[{"author":[{"last_name":"Opel","full_name":"Opel, Simone Anna","id":"72932","first_name":"Simone Anna"},{"id":"32312","full_name":"Schlichtig, Michael","last_name":"Schlichtig","first_name":"Michael"}],"volume":55,"oa":"1","date_updated":"2022-01-12T17:04:10Z","main_file_link":[{"url":"https://library.oapen.org/handle/20.500.12657/43933","open_access":"1"}],"doi":"https://doi.org/10.3278/6004722w","conference":{"location":"Siegen","end_date":"2019-03-13","start_date":"2019-03-11","name":"20. Hochschultage Berufliche Bildung (HTBB) \"Digitale Welt - Bildung und Arbeit in Transformationsgesellschaften\"."},"publication_status":"published","citation":{"ama":"Opel SA, Schlichtig M. Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II. In: Vollmer T, Karges T, Richter T, Schlömer B, Schütt-Sayed S, eds. <i>Sammelband der 27. Fachtagung der BAG Berufliche Bildung</i>. Vol 55. Berufsbildung, Arbeit und Innovation. wbv Media GmbH &#38; Co. KG; 2020:176-194. doi:<a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>","ieee":"S. A. Opel and M. Schlichtig, “Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II,” in <i>Sammelband der 27. Fachtagung der BAG Berufliche Bildung</i>, Siegen, 2020, vol. 55, pp. 176–194, doi: <a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>.","chicago":"Opel, Simone Anna, and Michael Schlichtig. “Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II.” In <i>Sammelband der 27. Fachtagung der BAG Berufliche Bildung</i>, edited by Thomas Vollmer, Torben Karges, Tim Richter, Britta Schlömer, and Sören Schütt-Sayed, 55:176–94. Berufsbildung, Arbeit und Innovation. Bielefeld: wbv Media GmbH &#38; Co. KG, 2020. <a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>.","apa":"Opel, S. A., &#38; Schlichtig, M. (2020). Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II. In T. Vollmer, T. Karges, T. Richter, B. Schlömer, &#38; S. Schütt-Sayed (Eds.), <i>Sammelband der 27. Fachtagung der BAG Berufliche Bildung</i> (Vol. 55, pp. 176–194). wbv Media GmbH &#38; Co. KG. <a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>","mla":"Opel, Simone Anna, and Michael Schlichtig. “Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II.” <i>Sammelband der 27. Fachtagung der BAG Berufliche Bildung</i>, edited by Thomas Vollmer et al., vol. 55, wbv Media GmbH &#38; Co. KG, 2020, pp. 176–94, doi:<a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>.","bibtex":"@inproceedings{Opel_Schlichtig_2020, place={Bielefeld}, series={Berufsbildung, Arbeit und Innovation}, title={Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II}, volume={55}, DOI={<a href=\"https://doi.org/10.3278/6004722w\">https://doi.org/10.3278/6004722w</a>}, booktitle={Sammelband der 27. Fachtagung der BAG Berufliche Bildung}, publisher={wbv Media GmbH &#38; Co. KG}, author={Opel, Simone Anna and Schlichtig, Michael}, editor={Vollmer, Thomas and Karges, Torben and Richter, Tim and Schlömer, Britta and Schütt-Sayed, Sören}, year={2020}, pages={176–194}, collection={Berufsbildung, Arbeit und Innovation} }","short":"S.A. Opel, M. Schlichtig, in: T. Vollmer, T. Karges, T. Richter, B. Schlömer, S. Schütt-Sayed (Eds.), Sammelband der 27. Fachtagung der BAG Berufliche Bildung, wbv Media GmbH &#38; Co. KG, Bielefeld, 2020, pp. 176–194."},"intvolume":"        55","page":"176-194","place":"Bielefeld","series_title":"Berufsbildung, Arbeit und Innovation","user_id":"32312","department":[{"_id":"67"}],"_id":"29298","type":"conference","status":"public","editor":[{"full_name":"Vollmer, Thomas","last_name":"Vollmer","first_name":"Thomas"},{"first_name":"Torben","full_name":"Karges, Torben","last_name":"Karges"},{"first_name":"Tim","full_name":"Richter, Tim","last_name":"Richter"},{"last_name":"Schlömer","full_name":"Schlömer, Britta","first_name":"Britta"},{"last_name":"Schütt-Sayed","full_name":"Schütt-Sayed, Sören","first_name":"Sören"}],"date_created":"2022-01-12T16:43:38Z","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","year":"2020","language":[{"iso":"ger"}],"keyword":["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"],"publication":"Sammelband der 27. Fachtagung der BAG Berufliche Bildung","abstract":[{"text":"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.