TY - CONF AU - Sparmann, Sören AU - Hüsing, Sven AU - Schulte, Carsten ID - 52380 T2 - Proceedings of the 23rd Koli Calling International Conference on Computing Education Research TI - JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks ER - TY - CONF AU - Hüsing, Sven AU - Schulte, Carsten AU - Sparmann, Sören AU - Bolte, Mario ID - 52379 T2 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 TI - Using Worked Examples for Engaging in Epistemic Programming Projects ER - TY - CHAP AU - Hüsing, Sven AU - Schulte, Carsten AU - Winkelnkemper, Felix ID - 40511 SN - 9781350296916 T2 - Computer Science Education TI - Epistemic Programming ER - TY - JOUR AU - Höper, Lukas AU - Schulte, Carsten ID - 46186 IS - 4 JF - MNU journal SN - 0025-5866 TI - Paradigmenwechsel vom klassischen zum datengetriebenen Problemlösen im Informatikunterricht VL - 76 ER - TY - JOUR AB - 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. AU - Winkelnkemper, Felix AU - Höper, Lukas AU - Schulte, Carsten ID - 47151 JF - Informatics in Education KW - Computer Science Applications KW - Communication KW - Education KW - General Engineering SN - 1648-5831 TI - ARIadne – An Explanation Model for Digital Artefacts ER - TY - JOUR AB - 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. AU - Höper, Lukas AU - Schulte, Carsten ID - 49655 JF - Information and Learning Sciences KW - Library and Information Sciences KW - Computer Science Applications KW - Education SN - 2398-5348 TI - The data awareness framework as part of data literacies in K-12 education ER - TY - CONF AB - 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. AU - Terfloth, Lutz AU - Schaffer, Michael AU - Buhl, Heike M. AU - Schulte, Carsten ID - 47448 SN - 978-3-031-44069-4 TI - Adding Why to What? Analyses of an Everyday Explanation ER - TY - JOUR AB - 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. AU - PODWORNY, SUSANNE AU - Hüsing, Sven AU - SCHULTE, CARSTEN ID - 32335 IS - 2 JF - STATISTICS EDUCATION RESEARCH JOURNAL KW - Education KW - Statistics and Probability SN - 1570-1824 TI - A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING VL - 21 ER - TY - CONF AB - 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. AU - Höper, Lukas AU - Podworny, Susanne AU - Schulte, Carsten AU - Frischemeier, Daniel ID - 31407 T2 - Proceedings of the IASE 2021 Satellite Conference TI - Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network ER - TY - CONF AU - Winkelnkemper, Felix AU - Huhmann, Tobias AU - Bechinie, Dominik AU - Eilerts, Katja AU - Lenke, Michael AU - Schulte, Carsten ID - 38158 KW - ⛔ No DOI found T2 - Society for Information Technology & Teacher Education International Conference TI - Supporting Geometry Learning Digitally-an Interdisciplinary Project to Foster Spatial Competences and Individual Learning Paths by Using Adaptable Algorithmic Feedback Capabilities ER - TY - CHAP AU - Schulte, Carsten AU - Winkelnkemper, Felix ID - 39080 T2 - Theologie im Übergang - Identität - Digitalisierung - Dialog TI - Digitalisierung als Chance und Herausforderung - Bemerkungen aus der Didaktik der Informatik ER - TY - CONF AU - Huhmann, Tobias AU - Winkelnkemper, Felix ID - 38160 T2 - EDULEARN22 Proceedings TI - SUPPORTING GEOMETRY LEARNING DIGITALLY THROUGH ADAPTABLE ALGORITHMIC FEEDBACK-CHALLENGES AND SOLUTIONS ER - TY - JOUR AU - Huhmann, Tobias AU - Eilerts, Katja AU - Winkelnkemper, Felix ID - 38162 IS - 4-2022 JF - Mathematik differenziert KW - ⛔ No DOI found TI - Pentomino Digital - Mit Einer App Geometrie Lernen ER - TY - CONF AB - 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. AU - Podworny, Susanne AU - Fleischer, Yannik AU - Hüsing, Sven ID - 40510 T2 - Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics TI - Grade 6 Students’ Perception and Use of Data-Based Decision Trees ER - TY - CONF AB - 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. AU - Fleischer, Yannik AU - Hüsing, Sven AU - Biehler, Rolf AU - Podworny, Susanne AU - Schulte, Carsten ED - Peters, S. A. ED - Zapata-Cardona, L. ED - Bonafini, F. ED - Fan, A. ID - 35674 T2 - Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics TI - Jupyter Notebooks for Teaching, Learning, and Doing Data Science ER - TY - CONF AB - 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. AU - Hüsing, Sven AU - Podworny, Susanne ID - 30937 T2 - Proceedings of the IASE 2021 Satellite Conference TI - Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School ER - TY - JOUR AB - 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. AU - Fleischer, Yannik AU - Biehler, Rolf AU - Schulte, Carsten ID - 35672 IS - 2 JF - Statistics Education Research Journal KW - Education KW - Statistics and Probability SN - 1570-1824 TI - Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks VL - 21 ER - TY - GEN ED - Schulte, Carsten ED - A. Becker, Brett ED - Divitini, Monica ED - Barendsen, Erik ID - 25521 SN - 978-1-4503-8397-4 TI - ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021 - Working Group Reports ER - TY - GEN ED - Schulte, Carsten ED - A. Becker, Brett ED - Divitini, Monica ED - Barendsen, Erik ID - 25522 SN - 978-1-4503-8214-4 TI - ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021 ER - TY - CONF AU - Podworny, Susanne AU - Höper, Lukas AU - Fleischer, Yannik AU - Hüsing, Sven AU - Schulte, Carsten ED - Humbert, Ludger ID - 25523 T2 - 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021 TI - Data Science ab Klasse 5 - Konkrete Unterrichtsvorschläge für künstliche Intelligenz unplugged und Datenbewusstsein VL - {P-313 ER - TY - CONF AU - Höper, Lukas AU - Schulte, Carsten ED - Humbert, Ludger ID - 25524 T2 - 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021 TI - Datenbewusstsein: Aufmerksamkeit für die eigenen Daten VL - P-313 ER - TY - CONF AU - Große-Bölting, Gregor AU - Gerstenberger, Dietrich Karl-Heinz AU - Gildehaus, Lara AU - Mühling, Andreas AU - Schulte, Carsten ED - J. Ko, Amy ED - Vahrenhold, Jan ED - McCauley, René ED - Hauswirth, Matthias ID - 25525 T2 - ICER 2021: ACM Conference on International Computing Education Research, Virtual Event, USA, August 16-19, 2021 TI - Identity in K-12 Computer Education Research: A Systematic Literature Review ER - TY - JOUR AU - Schulte, Carsten AU - A. Becker, Brett ID - 25527 IS - 3 JF - ACM SIGCSE Bull. TI - ITiCSE 2021 recap VL - 53 ER - TY - CONF AB - 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. AU - Höper, Lukas ID - 27491 KW - data awareness KW - machine learning KW - data science education KW - data-driven digital artifacts KW - artificial intelligence SN - 9781450384889 T2 - 21st Koli Calling International Conference on Computing Education Research TI - Developing and Evaluating the Concept Data Awareness for K12 Computing Education ER - TY - CONF AU - Podworny, Susanne AU - Fleischer, Yannik AU - Hüsing, Sven AU - Biehler, Rolf AU - Frischemeier, Daniel AU - Höper, Lukas AU - Schulte, Carsten ED - Seppälä, Otto ED - Petersen, Andrew ID - 27493 T2 - Koli Calling '21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021 TI - Using data cards for teaching data based decision trees in middle school ER - TY - CONF AU - Hüsing, Sven ED - Seppälä, Otto ED - Petersen, Andrew ID - 27494 T2 - Koli Calling '21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021 TI - Epistemic Programming - An insight-driven programming concept for Data Science ER - TY - CONF AU - Bovermann, Klaus AU - Fleischer, Yannik AU - Hüsing, Sven AU - Opitz, Christian ED - Humbert, Ludger ID - 27495 T2 - 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021 TI - Künstliche Intelligenz und maschinelles Lernen im Informatikunterricht der Sek. I mit Jupyter Notebooks und Python am Beispiel von Entscheidungsbäumen und künstlichen neuronalen Netzen VL - P-313 ER - TY - CONF AU - Höper, Lukas AU - Schulte, Carsten ID - 29706 SN - 978-3-88579-708-1 T2 - 51. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2021 - Computer Science & Sustainability, Berlin, Germany, 27. September - 1. Oktober, 2021 TI - Datenbewusstsein im Kontext digitaler Kompetenzen für einen selbstbestimmten Umgang mit datengetriebenen digitalen Artefakten ER - TY - JOUR AU - Höper, Lukas AU - Hüsing, Sven AU - Malatyali, Hülya AU - Schulte, Carsten AU - Budde, Lea ID - 29702 IS - 1 JF - LOG IN TI - Methodik für Datenprojekte im Informatikunterricht VL - 41 ER - TY - CONF AU - Bechinie, Dominik AU - Eilerts, Katja AU - Huhmann, Tobias AU - Lenke, Michael AU - Schulte, Carsten AU - Winkelnkemper, Felix ID - 29707 T2 - Beiträge zum Mathematikunterricht 2021 TI - Geometrielernen digital unterstützen - Räumliche Kompetenzen und individuelle Lernwege mittels adaptierbarer algorithmischer Rückmeldemöglichkeiten fördern ER - TY - JOUR AU - Gerstenberger, Dietrich Karl-Heinz AU - Winkelnkemper, Felix AU - Schulte, Carsten ID - 29708 JF - 9. Fachtagung Hochschuldidaktik Informatik (HDI) TI - Nutzung der Personas-Methode zum Umgang mit der Heterogenität von Informatik-Studierenden ER - TY - CONF AU - Höper, Lukas AU - Podworny, Susanne AU - Hüsing, Sven AU - Schulte, Carsten AU - Fleischer, Yannik AU - Biehler, Rolf AU - Frischemeier, Daniel AU - Malatyali, Hülya ED - Humbert, Ludger ID - 25520 SN - 978-3-88579-707-4 T2 - 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021 TI - Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz VL - P-313 ER - TY - THES AU - Budde, Lea ID - 27499 TI - Entwicklung und Rekonstruktion einer interaktionsgeprägten Sichtweise auf das komplementäre Mensch-Maschine-Verhältnis ER - TY - CHAP AU - Passey, Don AU - Brinda, Torsten AU - Cornu, Bernard AU - Holvikivi, Jaana AU - Lewin, Cathy AU - Magenheim, Johannes AU - Morel, Raymond AU - Osorio, Javier AU - Tatnall, Arthur AU - Thompson, Barrie AU - Webb, Mary ED - Goedicke, Michael ED - Neuhold, Erich ED - Rannenberg, Kai ID - 29720 KW - Educational technologies KW - Education and technologies KW - Digital technologies and education KW - Information technologies KW - Communication technologies KW - Educational technologies and research KW - Educational technologies and pedagogical practices KW - Educational technologies and policy KW - Educational management and technologies KW - Professional development and educational technologies SN - 978-3-030-81700-8 T2 - Advancing Research in Information and Communication Technology TI - Computers and Education – Recognising Opportunities and Managing Challenges VL - AICT-600 ER - TY - JOUR AU - Frischemeier, Daniel AU - Biehler, Rolf AU - Podworny, Susanne AU - Budde, Lea ID - 35751 IS - S1 JF - Teaching Statistics KW - Education KW - Statistics and Probability SN - 0141-982X TI - A first introduction to data science education in secondary schools: Teaching and learning about data exploration withCODAPusing survey data VL - 43 ER - TY - JOUR AU - Podworny, Susanne AU - Höper, Lukas AU - Fleischer, Yannik AU - Hüsing, Sven AU - Schulte, Carsten ID - 29710 JF - INFOS 2021–19. GI-Fachtagung Informatik und Schule TI - Data Science ab Klasse 5–Konkrete Unterrichtsvorschläge für künstliche Intelligenz unplugged und Datenbewusstsein ER - TY - JOUR AU - Höper, Lukas AU - Podworny, Susanne AU - Hüsing, Sven AU - Schulte, Carsten AU - Fleischer, Yannik AU - Biehler, Rolf AU - Frischemeier, Daniel AU - Malatyali, Hülya ID - 29712 JF - INFOS 2021–19. GI-Fachtagung Informatik und Schule TI - Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz ER - TY - JOUR AU - Hüsing, Sven AU - Weiser, Niklas AU - Biehler, Rolf ID - 40512 IS - 228 JF - mathematik lehren TI - Faszination 3D-Film: Entwicklung einer 3D-Konstruktion VL - 2021 ER - TY - JOUR AB - 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. AU - Rohlfing, Katharina J. AU - Cimiano, Philipp AU - Scharlau, Ingrid AU - Matzner, Tobias AU - Buhl, Heike M. AU - Buschmeier, Hendrik AU - Esposito, Elena AU - Grimminger, Angela AU - Hammer, Barbara AU - Haeb-Umbach, Reinhold AU - Horwath, Ilona AU - Hüllermeier, Eyke AU - Kern, Friederike AU - Kopp, Stefan AU - Thommes, Kirsten AU - Ngonga Ngomo, Axel-Cyrille AU - Schulte, Carsten AU - Wachsmuth, Henning AU - Wagner, Petra AU - Wrede, Britta ID - 24456 IS - 3 JF - IEEE Transactions on Cognitive and Developmental Systems KW - Explainability