@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 = {{2024}}, } @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}}, } @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 = {{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.}}, 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}}, } @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}}, publisher = {{Emerald}}, title = {{{The data awareness framework as part of data literacies in K-12 education}}}, doi = {{10.1108/ils-06-2023-0075}}, 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{31407, abstract = {{Students are not aware and have little understanding of collecting and processing personal data in their everyday contexts of interaction with data-driven digital artifacts. To be aware of where, how and why data are collected and processed is important to be self-determined. Therefore, we develop and evaluate a teaching sequence to provide reasoning about data as a fundamental aspect of statistical literacy. This teaching sequences deals with the context of interaction with a cellular network where location data are collected. Students get real location data from an unknown person which can be explored with the aim to characterize the person. Students gain different insights by using different basic filters and explain how they achieve these. The results of the exploratory study indicate that students learned to gain insights by exploring given location data and that these insights may describe the person with detailed aspects that may not necessarily be true.}}, author = {{Höper, Lukas and Podworny, Susanne and Schulte, Carsten and Frischemeier, Daniel}}, booktitle = {{Proceedings of the IASE 2021 Satellite Conference}}, publisher = {{International Association for Statistical Education}}, title = {{{Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network}}}, doi = {{10.52041/iase.nkppy}}, 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}}, } @inproceedings{40510, abstract = {{Decision-making processes are often based on data and data-driven machine learning methods in different areas such as recommender systems, medicine, criminalistics, etc. Well-informed citizens need at least a minimal understanding and critical reflection of corresponding data-driven machine learning methods. Decision trees are a method that can foster a preformal understanding of machine learning. We developed an exploratory teaching unit introducing decision trees in grade 6 along the question “How can Artificial Intelligence help us decide whether food is rather recommendable or not?” Students’ performances in an assessment task and self-assessment show that young learners can use a decision tree to classify new items and that they found the corresponding teaching unit informative.}}, author = {{Podworny, Susanne and Fleischer, Yannik and Hüsing, Sven}}, booktitle = {{Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics}}, publisher = {{International Association for Statistical Education}}, title = {{{Grade 6 Students’ Perception and Use of Data-Based Decision Trees}}}, doi = {{10.52041/iase.icots11.t2h3}}, year = {{2022}}, } @inproceedings{35674, abstract = {{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.}}, author = {{Fleischer, 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}}, } @inproceedings{30937, abstract = {{Data Science has become an increasingly important aspect of our everyday lives as we gain a lot of different insights from data analyses, for example in the context of environmental issues. In order to make the process of data analyses comprehensible for lower secondary school students, we developed a data analysis project for computer science classes, focusing on gaining insights from environmental data by using the concept of epistemic programming. In this article, we report on the second implementation of this project, which was conducted in a ninth-grade computer science class. Concretely, we want to examine, how far the students were able to create computational essays to conduct reproducible data analyses on their own. In this regard, the computational essays created with the help of the professional tool Jupyter Notebooks will be examined in terms of aspects of reproducibility.