\r\nAn 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.\r\nHierfür 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\r\nermöglicht, 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.","lang":"ger"},{"lang":"eng","text":"The topics ”Big Data”, “Artificial Intelligence” and “Data Science” are controversially discussed among the general public, but they present new challenges for training in IT and IT-related professions. These challenges will become more important in the future as a result of further social and technological development towards a data society.\r\nAt this point, the question arises as to which aspects of this large complex of topics are important for school and education, and how these topics can be integrated in a meaningful and profitable way into informatics education in vocational education. In 2017, we organized a symposium towards the topic “Data Science” and discussed relevant aspects for general and vocational education. Algorithms of artificial intelligence and their application in industry and society, explorations of Big Data as well as the handling of one's own data in social networks were worked out as core elements for teaching. For this reason, our aim is to develop a comprehensive curriculum on this topic from these subject areas and to develop and test modules for various teaching scenarios in order to enable teachers from computer science, mathematics or technology to teach these topics themselves.\r\nFor this purpose, an experimental project course was developed within the framework of the ProDaBi project (Project Data Science and Big Data at School, https://www.prodabi.de), which we conducted with students from upper secondary classes at the University of Paderborn in the school year 2018/19. In this course we try to address all these aspects. This course consists of several modules: One module has been designed to teach the exploration of Big Data. Another module encompasses aspects of machine learning as part of artificial intelligence. The course concludes in a project phase which, in cooperation with local companies, will enable the students to apply what they have learned into a real Data Science project. Based on the experiences of this project course and the parallel testing of individual modules with vocational schools, we will further develop the material and make it available to other cooperation partners for testing, so that not only complete teaching materials but also a comprehensive curriculum will have been developed until the end of the project."}]},{"year":"2020","place":"Voorborg, The Netherlands","citation":{"ieee":"R. Biehler <i>et al.</i>, “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,” in <i>New Skills in the Changing World of Statistics Education Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE)</i>, 2020.","chicago":"Biehler, Rolf, Franz Yannik Fleischer, Lea Budde, Daniel Frischemeier, Dietrich Gerstenberger, Susanne Podworny, and Carsten Schulte. “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.” In <i>New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE)</i>, edited by P. Arnold. Voorborg, The Netherlands: ISI/IASE, 2020.","ama":"Biehler R, Fleischer FY, Budde L, et al. 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. In: Arnold P, ed. <i>New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE)</i>. ISI/IASE; 2020.","apa":"Biehler, R., Fleischer, F. Y., Budde, L., Frischemeier, D., Gerstenberger, D., Podworny, S., &#38; Schulte, C. (2020). 