@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{57738,
  author       = {{Hüsing, Sven and Schönbrodt, Sarah}},
  title        = {{{Förderung von Epistemic Agency – Entwicklung von Computational Essays bei der Bearbeitung datengetriebener, realer Problemstellungen}}},
  doi          = {{10.17877/DE290R-25018}},
  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}},
}

@inbook{40511,
  author       = {{Hüsing, Sven and Schulte, Carsten and Winkelnkemper, Felix}},
  booktitle    = {{Computer Science Education}},
  isbn         = {{9781350296916}},
  publisher    = {{Bloomsbury Academic}},
  title        = {{{Epistemic Programming}}},
  doi          = {{10.5040/9781350296947.ch-022}},
  year         = {{2023}},
}

@article{46186,
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{0025-5866}},
  journal      = {{MNU journal}},
  number       = {{4}},
  pages        = {{314--320}},
  publisher    = {{Verlag Klaus Seeberger}},
  title        = {{{Paradigmenwechsel vom klassischen zum datengetriebenen Problemlösen im Informatikunterricht}}},
  volume       = {{76}},
  year         = {{2023}},
}

@article{47151,
  abstract     = {{<jats:p>When it comes to mastering the digital world, the education system is more and more facing the task of making students competent and self-determined agents when interacting with digital artefacts. This task often falls to computing education. In the traditional fields of computing education, a plethora of models, guidelines, and principles exist, which help scholars and teachers identify what the relevant aspects are and which of them one should cover in the classroom. When it comes to explaining the world of digital artefacts, however, there is hardly any such guiding model. The ARIadne model introduced in this paper provides a means of explanation and exploration of digital artefacts which help teachers and students to do a subject analysis of digital artefacts by scrutinizing them from several perspectives. Instead of artificially separating aspects which target the same phenomena within different areas of education (like computing, ICT or media education), the model integrates technological aspects of digital artefacts and the relevant societal discourses of their usage, their impacts and the reasons behind their development into a coherent explanation model.</jats:p>}},
  author       = {{Winkelnkemper, Felix and 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        = {{{ARIadne – An Explanation Model for Digital Artefacts}}},
  doi          = {{10.15388/infedu.2024.09}},
  year         = {{2023}},
}

@inproceedings{47448,
  abstract     = {{In XAI it is important to consider that, in contrast to explanations for professional audiences, one cannot assume common expertise when explaining for laypeople. But such explanations between humans vary greatly, making it difficult to research commonalities across explanations. We used the dual nature theory, a techno-philosophical approach, to cope with these challenges. According to it, one can explain, for example, an XAI's decision by addressing its dual nature: by focusing on the Architecture (e.g., the logic of its algorithms) or the Relevance (e.g., the severity of a decision, the implications of a recommendation). We investigated 20 game explanations using the theory as an analytical framework. We elaborate how we used the theory to quickly structure and compare explanations of technological artifacts. We supplemented results from analyzing the explanation contents with results from a video recall to explore how explainers justified their explanation. We found that explainers were focusing on the physical aspects of the game first (Architecture) and only later on aspects of the Relevance. Reasoning in the video recalls indicated that EX regarded the focus on the Architecture as important for structuring the explanation initially by explaining the basic components before focusing on more complex, intangible aspects. Shifting between addressing the two sides was justified by explanation goals, emerging misunderstandings, and the knowledge needs of the explainee. We discovered several commonalities that inspire future research questions which, if further generalizable, provide first ideas for the construction of synthetic explanations.}},
  author       = {{Terfloth, Lutz and Schaffer, Michael and Buhl, Heike M. and Schulte, Carsten}},
  isbn         = {{978-3-031-44069-4}},
  location     = {{Lisboa}},
  publisher    = {{Springer, Cham}},
  title        = {{{Adding Why to What? Analyses of an Everyday Explanation}}},
  doi          = {{10.1007/978-3-031-44070-0_13}},
  year         = {{2023}},
}