}}, author = {{Hüsing, Sven and Podworny, Susanne}}, booktitle = {{Proceedings of the IASE 2021 Satellite Conference}}, publisher = {{International Association for Statistical Education}}, title = {{{Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School}}}, doi = {{10.52041/iase.zwwoh}}, year = {{2022}}, } @article{35672, abstract = {{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.}}, author = {{Fleischer, 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}}, } @proceedings{25521, editor = {{Schulte, Carsten and A. Becker, Brett and Divitini, Monica and Barendsen, Erik}}, isbn = {{978-1-4503-8397-4}}, publisher = {{ACM}}, title = {{{ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021 - Working Group Reports}}}, doi = {{10.1145/3456565}}, year = {{2021}}, } @proceedings{25522, editor = {{Schulte, Carsten and A. Becker, Brett and Divitini, Monica and Barendsen, Erik}}, isbn = {{978-1-4503-8214-4}}, publisher = {{ACM}}, title = {{{ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021}}}, doi = {{10.1145/3430665}}, year = {{2021}}, } @inproceedings{25523, author = {{Podworny, Susanne and Höper, Lukas and Fleischer, Yannik and Hüsing, Sven and Schulte, Carsten}}, booktitle = {{19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021}}, editor = {{Humbert, Ludger}}, pages = {{327}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Data Science ab Klasse 5 - Konkrete Unterrichtsvorschläge für künstliche Intelligenz unplugged und Datenbewusstsein}}}, doi = {{10.18420/infos2021\_w278}}, volume = {{{P-313}}, year = {{2021}}, } @inproceedings{25524, author = {{Höper, Lukas and Schulte, Carsten}}, booktitle = {{19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021}}, editor = {{Humbert, Ludger}}, pages = {{73--82}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Datenbewusstsein: Aufmerksamkeit für die eigenen Daten}}}, doi = {{10.18420/infos2021\_f235}}, volume = {{P-313}}, year = {{2021}}, } @inproceedings{25525, author = {{Große-Bölting, Gregor and Gerstenberger, Dietrich Karl-Heinz and Gildehaus, Lara and Mühling, Andreas and Schulte, Carsten}}, booktitle = {{ICER 2021: ACM Conference on International Computing Education Research, Virtual Event, USA, August 16-19, 2021}}, editor = {{J. Ko, Amy and Vahrenhold, Jan and McCauley, René and Hauswirth, Matthias}}, pages = {{169--183}}, publisher = {{ACM}}, title = {{{Identity in K-12 Computer Education Research: A Systematic Literature Review}}}, doi = {{10.1145/3446871.3469757}}, year = {{2021}}, } @article{25527, author = {{Schulte, Carsten and A. Becker, Brett}}, journal = {{ACM SIGCSE Bull.}}, number = {{3}}, pages = {{3--4}}, title = {{{ITiCSE 2021 recap}}}, doi = {{10.1145/3483403.3483405}}, volume = {{53}}, year = {{2021}}, } @inproceedings{27491, abstract = {{ Students often have a lack of understanding and awareness of where, how, and why personal data about them is collected and processed. Especially, when interacting with data-driven digital artifacts, an appropriate perception of the data collection and processing is necessary for self-determination. This dissertation deals with the development and evaluation of a concept called data awareness which aims to foster students’ self-determination interacting with data-driven digital artifacts.}}, author = {{Höper, Lukas}}, booktitle = {{21st Koli Calling International Conference on Computing Education Research}}, isbn = {{9781450384889}}, keywords = {{data awareness, machine learning, data science education, data-driven digital artifacts, artificial intelligence}}, publisher = {{Association for Computing Machinery}}, title = {{{Developing and Evaluating the Concept Data Awareness for K12 Computing Education}}}, doi = {{10.1145/3488042.3490509}}, year = {{2021}}, } @inproceedings{27493, author = {{Podworny, Susanne and Fleischer, Yannik and Hüsing, Sven and Biehler, Rolf and Frischemeier, Daniel and Höper, Lukas and Schulte, Carsten}}, booktitle = {{Koli Calling '21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021}}, editor = {{Seppälä, Otto and Petersen, Andrew}}, pages = {{39:1--39:3}}, publisher = {{ACM}}, title = {{{Using