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. In P. Arnold (Ed.), <i>New Skills in the Changing World of Statistics Education Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE)</i>. ISI/IASE.","mla":"Biehler, Rolf, et al. “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.” <i>New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE)</i>, edited by P. Arnold, ISI/IASE, 2020.","bibtex":"@inproceedings{Biehler_Fleischer_Budde_Frischemeier_Gerstenberger_Podworny_Schulte_2020, place={Voorborg, The Netherlands}, title={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}, booktitle={New Skills in the Changing World of Statistics Education Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE)}, publisher={ISI/IASE}, author={Biehler, Rolf and Fleischer, Franz Yannik and Budde, Lea and Frischemeier, Daniel and Gerstenberger, Dietrich and Podworny, Susanne and Schulte, Carsten}, editor={Arnold, P.}, year={2020} }","short":"R. Biehler, F.Y. Fleischer, L. Budde, D. Frischemeier, D. Gerstenberger, S. Podworny, C. Schulte, in: P. Arnold (Ed.), New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE), ISI/IASE, Voorborg, The Netherlands, 2020."},"date_updated":"2024-08-21T10:03:31Z","publisher":"ISI/IASE","date_created":"2023-01-10T11:19:32Z","author":[{"first_name":"Rolf","full_name":"Biehler, Rolf","id":"16274","last_name":"Biehler"},{"id":"42660","full_name":"Fleischer, Franz Yannik","last_name":"Fleischer","orcid":"https://orcid.org/0000-0003-0318-0329","first_name":"Franz Yannik"},{"first_name":"Lea","full_name":"Budde, Lea","last_name":"Budde"},{"last_name":"Frischemeier","full_name":"Frischemeier, Daniel","first_name":"Daniel"},{"first_name":"Dietrich","last_name":"Gerstenberger","full_name":"Gerstenberger, Dietrich"},{"first_name":"Susanne","full_name":"Podworny, Susanne","id":"30619","last_name":"Podworny","orcid":"0000-0002-6313-5987"},{"first_name":"Carsten","full_name":"Schulte, Carsten","id":"60311","last_name":"Schulte"}],"title":"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","publication":"New Skills in the Changing World of Statistics Education Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE)","type":"conference","editor":[{"first_name":"P.","full_name":"Arnold, P.","last_name":"Arnold"}],"status":"public","_id":"35814","department":[{"_id":"363"},{"_id":"67"}],"user_id":"37888","language":[{"iso":"eng"}]},{"user_id":"37888","department":[{"_id":"363"},{"_id":"67"}],"_id":"35821","file_date_updated":"2024-11-12T11:03:44Z","language":[{"iso":"eng"}],"ddc":["510"],"type":"book_chapter","publication":"New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020","file":[{"date_updated":"2024-11-12T11:03:44Z","date_created":"2024-11-12T11:03:44Z","creator":"krueter","file_size":340591,"file_id":"56999","file_name":"IASE2020_Roundtable_24_Frischem.pdf","access_level":"closed","content_type":"application/pdf","success":1,"relation":"main_file"}],"status":"public","editor":[{"first_name":"P.","full_name":"Arnold, P.","last_name":"Arnold"}],"author":[{"first_name":"Lea","last_name":"Budde","full_name":"Budde, Lea"},{"first_name":"Daniel","last_name":"Frischemeier","full_name":"Frischemeier, Daniel"},{"last_name":"Biehler","id":"16274","full_name":"Biehler, Rolf","first_name":"Rolf"},{"last_name":"Fleischer","orcid":"https://orcid.org/0000-0003-0318-0329","id":"42660","full_name":"Fleischer, Franz Yannik","first_name":"Franz Yannik"},{"first_name":"Dietrich","last_name":"Gerstenberger","full_name":"Gerstenberger, Dietrich"},{"full_name":"Podworny, Susanne","id":"30619","orcid":"0000-0002-6313-5987","last_name":"Podworny","first_name":"Susanne"},{"first_name":"Carsten","id":"60311","full_name":"Schulte, Carsten","last_name":"Schulte"}],"date_created":"2023-01-10T11:41:21Z","date_updated":"2024-11-12T11:03:59Z","publisher":"ISI/IASE","main_file_link":[{"url":"https://fddm.uni-paderborn.de/fileadmin/mathematik/Didaktik_der_Mathematik/BiehlerRolf/Publikationen/IASE2020_Roundtable_24_Frischem.pdf"}],"title":"Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP","has_accepted_license":"1","citation":{"ieee":"L. Budde <i>et al.