@article{32335,
  abstract     = {{Aspects of data science surround us in many contexts, for example regarding climate change, air pollution, and other environmental issues. To open the “data-science-black-box” for lower secondary school students we developed a data science project focussing on the analysis of self-collected environmental data. We embed this project in computer science education, which enables us to use a new knowledge-based programming approach for the data analysis within Jupyter Notebooks and the programming language Python. In this paper, we evaluate the second cycle of this project which took place in a ninth-grade computer science class. In particular, we present how the students coped with the professional tool of Jupyter Notebooks for doing statistical investigations and which insights they gained.}},
  author       = {{PODWORNY, SUSANNE and Hüsing, Sven and SCHULTE, CARSTEN}},
  issn         = {{1570-1824}},
  journal      = {{STATISTICS EDUCATION RESEARCH JOURNAL}},
  keywords     = {{Education, Statistics and Probability}},
  number       = {{2}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}}},
  doi          = {{10.52041/serj.v21i2.46}},
  volume       = {{21}},
  year         = {{2022}},
}

@inproceedings{35674,
  abstract     = {{<jats:p>We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.</jats:p>}},
  author       = {{Fleischer, Franz Yannik and Hüsing, Sven and Biehler, Rolf and Podworny, Susanne and Schulte, Carsten}},
  booktitle    = {{Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics}},
  editor       = {{Peters, S. A. and Zapata-Cardona, L. and Bonafini, F. and Fan, A.}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{Jupyter Notebooks for Teaching, Learning, and Doing Data Science}}},
  doi          = {{10.52041/iase.icots11.t10e3}},
  year         = {{2022}},
}

@article{35672,
  abstract     = {{<jats:p>This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students’ work is based on a teaching module about decision trees in machine learning and a worked example of such a modelling process. The study outlines the students’ performance in carrying out the machine learning technically and reasoning about bias in the data, different data preparation steps, the application context, and the resulting decision model. Furthermore, the context of the study and the theoretical backgrounds are presented.</jats:p>}},
  author       = {{Fleischer, Franz Yannik and Biehler, Rolf and Schulte, Carsten}},
  issn         = {{1570-1824}},
  journal      = {{Statistics Education Research Journal}},
  keywords     = {{Education, Statistics and Probability}},
  number       = {{2}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks}}},
  doi          = {{10.52041/serj.v21i2.61}},
  volume       = {{21}},
  year         = {{2022}},
}

@inproceedings{38158,
  author       = {{Winkelnkemper, Felix and Huhmann, Tobias and Bechinie, Dominik and Eilerts, Katja and Lenke, Michael and Schulte, Carsten}},
  booktitle    = {{Society for Information Technology & Teacher Education International Conference}},
  keywords     = {{⛔ No DOI found}},
  pages        = {{1407–1413}},
  title        = {{{Supporting Geometry Learning Digitally-an Interdisciplinary Project to Foster Spatial Competences and Individual Learning Paths by Using Adaptable Algorithmic Feedback Capabilities}}},
  year         = {{2022}},
}

@inbook{39080,
  author       = {{Schulte, Carsten and Winkelnkemper, Felix}},
  booktitle    = {{Theologie im Übergang - Identität - Digitalisierung - Dialog}},
  pages        = {{117–135}},
  publisher    = {{Herder}},
  title        = {{{Digitalisierung als Chance und Herausforderung - Bemerkungen aus der Didaktik der Informatik}}},
  year         = {{2022}},
}

@inproceedings{38160,
  author       = {{Huhmann, Tobias and Winkelnkemper, Felix}},
  booktitle    = {{EDULEARN22 Proceedings}},
  pages        = {{10017–10026}},
  title        = {{{SUPPORTING GEOMETRY LEARNING DIGITALLY THROUGH ADAPTABLE ALGORITHMIC FEEDBACK-CHALLENGES AND SOLUTIONS}}},
  doi          = {{10.21125/edulearn.2022.2416}},
  year         = {{2022}},
}

@article{38162,
  author       = {{Huhmann, Tobias and Eilerts, Katja and Winkelnkemper, Felix}},
  journal      = {{Mathematik differenziert}},
  keywords     = {{⛔ No DOI found}},
  number       = {{4-2022}},
  pages        = {{42–45}},
  title        = {{{Pentomino Digital - Mit Einer App Geometrie Lernen}}},
  year         = {{2022}},
}