data cards for teaching data based decision trees in middle school}}}, doi = {{10.1145/3488042.3489966}}, year = {{2021}}, } @inproceedings{27494, author = {{Hüsing, Sven}}, booktitle = {{Koli Calling '21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021}}, editor = {{Seppälä, Otto and Petersen, Andrew}}, pages = {{42:1--42:3}}, publisher = {{ACM}}, title = {{{Epistemic Programming - An insight-driven programming concept for Data Science}}}, doi = {{10.1145/3488042.3490510}}, year = {{2021}}, } @inproceedings{27495, author = {{Bovermann, Klaus and Fleischer, Yannik and Hüsing, Sven and Opitz, Christian}}, booktitle = {{19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021}}, editor = {{Humbert, Ludger}}, pages = {{319}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Künstliche Intelligenz und maschinelles Lernen im Informatikunterricht der Sek. I mit Jupyter Notebooks und Python am Beispiel von Entscheidungsbäumen und künstlichen neuronalen Netzen}}}, doi = {{10.18420/infos2021\_w283}}, volume = {{P-313}}, year = {{2021}}, } @inproceedings{29706, author = {{Höper, Lukas and Schulte, Carsten}}, booktitle = {{51. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2021 - Computer Science & Sustainability, Berlin, Germany, 27. September - 1. Oktober, 2021}}, isbn = {{978-3-88579-708-1}}, location = {{Bonn}}, pages = {{1623--1632}}, publisher = {{Gesellschaft für Informatik}}, title = {{{Datenbewusstsein im Kontext digitaler Kompetenzen für einen selbstbestimmten Umgang mit datengetriebenen digitalen Artefakten}}}, doi = {{10.18420/informatik2021-136}}, year = {{2021}}, } @article{29702, author = {{Höper, Lukas and Hüsing, Sven and Malatyali, Hülya and Schulte, Carsten and Budde, Lea}}, journal = {{LOG IN}}, number = {{1}}, pages = {{31--38}}, publisher = {{LOG IN Verlag}}, title = {{{Methodik für Datenprojekte im Informatikunterricht}}}, volume = {{41}}, year = {{2021}}, } @inproceedings{29707, author = {{Bechinie, Dominik and Eilerts, Katja and Huhmann, Tobias and Lenke, Michael and Schulte, Carsten and Winkelnkemper, Felix}}, booktitle = {{Beiträge zum Mathematikunterricht 2021}}, publisher = {{WTM Verlag, Münster}}, title = {{{Geometrielernen digital unterstützen - Räumliche Kompetenzen und individuelle Lernwege mittels adaptierbarer algorithmischer Rückmeldemöglichkeiten fördern}}}, year = {{2021}}, } @article{29708, author = {{Gerstenberger, Dietrich Karl-Heinz and Winkelnkemper, Felix and Schulte, Carsten}}, journal = {{9. Fachtagung Hochschuldidaktik Informatik (HDI)}}, pages = {{49}}, title = {{{Nutzung der Personas-Methode zum Umgang mit der Heterogenität von Informatik-Studierenden}}}, year = {{2021}}, } @inproceedings{25520, author = {{Höper, Lukas and Podworny, Susanne and Hüsing, Sven and Schulte, Carsten and Fleischer, Yannik and Biehler, Rolf and Frischemeier, Daniel and Malatyali, Hülya}}, booktitle = {{19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021}}, editor = {{Humbert, Ludger}}, isbn = {{978-3-88579-707-4}}, pages = {{345}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz}}}, doi = {{10.18420/infos2021\_a230}}, volume = {{P-313}}, year = {{2021}}, } @phdthesis{27499, author = {{Budde, Lea}}, publisher = {{University of Paderborn, Germany}}, title = {{{Entwicklung und Rekonstruktion einer interaktionsgeprägten Sichtweise auf das komplementäre Mensch-Maschine-Verhältnis}}}, year = {{2021}}, } @inbook{29720, author = {{Passey, Don and Brinda, Torsten and Cornu, Bernard and Holvikivi, Jaana and Lewin, Cathy and Magenheim, Johannes and Morel, Raymond and Osorio, Javier and Tatnall, Arthur and Thompson, Barrie and Webb, Mary}}, booktitle = {{Advancing Research in Information and Communication Technology}}, editor = {{Goedicke, Michael and Neuhold, Erich and Rannenberg, Kai}}, isbn = {{978-3-030-81700-8}}, issn = {{1868-422X}}, keywords = {{Educational technologies, Education and technologies, Digital technologies and education, Information technologies, Communication technologies, Educational technologies and research, Educational technologies and pedagogical practices, Educational technologies and policy, Educational management and technologies, Professional development and