</i>, “Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP,” in <i>New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020</i>, P. Arnold, Ed. Voorborg, The Netherlands: ISI/IASE, 2020.","chicago":"Budde, Lea, Daniel Frischemeier, Rolf Biehler, Franz Yannik Fleischer, Dietrich Gerstenberger, Susanne Podworny, and Carsten Schulte. “Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP.” In <i>New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE), July 2020</i>, edited by P. Arnold. Voorborg, The Netherlands: ISI/IASE, 2020.","ama":"Budde L, Frischemeier D, Biehler R, et al. Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP. In: Arnold P, ed. <i>New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE), July 2020</i>. ISI/IASE; 2020.","apa":"Budde, L., Frischemeier, D., Biehler, R., Fleischer, F. Y., Gerstenberger, D., Podworny, S., &#38; Schulte, C. (2020). Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP. In P. Arnold (Ed.), <i>New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020</i>. ISI/IASE.","bibtex":"@inbook{Budde_Frischemeier_Biehler_Fleischer_Gerstenberger_Podworny_Schulte_2020, place={Voorborg, The Netherlands}, title={Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP}, booktitle={New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable conference of the International Association for Statistical Education (IASE), July 2020}, publisher={ISI/IASE}, author={Budde, Lea and Frischemeier, Daniel and Biehler, Rolf and Fleischer, Franz Yannik and Gerstenberger, Dietrich and Podworny, Susanne and Schulte, Carsten}, editor={Arnold, P.}, year={2020} }","short":"L. Budde, D. Frischemeier, R. Biehler, F.Y. Fleischer, D. Gerstenberger, S. Podworny, C. Schulte, in: P. Arnold (Ed.), New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE), July 2020, ISI/IASE, Voorborg, The Netherlands, 2020.","mla":"Budde, Lea, et al. “Data Science Education in Secondary School: How to Develop Statistical Reasoning When Exploring Data Using CODAP.” <i>New Skills in the Changing World of Statistics Education: Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE), July 2020</i>, edited by P. Arnold, ISI/IASE, 2020."},"year":"2020","place":"Voorborg, The Netherlands"},{"_id":"21267","project":[{"_id":"114","name":"TRR 318 - A04: TRR 318 - Integration des technischen Modells in das Partnermodell bei der Erklärung von digitalen Artefakten (Teilprojekt A04)","grant_number":"438445824"}],"department":[{"_id":"67"},{"_id":"427"}],"user_id":"90826","keyword":["⛔ No DOI found"],"language":[{"iso":"eng"}],"publication":"Seventh International Conference on Learning and Teaching in Computing and Engineeringe","type":"journal_article","status":"public","publisher":"(IEEE)","date_updated":"2025-08-12T07:15:23Z","date_created":"2021-02-24T09:18:36Z","author":[{"last_name":"Budde","id":"32443","full_name":"Budde, Lea","first_name":"Lea"},{"first_name":"Carsten","id":"60311","full_name":"Schulte, Carsten","last_name":"Schulte"},{"first_name":"Heike M.","id":"27152","full_name":"Buhl, Heike M.","last_name":"Buhl"},{"last_name":"Muehling","full_name":"Muehling, Andreas","first_name":"Andreas"}],"title":"Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows)","year":"2020","citation":{"ama":"Budde L, Schulte C, Buhl HM, Muehling A. Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows). <i>Seventh International Conference on Learning and Teaching in Computing and Engineeringe</i>. Published online 2020.","chicago":"Budde, Lea, Carsten Schulte, Heike M. Buhl, and Andreas Muehling. “Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows).” <i>Seventh International Conference on Learning and Teaching in Computing and Engineeringe</i>, 2020.","ieee":"L. Budde, C. Schulte, H. M. Buhl, and A. Muehling, “Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows),” <i>Seventh International Conference on Learning and Teaching in Computing and Engineeringe</i>, 2020.","short":"L. Budde, C. Schulte, H.M. Buhl, A. Muehling, Seventh International Conference on Learning and Teaching in Computing and Engineeringe (2020).","bibtex":"@article{Budde_Schulte_Buhl_Muehling_2020, title={Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows)}, journal={Seventh International Conference on Learning and Teaching in Computing and Engineeringe}, publisher={(IEEE)}, author={Budde, Lea and Schulte, Carsten and Buhl, Heike M. and Muehling, Andreas}, year={2020} }","mla":"Budde, Lea, et al. “Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows).” <i>Seventh International Conference on Learning and Teaching in Computing and Engineeringe</i>, (IEEE), 2020.","apa":"Budde, L., Schulte, C., Buhl, H. M., &#38; Muehling, A. (2020). Understanding and Explaining Digital Artefacts - the Role of a Duality (Accepted Paper - Digital Publication Follows). <i>Seventh International Conference on Learning and Teaching in Computing and Engineeringe</i>."}},{"page":"261-262","citation":{"short":"C. Izu, C. Schulte, A. Aggarwal, Q. I. Cutts, R. Duran, M. Gutica, B. Heinemann, E. Kraemer, V. Lonati, C. Mirolo, R. Weeda, in: Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019, 2019, pp. 261–262.","bibtex":"@inproceedings{Izu_Schulte_Aggarwal_I. Cutts_Duran_Gutica_Heinemann_Kraemer_Lonati_Mirolo_et al._2019, title={Program Comprehension: Identifying Learning Trajectories for Novice Programmers}, DOI={<a href=\"https://doi.org/10.1145/3304221.3325531\">10.1145/3304221.3325531</a>}, booktitle={Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019}, 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 et al.}, year={2019}, pages={261–262} }","mla":"Izu, Cruz, et al. “Program Comprehension: Identifying Learning Trajectories for Novice Programmers.” <i>Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019</i>, 2019, pp. 261–62, doi:<a href=\"https://doi.org/10.1145/3304221.3325531\">10.1145/3304221.3325531</a>.","apa":"Izu, C., Schulte, C., Aggarwal, A., I. Cutts, Q., Duran, R., Gutica, M., … Weeda, R. (2019). Program Comprehension: Identifying Learning Trajectories for Novice Programmers. In <i>Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019</i> (pp. 261–262). <a href=\"https://doi.org/10.1145/3304221.3325531\">https://doi.org/10.1145/3304221.3325531</a>","ama":"Izu C, Schulte C, Aggarwal A, et al. Program Comprehension: Identifying Learning Trajectories for Novice Programmers. In: <i>Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019</i>. ; 2019:261-262. doi:<a href=\"https://doi.org/10.1145/3304221.3325531\">10.1145/3304221.3325531</a>","ieee":"C. Izu <i>et al.</i>, “Program Comprehension: Identifying Learning Trajectories for Novice Programmers,” in <i>Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019</i>, 2019, pp. 261–262.","chicago":"Izu, Cruz, Carsten Schulte, Ashish Aggarwal, Quintin I. Cutts, Rodrigo Duran, Mirela Gutica, Birte Heinemann, et al. “Program Comprehension: Identifying Learning Trajectories for Novice Programmers.” In <i>Proceedings of the 2019 (ACM) Conference on Innovation and Technology in Computer Science Education, Aberdeen, Scotland, UK, July 15-17, 2019</i>, 261–62, 2019. <a href=\"https://doi.org/10.1145/3304221.3325531\">https://doi.org/10.1145/3304221.3325531</a>."