KW - process ofexplaining andunderstanding KW - explainable artificial systems SN - 2379-8920 TI - Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems VL - 13 ER - TY - CHAP AU - Huhmann, Tobias AU - Eilterts, Katja AU - Schulte, Carsten AU - Winkelnkemper, Felix ID - 21268 T2 - Digitales Lernen in der Grundschule II: Aktuelle Trends in Forschung und Praxis TI - Der Darstellungsflüchtigkeit im Geometrieunterricht durch digitale Unterstützung entgegenwirken ER - TY - CONF AU - Winkelnkemper, Felix AU - Schulte, Carsten AU - Eilerts, Katja AU - Bechinie, Dominik AU - Huhmann, Tobias ID - 20335 T2 - EdMedia+ Innovate Learning TI - The Interdisciplinary Development of an Educational Game for Primary School Children--Lessons Learned ER - TY - CONF AB - 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? AU - Terfloth, Lutz AU - Budde, Lea AU - Schulte, Carsten ID - 20452 SN - 9781450389211 TI - Combining Ideas and Artifacts: An Interaction-Focused View on Computing Education Using a Cybersecurity Example ER - TY - JOUR AU - Webb, Mary E AU - Fluck, Andrew AU - Magenheim, Johannes AU - Malyn-Smith, Joyce AU - Waters, Juliet AU - Deschênes , Michelle AU - Zagami, Jason ID - 20834 JF - Educational Technology Research and Development TI - Machine learning for human learners: opportunities, issues, tensions and threats ER - TY - JOUR AU - Magenheim, Johannes ID - 20835 JF - MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung TI - < Big Data> aus der Perspektive von Informatischer Bildung und Medienpädagogik VL - 37 ER - TY - JOUR AU - Magenheim, Johannes AU - Schulte, Carsten ID - 20836 JF - Encyclopedia of Education and Information Technologies. Cham: Springer TI - Data science education ER - TY - CHAP AU - Schulte, Carsten AU - Budde, Lea AU - Winkelnkemper, Felix ID - 20840 T2 - Mobile Medien im Schulkontext TI - Programmieren - Lehren und Lernen mit und über Medien ER - TY - CONF AB - 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. AU - Opel, Simone Anna AU - Schlichtig, Michael ED - Vollmer, Thomas ED - Karges, Torben ED - Richter, Tim ED - Schlömer, Britta ED - Schütt-Sayed, Sören ID - 29298 KW - Berufsbildung KW - vocational education KW - Ausbildung KW - training KW - berufliche Weiterbildung KW - advanced vocational education KW - Digitalisierung KW - digitalization KW - Unterricht KW - teaching KW - Lehrmethode KW - teaching method KW - Interdisziplinarität KW - interdisciplinarity KW - Fachdidaktik KW - subject didactics KW - Curriculum KW - curriculum KW - gewerblich-technischer Beruf KW - vocational/technical occupation KW - Fachkraft KW - specialist KW - Qualifikationsanforderungen KW - qualification requirements KW - Kompetenz KW - competence KW - Lehrerbildung KW - teacher training KW - Bundesrepublik Deutschland KW - Federal Republic of Germany T2 - Sammelband der 27. Fachtagung der BAG Berufliche Bildung TI - Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II VL - 55 ER - TY - JOUR AU - Budde, Lea AU - Schulte, Carsten AU - Buhl, Heike M. AU - Muehling, Andreas ID - 21267 JF - Seventh International Conference on Learning and Teaching in Computing and Engineeringe KW - ⛔ No DOI found TI - Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows) ER - TY - CONF AU - Biehler, Rolf AU - Fleischer, Yannik AU - Budde, Lea AU - Frischemeier, Daniel AU - Gerstenberger, Dietrich AU - Podworny, Susanne AU - Schulte, Carsten ED - Arnold, P. ID - 35814 T2 - New Skills in the Changing World of Statistics Education Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE) TI - Data science education in secondary schools: Teaching and learning decision trees with CODAP and Jupyter Notebooks as an example of integrating machine learning into statistics education ER - TY - CHAP AU - Budde, Lea AU - Frischemeier, Daniel AU - Biehler, Rolf AU - Fleischer, Yannik AU - Gerstenberger, Dietrich AU - Podworny, Susanne AU - Schulte, Carsten ED - Arnold, P. ID - 35821 T2 - New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020 TI - Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP ER -