, Lena and Niederhaus, Constanze and Roll, Heike and Roth, Hans-Joachim}},
  title        = {{{Deutsch als Zweitsprache, Sprachbildung und Mehrsprachigkeit: Curriculare Grundlagen für die Professionalisierung von Lehrkräften}}},
  doi          = {{10.17185/duepublico/86541}},
  year         = {{2026}},
}

@inproceedings{66683,
  abstract     = {{Design for Assembly, Disassembly and Reassembly (DfADR) prepares for high levels of material circularity in terms of repair and remanufacturing. The intention of reassembling products and their part simplies that inspection and sorting need to be integrated with value-conserving objectives. Further, disassembly and reassembly require higher competence levels of workforce than assembly. To provide the required information during engineering, a metadata model (MDM) is required that links established product models to capability models. Since processes to be carried out for realizing a product largely determine required employees’ capabilities, the proposed approach uses the ADR process domain to connect product and capability domains. The research is based on a systematic literature analysis to identify existing approaches regarding MDMs of ADR processes. Based on the results, an integrative MDM is developed that answers defined competence questions. The model enables queries which support engineers by feedback on which skills are required for a product. This builds up a basis to check whether required skills are available in the manufacturing company, either early in product engineering or later in ADR planning.}},
  author       = {{Gräßler, I. and Hesse, Thomas and Pottebaum, Jens}},
  booktitle    = {{1st International Symposium on Hybrid Intelligence in Product and Production Engineering}},
  editor       = {{Graessler, Iris}},
  location     = {{Paderborn}},
  publisher    = {{Universitätsbibliothek}},
  title        = {{{Enabling extreme data by using DS/AI approaches}}},
  doi          = {{10.17619/UNIPB/1-2640}},
  year         = {{2026}},
}

@inproceedings{66514,
  abstract     = {{Manufacturing companies increasingly integrate the strive towards sustainability into product engineering to reduce resource consumption and environmental impacts. A substantial share of a product’s environmental performance is determined during engineering. Early assessments rely on generic data, which is gradually replaced by more concrete simulation and primary data as product maturity increases. The effective use of engineering simulation models for Life Cycle Assessment (LCA) therefore remains a central challenge under heterogeneous, distributed and rapidly evolving data. This article presents a systematic review of product engineering approaches for integrating simulation models into LCA. A seven-step research approach is applied to identify, categorize and evaluate existing approaches across CAx tools. Relevant simulation parameters for sustainability assessment, including material properties, process descriptors, consumables and waste streams, are identified and analyzed. Based on identified data characteristics, the potential of Data Science and Artificial Intelligence methods for LCA data preparation is assessed. A conceptual knowledge-graph-based decision support approach is derived to enable structured integration, traceability and reuse of simulation data for sustainability assessment. The approach is evaluated using criteria from literature. Structured integration of simulation data improves early-stage data quality and supports decision-making in sustainable product engineering.}},
  author       = {{Gräßler, Iris and Aydin, Simon and Rarbach, Sven}},
  booktitle    = {{1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}},
  editor       = {{Gräßler, Iris}},
  location     = {{Paderborn}},
  publisher    = {{Universitätsbibliothek}},
  title        = {{{Systematic review of engineering simulation models for life cycle assessment}}},
  doi          = {{10.17619/UNIPB/1-2637}},
  year         = {{2026}},
}

@proceedings{66704,
  editor       = {{Gräßler, Iris}},
  location     = {{Paderborn}},
  publisher    = {{Universitätsbibliothek}},
  title        = {{{1st International Symposium : March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}}},
  doi          = {{10.17619/UNIPB/1-2663}},
  year         = {{2026}},
}