},"year":"2019","date_created":"2020-01-15T07:55:25Z","author":[{"first_name":"Cruz","full_name":"Izu, Cruz","last_name":"Izu"},{"last_name":"Schulte","full_name":"Schulte, Carsten","id":"60311","first_name":"Carsten"},{"first_name":"Ashish","last_name":"Aggarwal","full_name":"Aggarwal, Ashish"},{"full_name":"I. Cutts, Quintin","last_name":"I. 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Pozdniakov (Eds.), ISSEP 2019 - 12th International Conference on Informatics in Schools: Situation, Evaluation and Perspectives, Local Proceedings, 2019, pp. 65–73.","bibtex":"@inproceedings{Schlichtig_Opel_Budde_Schulte_2019, title={Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material}, volume={12}, booktitle={ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives, Local Proceedings}, author={Schlichtig, Michael and Opel, Simone Anna and Budde, Lea and Schulte, Carsten}, editor={Jasutė, Eglė and Pozdniakov, Sergei}, year={2019}, pages={65–73} }","ama":"Schlichtig M, Opel SA, Budde L, Schulte C. Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material. In: Jasutė E, Pozdniakov S, eds. <i>ISSEP 2019 - 12th International Conference on Informatics in Schools: Situation, Evaluation and Perspectives, Local Proceedings</i>. Vol 12. ; 2019:65-73.","chicago":"Schlichtig, Michael, Simone Anna Opel, Lea Budde, and Carsten Schulte. “Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material.” In <i>ISSEP 2019 - 12th International Conference on Informatics in Schools: Situation, Evaluation and Perspectives, Local Proceedings</i>, edited by Eglė Jasutė and Sergei Pozdniakov, 12:65–73, 2019.","ieee":"M. Schlichtig, S. A. Opel, L. Budde, and C. Schulte, “Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material,” in <i>ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives, Local Proceedings</i>, Lanarca, 2019, vol. 12, pp. 65–73."},"page":"65 - 73","intvolume":"        12","publication_status":"published","publication_identifier":{"isbn":["978-9925-553-27-3"]},"main_file_link":[{"url":"http://cyprusconferences.org/issep2019/wp-content/uploads/2019/10/LocalISSEP-v5.pdf"}],"conference":{"location":"Lanarca","end_date":"2019-11-20","start_date":"2019-11-18","name":"ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives"},"date_updated":"2022-07-26T11:41:41Z","author":[{"last_name":"Schlichtig","orcid":"0000-0001-6600-6171","id":"32312","full_name":"Schlichtig, Michael","first_name":"Michael"},{"last_name":"Opel","id":"72932","full_name":"Opel, Simone Anna","first_name":"Simone Anna"},{"last_name":"Budde","full_name":"Budde, Lea","id":"32443","first_name":"Lea"},{"last_name":"Schulte","full_name":"Schulte, Carsten","id":"60311","first_name":"Carsten"}],"volume":12,"abstract":[{"text":"Artificial intelligence (AI) has the potential for far-reaching – in our opinion – irreversible changes.\r\nThey range from effects on the individual and society to new societal and social issues. The question arises\r\nas to how students can learn the basic functioning of AI systems, what areas of life and society are affected\r\nby these and – most important – how their own lives are affected by these changes. Therefore, we are developing and evaluating school materials for the German ”Science Year AI”. It can be used for students of all\r\nschool types from the seventh grade upwards and will be distributed to about 2000 schools in autumn with\r\nthe support of the Federal Ministry of Education and Research. The material deals with the following aspects\r\nof AI: Discussing everyday experiences with AI, how does machine learning work, historical development\r\nof AI concepts, difference between man and machine, future distribution of roles between man and machine,\r\nin which AI world do we want to live and how much AI would we like to have in our lives. Through an\r\naccompanying evaluation, high quality of the technical content and didactic preparation is achieved in order\r\nto guarantee the long-term applicability in the teaching context in the different age groups and school types.