@inbook{65061,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>
                    One of the purposes for which XAI is often brought into play is to enable a user to act responsibly. However, responsibility is a complex normative and social phenomenon that we unfold in this chapter. We consider that the classical concepts of agency and responsibility do not fully capture what is needed for meaningful collaboration between human users and XAI. Advocating the perspective of sXAI, we argue that the growing adaptivity of AI systems will result in sXAI being considered as partners. Both partners adopt particular (dialogical) roles within a collaborative process and take responsibility for them. We expect that these roles lead to reactive attitudes toward the sXAI on the side of the human partners that make these roles relational. They resemble those reactive attitudes that we hold toward other human agents. For agents to exercise their responsibility, they need to possess agential capacities to fulfill their role with respect to the structure of a social interaction. Hence, sXAI can be expected to act responsibly. But because of XAI’s limited normative capacities, it might rather act as a marginal agent. We refer to marginal agents and show they can be scaffolded with regard to their agential capacities and their knowledge about the structure of a social interaction. The structure links the actions of the partners to each other in terms of a set of stimuli and responses to it in pursuit of a particular goal. Hence, it is important to differentiate between the different goals that a structure can impose for exercising responsibility. Therefore, we follow (Responsibility from the margins. Oxford University Press; 2015.
                    <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1093/acprof:oso/9780198715672.24001.0001" ext-link-type="uri">https://doi.org/10.1093/acprof:oso/9780198715672.24001.0001</jats:ext-link>
                    ) and offer three structures that can help to organize responsibility for
                    <jats:italic>decisions made</jats:italic>
                    with the assistance of AI systems. These structures are attributability, answerability, and accountability. Our insights will inform the development and design process of XAI to meet the guiding principles of responsible research and innovation as well as trustworthy AI.
                  </jats:p>}},
  author       = {{Rohlfing, Katharina J. and Alpsancar, Suzana and Schulte, Carsten}},
  booktitle    = {{Social Explainable AI}},
  isbn         = {{9789819652891}},
  pages        = {{157--177}},
  publisher    = {{Springer Nature Singapore}},
  title        = {{{Responsibilities in sXAI}}},
  doi          = {{10.1007/978-981-96-5290-7_9}},
  year         = {{2026}},
}

@techreport{65180,
  author       = {{Terfloth, Lutz and Buhl, Heike M. and Lohmer, Vivien and Schaffer, Michael and Kern, Frederike and Schulte, Carsten}},
  title        = {{{Bridging the Dual Nature: How Integrated Explanations Enhance Understanding of Technical Artifacts}}},
  year         = {{2026}},
}

@article{65492,
  author       = {{Lutz, Terfloth and Buhl, Heike M. and Lohmer, Vivien and Kern, Friederike and Schaffer, Michael E. and Schulte, Carsten}},
  journal      = {{International Journal of Technology and Design Education}},
  publisher    = {{Springer}},
  title        = {{{Navigating the dual nature: do explainers adapt to explainee interests when explaining technical artifacts}}},
  year         = {{2026}},
}

@article{60357,
  abstract     = {{<jats:p>Transcripts play a crucial role in qualitative research in computing education, with significant implications for the credibility and reproducibility of findings. However, unreflective and inconsistent transcription standards may unintentionally introduce biases, potentially undermining the validity of research outcomes and the collective progress of the field. In this article, we introduce transcription as a theoretically guided process rather than a mere preparatory step, illustrating its role using a case example. Additionally, through a systematic review of 107 qualitative research articles in computing education, we identify widespread shortcomings in the reporting and implementation of transcription practices, revealing a need for greater intentionality and transparency. To address these challenges, we propose a three-step framework for selecting, applying, and documenting transcription standards that align with the specific context and goals of a study. Rather than advocating for overly complex, one-size-fits-all transcription strategies, we emphasize the importance of a context-appropriate approach that is clearly communicated to foster trust and reproducibility. By advancing a more robust transcription culture, this work aims to support computing education researchers in adopting standards that enhance the quality and reliability of qualitative research in the field.</jats:p>}},
  author       = {{Terfloth, Lutz and Lohmer, Vivien and Kern, Friederike and Schulte, Carsten}},
  issn         = {{1648-5831}},
  journal      = {{Informatics in Education}},
  publisher    = {{Vilnius University Press}},
  title        = {{{Transcription in Computing Education Research: A Review and Recommendations}}},
  doi          = {{10.15388/infedu.2025.09}},
  year         = {{2025}},
}

@article{60508,
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{0899-3408}},
  journal      = {{Computer Science Education}},
  pages        = {{1--33}},
  publisher    = {{Informa UK Limited}},
  title        = {{{ReVEAL model and its application to revealing viewpoints on educational approaches to learning about data and AI}}},
  doi          = {{10.1080/08993408.2025.2516957}},
  year         = {{2025}},
}