educational technologies}}, pages = {{129--152}}, publisher = {{Springer, Cham}}, title = {{{Computers and Education – Recognising Opportunities and Managing Challenges}}}, doi = {{10.1007/978-3-030-81701-5_5}}, volume = {{AICT-600}}, year = {{2021}}, } @article{29710, author = {{Podworny, Susanne and Höper, Lukas and Fleischer, Yannik and Hüsing, Sven and Schulte, Carsten}}, journal = {{INFOS 2021–19. GI-Fachtagung Informatik und Schule}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Data Science ab Klasse 5–Konkrete Unterrichtsvorschläge für künstliche Intelligenz unplugged und Datenbewusstsein}}}, year = {{2021}}, } @article{29712, author = {{Höper, Lukas and Podworny, Susanne and Hüsing, Sven and Schulte, Carsten and Fleischer, Yannik and Biehler, Rolf and Frischemeier, Daniel and Malatyali, Hülya}}, journal = {{INFOS 2021–19. GI-Fachtagung Informatik und Schule}}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz}}}, year = {{2021}}, } @article{40512, author = {{Hüsing, Sven and Weiser, Niklas and Biehler, Rolf}}, journal = {{mathematik lehren}}, number = {{228}}, pages = {{23–27}}, publisher = {{Friedrich Verlag}}, title = {{{Faszination 3D-Film: Entwicklung einer 3D-Konstruktion}}}, volume = {{2021}}, year = {{2021}}, } @article{24456, abstract = {{One objective of current research in explainable intelligent systems is to implement social aspects in order to increase the relevance of explanations. In this paper, we argue that a novel conceptual framework is needed to overcome shortcomings of existing AI systems with little attention to processes of interaction and learning. Drawing from research in interaction and development, we first outline the novel conceptual framework that pushes the design of AI systems toward true interactivity with an emphasis on the role of the partner and social relevance. We propose that AI systems will be able to provide a meaningful and relevant explanation only if the process of explaining is extended to active contribution of both partners that brings about dynamics that is modulated by different levels of analysis. Accordingly, our conceptual framework comprises monitoring and scaffolding as key concepts and claims that the process of explaining is not only modulated by the interaction between explainee and explainer but is embedded into a larger social context in which conventionalized and routinized behaviors are established. We discuss our conceptual framework in relation to the established objectives of transparency and autonomy that are raised for the design of explainable AI systems currently.}}, author = {{Rohlfing, Katharina J. and Cimiano, Philipp and Scharlau, Ingrid and Matzner, Tobias and Buhl, Heike M. and Buschmeier, Hendrik and Esposito, Elena and Grimminger, Angela and Hammer, Barbara and Haeb-Umbach, Reinhold and Horwath, Ilona and Hüllermeier, Eyke and Kern, Friederike and Kopp, Stefan and Thommes, Kirsten and Ngonga Ngomo, Axel-Cyrille and Schulte, Carsten and Wachsmuth, Henning and Wagner, Petra and Wrede, Britta}}, issn = {{2379-8920}}, journal = {{IEEE Transactions on Cognitive and Developmental Systems}}, keywords = {{Explainability, process ofexplaining andunderstanding, explainable artificial systems}}, number = {{3}}, pages = {{717--728}}, title = {{{Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems}}}, doi = {{10.1109/tcds.2020.3044366}}, volume = {{13}}, year = {{2021}}, } @inbook{21268, author = {{Huhmann, Tobias and Eilterts, Katja and Schulte, Carsten and Winkelnkemper, Felix}}, booktitle = {{Digitales Lernen in der Grundschule II: Aktuelle Trends in Forschung und Praxis}}, publisher = {{Waxmann Verlag}}, title = {{{Der Darstellungsflüchtigkeit im Geometrieunterricht durch digitale Unterstützung entgegenwirken}}}, year = {{2020}}, } @inproceedings{20335, author = {{Winkelnkemper, Felix and Schulte, Carsten and Eilerts, Katja and Bechinie, Dominik and Huhmann, Tobias}}, booktitle = {{EdMedia+ Innovate Learning}}, pages = {{522--529}}, title = {{{The Interdisciplinary Development of an Educational Game for Primary School Children--Lessons Learned}}}, year = {{2020}}, } @inproceedings{20452, abstract = {{In this paper, we present a novel