\r\nIn this paper, we describe the current state of the material development, the challenges arising, and the results\r\nof tests with different classes to date. We also present first ideas for evaluating the results.","lang":"eng"}],"publication":"ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives, Local Proceedings","keyword":["Artificial Intelligence","Machine Learning","Teaching Material","Societal Aspects","Ethics. Social Aspects","Science Year","Simulation Game"],"language":[{"iso":"eng"}],"year":"2019","quality_controlled":"1","title":"Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material","date_created":"2019-12-16T17:50:08Z"},{"author":[{"first_name":"Simone Anna","full_name":"Opel, Simone Anna","id":"72932","last_name":"Opel"},{"id":"32312","full_name":"Schlichtig, Michael","orcid":"0000-0001-6600-6171","last_name":"Schlichtig","first_name":"Michael"},{"last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten","first_name":"Carsten"},{"first_name":"Rolf","full_name":"Biehler, Rolf","last_name":"Biehler"},{"first_name":"Daniel","last_name":"Frischemeier","full_name":"Frischemeier, Daniel"},{"first_name":"Susanne","full_name":"Podworny, Susanne","last_name":"Podworny"},{"first_name":"Thomas","full_name":"Wassong, Thomas","id":"21241","last_name":"Wassong"}],"date_created":"2020-01-28T10:28:34Z","volume":"P-288","publisher":"Gesellschaft für Informatik","date_updated":"2022-07-26T11:42:05Z","title":"Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II","quality_controlled":"1","citation":{"apa":"Opel, S. A., Schlichtig, M., Schulte, C., Biehler, R., Frischemeier, D., Podworny, S., &#38; Wassong, T. (2019). Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II. <i>INFOS</i>, <i>P-288</i>, 285–294.","short":"S.A. Opel, M. Schlichtig, C. Schulte, R. Biehler, D. Frischemeier, S. Podworny, T. Wassong, in: INFOS, Gesellschaft für Informatik, 2019, pp. 285–294.","bibtex":"@inproceedings{Opel_Schlichtig_Schulte_Biehler_Frischemeier_Podworny_Wassong_2019, series={LNI}, title={Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II}, volume={P-288}, booktitle={INFOS}, publisher={Gesellschaft für Informatik}, author={Opel, Simone Anna and Schlichtig, Michael and Schulte, Carsten and Biehler, Rolf and Frischemeier, Daniel and Podworny, Susanne and Wassong, Thomas}, year={2019}, pages={285–294}, collection={LNI} }","mla":"Opel, Simone Anna, et al. “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II.” <i>INFOS</i>, vol. P-288, Gesellschaft für Informatik, 2019, pp. 285–94.","chicago":"Opel, Simone Anna, Michael Schlichtig, Carsten Schulte, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, and Thomas Wassong. “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II.” In <i>INFOS</i>, P-288:285–94. LNI. Gesellschaft für Informatik, 2019.","ieee":"S. A. Opel <i>et al.</i>, “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II,” in <i>INFOS</i>, 2019, vol. P-288, pp. 285–294.","ama":"Opel SA, Schlichtig M, Schulte C, et al. Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II. In: <i>INFOS</i>. Vol P-288. LNI. Gesellschaft für Informatik; 2019:285-294."},"page":"285-294","year":"2019","series_title":"LNI","user_id":"32312","department":[{"_id":"67"}],"_id":"15640","language":[{"iso":"ger"}],"type":"conference","publication":"INFOS","status":"public"},{"type":"conference","publication":"INFOS","status":"public","_id":"15641","user_id":"32312","series_title":"LNI","department":[{"_id":"67"}],"language":[{"iso":"ger"}],"quality_controlled":"1","year":"2019","citation":{"chicago":"Schlichtig, Michael, Simone Anna Opel, Carsten Schulte, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, and Thomas Wassong. “Maschinelles Lernen im Unterricht mit Jupyter Notebook.” In <i>INFOS</i>, P-288:385. LNI. Gesellschaft für Informatik, 2019.","ieee":"M. Schlichtig <i>et al.