@inproceedings{66547,
  abstract     = {{Tacit knowledge is particularly valuable in product engineering. Experiences reside in minds of employees and are not systematically documented but could have a significant influence on sustainable product engineering. Existing approaches do not offer sufficient support for harnessing technical tacit knowledge regarding sustainable product engineering. In this paper a three-step method is presented: The method contains knowledge acquisition, requirements extraction und requirements validation for quality assurance. Acquisition is performed by support artifacts like interview guidelines. Extraction is supported by Artificial Intelligence, converting statements into requirements. These requirements are validated using a specific questionnaire. The developed approach is applied in a funded project of the European Union (EU) with automotive industry partners. The method supports product engineers to collect tacit knowledge from experienced employees, transform unsystematic knowledge into standardized technical requirements and validate them. Application of this method enables creation of validated requirements that can be applied throughout the company and are not exclusively dependent on a single employee.}},
  author       = {{Mansheim, Johanna and Gräßler, Iris and Pfeifer, Jan Niklas}},
  booktitle    = {{1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}},
  editor       = {{Graessler, Iris}},
  keywords     = {{Tacit knowledge, Sustainability, Product Engineering, Artificial Intelligence}},
  location     = {{Paderborn}},
  pages        = {{229--238}},
  publisher    = {{Universitätsbibliothek}},
  title        = {{{Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence}}},
  doi          = {{10.17619/UNIPB/1-2639}},
  volume       = {{1}},
  year         = {{2026}},
}

@inproceedings{66702,
  abstract     = {{Strategic product planning defines foresighted directions for product engineering by determining which ideas, technologies and concepts are pursued further. Decisions made in this phase strongly influence subsequent life cycle phases but are characterized by high uncertainty, fragmented information, and predominantly qualitative assessment practices. At the same time, increasing digitalization generates large, heterogeneous, and dynamic data from markets, engineering, usage, and sustainability domains. In this work, such information is understood as extreme data, as its heterogeneity, variety, and dynamics exceed the capabilities of traditional planning approaches. This paper investigates the potential of leveraging extreme data to strengthen hybrid decision support in strategic product planning. A structured literature review is conducted to identify key challenges. These challenges are analysed along the generic product life cycle to capture decision points, information flows, and information circularity. Relevant data sources are identified with respect to their relevance for strategic decisions. Based on this analysis, seventeen potentials for hybrid decision support are derived and clustered into five fields of action. The results indicate that extreme data can enhance strategic foresight, idea evaluation and portfolio decisions, lifecycle-spanning knowledge integration, engineering support for strategic decisions, and the adoption of AI-based methods.}},
  author       = {{Gräßler, Iris and Goldstein, Julius Hendrik}},
  booktitle    = {{1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}},
  editor       = {{Gräßler, Iris}},
  location     = {{Paderborn}},
  publisher    = {{Universitätsbibliothek}},
  title        = {{{Hybrid decision support in strategic product planning}}},
  doi          = {{10.17619/UNIPB/1-2644}},
  year         = {{2026}},
}

@inproceedings{66687,
  abstract     = {{With a range of consumer devices available, augmented reality (AR) continues to make its way into everyday life and is also increasingly used in professional and sensitive contexts. Especially collaborative use cases, such as remote meetings or maintenance, offer potential, but also move issues in the area of privacy and security into focus. We conducted a scoping review to gain an overview of the current situation and found a lack of clear standards, with most approaches focusing on single protection features. Using the knowledge from the scoping review, we set up and conducted expert interviews. They revealed that end-users are almost completely dependent on developers or device manufacturers regarding their options for protection. The interviews also showed that most developers put little focus on privacy and security, often due to external constraints, such as employers treating the topic as an “afterthought” and not budgeting enough time for it. The experts suggested offering better software support to developers to enable the inclusion of privacy and security with less overhead as a solution. It was also suggested that a general rise in privacy and security awareness could improve the overall situation.}},
  author       = {{Krings, Sarah Claudia and Yigitbas, Enes and Sauer, Stefan}},
  booktitle    = {{Blending Experiences in Interaction Design}},
  editor       = {{Maciel, Cristiano and Spano, Davide Lucio and Ardito, Carmelo and Freire, André and Prates, Raquel}},
  isbn         = {{978-3-032-22934-2}},
  pages        = {{253–276}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Perspectives on Privacy and Security in Collaborative AR - Insights from a Scoping Review and an Expert Interview Study}}},
  year         = {{2026}},
}

@article{66688,
  author       = {{Wüppelmann, Dennis and Yigitbas, Enes}},
  issn         = {{2944-7682}},
  journal      = {{GI - Software Engineering }},
  publisher    = {{Gesellschaft für Informatik, Bonn}},
  title        = {{{SecCityVR: Visualization and Collaborative Exploration of Software Vulnerabilities in Virtual Reality}}},
  doi          = {{10.18420/se2026_53}},
  year         = {{2026}},
}