@inbook{60532,
  author       = {{Biehler, Rolf and Schulte, Carsten}},
  booktitle    = {{Proceedings of the 1st Symposium on Integrating AI and Data Science into School Education Across Disciplines (AIDEA 1 2025), Salzburg, Austria}},
  title        = {{{Lessons Learned from the ProDaBi Project: Shaping Perspectives at the Intersection of Data, AI, and Education Towards Fostering AI and Data Science Literacy in Schools Across Disciplines.}}},
  year         = {{2025}},
}

@inbook{61222,
  author       = {{Lenke, Michael and Klowait, Nils and Biere, Lea and Schulte, Carsten}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783032012210}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Assessing AI Literacy: A Systematic Review of Questionnaires with Emphasis on Affective, Behavioral, Cognitive, and Ethical Aspects}}},
  doi          = {{10.1007/978-3-032-01222-7_8}},
  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}},
}

@inproceedings{52379,
  author       = {{Hüsing, Sven and Schulte, Carsten and Sparmann, Sören and Bolte, Mario}},
  booktitle    = {{Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1}},
  publisher    = {{ACM}},
  title        = {{{Using Worked Examples for Engaging in Epistemic Programming Projects}}},
  doi          = {{10.1145/3626252.3630961}},
  year         = {{2024}},
}

@inproceedings{54796,
  author       = {{Hüsing, Sven and Sparmann, Sören and Schulte, Carsten and Bolte, Mario}},
  booktitle    = {{Proceedings of the 2024 Symposium on Eye Tracking Research and Applications}},
  publisher    = {{ACM}},
  title        = {{{Identifying K-12 Students' Approaches to Using Worked Examples for Epistemic Programming}}},
  doi          = {{10.1145/3649902.3655094}},
  year         = {{2024}},
}

@inbook{56476,
  author       = {{Höper, Lukas and Schulte, Carsten and Benzmüller, Christoph}},
  booktitle    = {{Künstliche Intelligenz für Lehrkräfte}},
  editor       = {{Furbach, Ulrich and Kitzelmann, Emanuel and Michaeli, Tilman and Schmid, Ute}},
  isbn         = {{9783658442477}},
  issn         = {{2662-5970}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Verantwortung}}},
  doi          = {{10.1007/978-3-658-44248-4_16}},
  year         = {{2024}},
}

@article{49655,
  abstract     = {{In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This article addresses these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on the role of data in everyday life. The paper also presents an empirical study on young school students' data awareness. The study involves a teaching unit on data awareness framed by a pretest-posttest design using a questionnaire on students' awareness and understanding of and reflection on data practices of data-driven digital artefacts. The study's findings indicate that the data awareness framework supports students in understanding data practices of data-driven digital artefacts. The findings also suggest that the framework encourages students to reflect on these data practices and think about their daily behaviour. Students learn a model about interactions with data-driven digital artefacts and use it to analyse data-driven applications. This approach appears to enable students to understand these artefacts from everyday life and reflect on these interactions. The work contributes to research on data and AI literacies and suggests a way to support students in developing self-determination and agency during interactions with data-driven digital artefacts.}},
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{2398-5348}},
  journal      = {{Information and Learning Sciences}},
  keywords     = {{Library and Information Sciences, Computer Science Applications, Education}},
  number       = {{7/8}},
  pages        = {{491--512}},
  publisher    = {{Emerald}},
  title        = {{{The data awareness framework as part of data literacies in K-12 education}}},
  doi          = {{10.1108/ils-06-2023-0075}},
  volume       = {{125}},
  year         = {{2024}},
}

@article{53622,
  abstract     = {{<jats:p>In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life and developing agency in a digital world. This paper presents a qualitative study that explores students’ perspectives on the relevance of learning concepts of data-driven technologies for navigating the digital world. The underlying approach of the study is data awareness, which aims to support students in understanding and reflecting on such technologies to develop agency in a data-driven world. This approach teaches students an explanatory model encompassing several concepts of the role of data in data-driven technologies. We developed an intervention and conducted retrospective interviews with students. Findings from the analysis of the interviews indicate that students can analyse and understand data-driven technologies from their everyday lives according to the central role of data. In addition, students’ answers revealed four areas of how learning about data-driven technologies becomes relevant to them. The paper concludes with a preliminary model suggesting how computing education can make concepts of data-driven technologies meaningful for students to understand and navigate the digital world.</jats:p>}},
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{1648-5831}},
  journal      = {{Informatics in Education}},
  keywords     = {{Computer Science Applications, Communication, Education, General Engineering}},
  publisher    = {{Vilnius University Press}},
  title        = {{{Empowering Students for the Data-Driven World: A Qualitative Study of the Relevance of Learning about Data-Driven Technologies}}},
  doi          = {{10.15388/infedu.2024.19}},
  year         = {{2024}},
}