approach to design teaching interventions for computing education, elaborated using an example of cybersecurity education. Cybersecurity education, similar to other computing education domains, often focuses on one aspect and separate themselves from the other approach. In other words, they focus on one of the two different aspects: a) either teaching how to use and to behave, or b) how technology works. Here we suggest another point of focal awareness for teaching – interaction – that allows the recombination of both approaches in a novel way, leading to a reconstruction of the teaching and learning content in a way that – as we hope – supports an understanding on a higher level and thus gives the chance to better develop agency. For this didactic reconstruction of teaching content, we use an approach called the hybrid interaction system framework. In cybersecurity training, teaching interventions oftentimes are in a way successful but seem to not lead to long-lasting changes towards secure behavior. Using simply password security as an example, we show how this new approach recombines the two different priory mentioned teaching approaches in a novel way. Within this short paper, we present our current research progress, discuss potentials and values of the approach in general, and by way of example. Our intention of this submission and early disclosure is to spark discussion and generate further insights especially regarding the following question: What implications does the hybrid interaction system approach have on learning scenarios?}}, author = {{Terfloth, Lutz and Budde, Lea and Schulte, Carsten}}, isbn = {{9781450389211}}, publisher = {{Association for Computing Machinery}}, title = {{{Combining Ideas and Artifacts: An Interaction-Focused View on Computing Education Using a Cybersecurity Example}}}, doi = {{10.1145/3428029.3428052}}, year = {{2020}}, } @article{20834, author = {{Webb, Mary E and Fluck, Andrew and Magenheim, Johannes and Malyn-Smith, Joyce and Waters, Juliet and Deschênes , Michelle and Zagami, Jason}}, journal = {{Educational Technology Research and Development}}, pages = {{1--22}}, publisher = {{Springer}}, title = {{{Machine learning for human learners: opportunities, issues, tensions and threats}}}, doi = {{10.1007/s11423-020-09858-2}}, year = {{2020}}, } @article{20835, author = {{Magenheim, Johannes}}, journal = {{MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung}}, pages = {{139--163}}, title = {{{< Big Data> aus der Perspektive von Informatischer Bildung und Medienpädagogik}}}, doi = {{10.21240/mpaed/37/2020.07.08.X}}, volume = {{37}}, year = {{2020}}, } @article{20836, author = {{Magenheim, Johannes and Schulte, Carsten}}, journal = {{Encyclopedia of Education and Information Technologies. Cham: Springer}}, title = {{{Data science education}}}, doi = {{10.1007/978-3-030-10576-1_253}}, year = {{2020}}, } @inbook{20840, author = {{Schulte, Carsten and Budde, Lea and Winkelnkemper, Felix}}, booktitle = {{Mobile Medien im Schulkontext}}, pages = {{215--240}}, publisher = {{Springer}}, title = {{{Programmieren - Lehren und Lernen mit und über Medien}}}, doi = {{10.1007/978-3-658-29039-9}}, year = {{2020}}, } @inproceedings{29298, abstract = {{Die Themen „Big Data“, „Künstliche Intelligenz und „Data Science“ werden seit einiger Zeit nicht nur in der breiten Öffentlichkeit kontrovers diskutiert, sondern stellen für die Ausbildung in den IT- und IT-nahen Berufen schon heute neue Herausforderungen dar, die in Zukunft durch die gesellschaftliche und technologische Weiterentwicklung hin zu einer Datengesellschaft noch größer werden. An dieser Stelle stellt sich die Frage, welche Aspekte dieses großen Themenkomplexes für Schule und Ausbildung von Wichtigkeit sind und wie diese Themen sinnstiftend und gewinnbringend in die informatische Ausbildung in verschiedenen Bildungsgängen integriert werden können. Im Rahmen des von uns im Jahr 2017 organisierten Symposiums zum Thema „Data Science“ wurden für die Bildung relevante Aspekte erörtert, wodurch als Kernelemente für den Unterricht Algorithmen der Künstlichen Intelligenz und ihre Anwendung in Industrie und Gesellschaft, Explorationen von Big Data sowie der Umgang mit eigenen Daten in sozialen Netzwerken herausgearbeitet wurden. Ziel ist, aus diesen Themenbereichen sowohl ein umfassendes Curriculum als auch Module für verschiedene Unterrichtsszenarien zu entwickeln und zu erproben. Durch diese Materialien soll es Lehrkräften aus der Informatik, Mathematik oder Technik ermöglicht werden, diese Themen auf Basis des Curriculums und der erprobten Unterrichtskonzepte selbst zu unterrichten. Hierfür wurde im Rahmen des Projekts ProDaBi (Projekt Data Science und Big Data in der Schule, https://www.prodabi.de), initiiert von der Telekom Stiftung, ein experimenteller Projektkurs entwickelt, den wir mit Schüler:innen der Sekundarstufe II an der Universität Paderborn im Schuljahr 2018/19 durchführten. Dieser Kurs enthält neben einem Modul zur Exploration von Big Data und einem weiteren Modul zum Maschinellen Lernen als Teil der Künstlichen Intelligenz auch eine Projektphase, die es in Zusammenarbeit mit lokalen Unternehmen den Schüler:innen ermöglicht, das Erlernte in ein reales Data Science-Projekt einzubringen. Aus den Erfahrungen dieses Projektkurses sowie den parallel durchgeführten Erprobungen einzelner Bausteine auch mit beruflichen Schulen werden ab dem Schuljahr 2019/20 die hierfür verwendeten Materialien weiterentwickelt und weiteren Kooperationspartnern zur Erprobung zur Verfügung gestellt. Damit wurden zum Ende des Projekts nicht nur vollständige Unterrichtsmaterialien, sondern auch ein umfassendes Curriculum entwickelt.}}, author = {{Opel, Simone Anna and Schlichtig, Michael}}, booktitle = {{Sammelband der 27. Fachtagung der BAG Berufliche Bildung}}, editor = {{Vollmer, Thomas and Karges, Torben and Richter, Tim and Schlömer, Britta and Schütt-Sayed, Sören}}, keywords = {{Berufsbildung, vocational education, Ausbildung, training, berufliche Weiterbildung, advanced vocational education, Digitalisierung, digitalization, Unterricht, teaching, Lehrmethode, teaching method, Interdisziplinarität, interdisciplinarity, Fachdidaktik, subject didactics, Curriculum, curriculum, gewerblich-technischer Beruf, vocational/technical occupation, Fachkraft, specialist, Qualifikationsanforderungen, qualification requirements, Kompetenz, competence, Lehrerbildung, teacher training, Bundesrepublik Deutschland, Federal Republic of Germany}}, location = {{Siegen}}, pages = {{176--194}}, publisher = {{wbv Media GmbH & Co. KG}}, title = {{{Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II}}}, doi = {{https://doi.org/10.3278/6004722w}}, volume = {{55}}, year = {{2020}}, } @article{21267, author = {{Budde, Lea and Schulte, Carsten and Buhl, Heike M. and Muehling, Andreas}}, journal = {{Seventh International Conference on Learning and Teaching in Computing and Engineeringe}}, keywords = {{⛔ No DOI found}}, publisher = {{(IEEE)}}, title = {{{Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows)}}}, year = {{2020}}, } @inproceedings{15578, author = {{Izu, Cruz and Schulte, Carsten and Aggarwal, Ashish and I. Cutts, Quintin and Duran, Rodrigo and Gutica, Mirela and Heinemann, Birte and Kraemer, Eileen and Lonati, Violetta and Mirolo, Claudio and Weeda, Renske}}, booktitle = {{Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019}}, pages = {{261--262}}, title = {{{Program Comprehension: Identifying Learning Trajectories for Novice Programmers}}}, doi = {{10.1145/3304221.3325531}}, year = {{2019}}, } @inproceedings{15579, author = {{Kapp, Florian and Schulte, Carsten}}, booktitle = {{Informatik für alle, 18. GI-Fachtagung Informatik und Schule, (INFOS) 2019, 16.-18. September 2019, Dortmund}}, pages = {{247--256}}, title = {{{Einsatz von Jupyter Notebooks am Beispiel eines fiktiven Kriminalfalls}}}, doi = {{10.18420/infos2019-c10}}, year = {{2019}}, } @inproceedings{15581, author = {{Müller, Kathrin and Schulte, Carsten and Magenheim, Johannes}}, booktitle = {{Informatik für alle, 18. GI-Fachtagung Informatik und Schule, (INFOS) 2019, 16.-18. September 2019, Dortmund}}, pages = {{139--148}}, title = {{{Zur Relevanz eines Prozessbereiches Interaktion und Exploration im Kontext informatischer Bildung im Primarbereich}}}, doi = {{10.18420/infos2019-b10}}, year = {{2019}}, }