@inproceedings{57209,
  author       = {{Höper, Lukas and Schulte, Carsten}},
  booktitle    = {{Proceedings of the 24th Koli Calling International Conference on Computing Education Research}},
  location     = {{Koli, Finnland}},
  publisher    = {{ACM}},
  title        = {{{New Perspectives on the Future of Computing Education: Teaching and Learning Explanatory Models}}},
  doi          = {{10.1145/3699538.3699558}},
  year         = {{2024}},
}

@inproceedings{55481,
  author       = {{Höper, Lukas and Schulte, Carsten and Mühling, Andreas}},
  booktitle    = {{Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1}},
  location     = {{Mailand, Italien}},
  publisher    = {{ACM}},
  title        = {{{Students' Motivation and Intention to Engage with Data-Driven Technologies from a CS Perspective in Everyday Life}}},
  doi          = {{10.1145/3649217.3653625}},
  year         = {{2024}},
}

@inproceedings{55656,
  author       = {{Höper, Lukas and Schulte, Carsten and Mühling, Andreas}},
  booktitle    = {{Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1}},
  publisher    = {{ACM}},
  title        = {{{Learning an Explanatory Model of Data-Driven Technologies can Lead to Empowered Behavior: A Mixed-Methods Study in K-12 Computing Education}}},
  doi          = {{10.1145/3632620.3671118}},
  volume       = {{10}},
  year         = {{2024}},
}

@inproceedings{57356,
  author       = {{Schaffer, Michael Erol  and Terfloth, Lutz and Schulte, Carsten and Buhl, Heike M.}},
  location     = {{Valletta, Malta}},
  title        = {{{Perception and Consideration of the Explainees’ Needs for Satisfying Explanations}}},
  year         = {{2024}},
}

@inproceedings{57357,
  author       = {{Schaffer, Michael Erol  and Terfloth, Lutz and Schulte, Carsten and Buhl, Heike M.}},
  booktitle    = {{Joint Proceedings of the xAI-2024 Late-breaking Work, Demos and Doctoral Consortium. 3793}},
  title        = {{{Explainers’ Mental Representations of Explainees’ Needs in Everyday Explanations}}},
  year         = {{2024}},
}

@inbook{58216,
  abstract     = {{AnnoPy ist ein digitales Werkzeug, das an der Universität Paderborn in einer interdisziplinären Kooperation zwischen der Germanistischen Sprachdidaktik, Mathematikdidaktik und Informatikdidaktik entwickelt wurde, um wissenschaftliche Textkompetenzen zu fördern. Es kann in Präsenz- oder Blended-Learning-Szenarien eingesetzt werden, um eine Brücke zwischen individueller Auseinandersetzung mit dem Text und dessen sozial-diskursiver Aushandlung zu schlagen. Im Beitrag werden unterschiedliche Einsatzszenarien aus den drei beteiligten Disziplinen exemplarisch dargestellt, die jeweils unterschiedliche Facetten wissenschaftlicher Textkompetenz in den Mittelpunkt stellen. Im Fokus stehen dabei insbesondere die Förderung fachspezifischer Lesekompetenz im Rahmen einer Vorlesung mit großen Teilnehmendenzahlen sowie die Anwendung fachspezifischer Theorien und Konzepte in der Erschließung, Analyse und Beurteilung von Texten.}},
  author       = {{Rezat, Sebastian and Rezat, Sara and Scholle, Oliver and Schulte, Carsten and Winkelnkemper, Felix}},
  booktitle    = {{Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven}},
  editor       = {{Herzig, Bardo and Eickelmann, Birgit and Schwabl, Franziska and Schulze, Johanna and Niemann, Jan}},
  isbn         = {{9783830948377}},
  keywords     = {{digitale Medien, wissenschaftliche Textkompetenz, Lehrkonzept}},
  pages        = {{219–230}},
  publisher    = {{Waxmann}},
  title        = {{{AnnoPy. Fachspezifische wissenschaftliche Textkompetenzen mit digitalen Medien in der Lehre fördern}}},
  doi          = {{10.31244/9783830998372}},
  year         = {{2024}},
}

@inproceedings{52380,
  author       = {{Sparmann, Sören and Hüsing, Sven and Schulte, Carsten}},
  booktitle    = {{Proceedings of the 23rd Koli Calling International Conference on Computing Education Research}},
  publisher    = {{ACM}},
  title        = {{{JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks}}},
  doi          = {{10.1145/3631802.3631824}},
  year         = {{2023}},
}