</i>, “Maschinelles Lernen im Unterricht mit Jupyter Notebook,” in <i>INFOS</i>, 2019, vol. P-288, p. 385.","ama":"Schlichtig M, Opel SA, Schulte C, et al. Maschinelles Lernen im Unterricht mit Jupyter Notebook. In: <i>INFOS</i>. Vol P-288. LNI. Gesellschaft für Informatik; 2019:385.","short":"M. Schlichtig, S.A. Opel, C. Schulte, R. Biehler, D. Frischemeier, S. Podworny, T. Wassong, in: INFOS, Gesellschaft für Informatik, 2019, p. 385.","mla":"Schlichtig, Michael, et al. “Maschinelles Lernen im Unterricht mit Jupyter Notebook.” <i>INFOS</i>, vol. P-288, Gesellschaft für Informatik, 2019, p. 385.","bibtex":"@inproceedings{Schlichtig_Opel_Schulte_Biehler_Frischemeier_Podworny_Wassong_2019, series={LNI}, title={Maschinelles Lernen im Unterricht mit Jupyter Notebook}, volume={P-288}, booktitle={INFOS}, publisher={Gesellschaft für Informatik}, author={Schlichtig, Michael and Opel, Simone Anna and Schulte, Carsten and Biehler, Rolf and Frischemeier, Daniel and Podworny, Susanne and Wassong, Thomas}, year={2019}, pages={385}, collection={LNI} }","apa":"Schlichtig, M., Opel, S. A., Schulte, C., Biehler, R., Frischemeier, D., Podworny, S., &#38; Wassong, T. (2019). Maschinelles Lernen im Unterricht mit Jupyter Notebook. <i>INFOS</i>, <i>P-288</i>, 385."},"page":"385","publisher":"Gesellschaft für Informatik","date_updated":"2022-07-26T11:41:58Z","author":[{"first_name":"Michael","full_name":"Schlichtig, Michael","id":"32312","orcid":"0000-0001-6600-6171","last_name":"Schlichtig"},{"id":"72932","full_name":"Opel, Simone Anna","last_name":"Opel","first_name":"Simone Anna"},{"full_name":"Schulte, Carsten","id":"60311","last_name":"Schulte","first_name":"Carsten"},{"first_name":"Rolf","last_name":"Biehler","full_name":"Biehler, Rolf"},{"first_name":"Daniel","full_name":"Frischemeier, Daniel","last_name":"Frischemeier"},{"first_name":"Susanne","full_name":"Podworny, Susanne","last_name":"Podworny"},{"first_name":"Thomas","full_name":"Wassong, Thomas","id":"21241","last_name":"Wassong"}],"date_created":"2020-01-28T10:28:35Z","volume":"P-288","title":"Maschinelles Lernen im Unterricht mit Jupyter Notebook"},{"publisher":"ACM","date_updated":"2022-07-26T11:41:51Z","author":[{"last_name":"Opel","id":"72932","full_name":"Opel, Simone Anna","first_name":"Simone Anna"},{"last_name":"Schlichtig","orcid":"0000-0001-6600-6171","id":"32312","full_name":"Schlichtig, Michael","first_name":"Michael"},{"id":"60311","full_name":"Schulte, Carsten","last_name":"Schulte","first_name":"Carsten"}],"date_created":"2020-01-28T10:28:37Z","title":"Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress)","quality_controlled":"1","year":"2019","page":"11:1-11:2","citation":{"apa":"Opel, S. A., Schlichtig, M., &#38; Schulte, C. (2019). Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress). <i>WiPSCE</i>, 11:1-11:2.","bibtex":"@inproceedings{Opel_Schlichtig_Schulte_2019, title={Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress)}, booktitle={WiPSCE}, publisher={ACM}, author={Opel, Simone Anna and Schlichtig, Michael and Schulte, Carsten}, year={2019}, pages={11:1-11:2} }","short":"S.A. Opel, M. Schlichtig, C. Schulte, in: WiPSCE, ACM, 2019, p. 11:1-11:2.","mla":"Opel, Simone Anna, et al. “Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress).” <i>WiPSCE</i>, ACM, 2019, p. 11:1-11:2.","chicago":"Opel, Simone Anna, Michael Schlichtig, and Carsten Schulte. “Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress).” In <i>WiPSCE</i>, 11:1-11:2. ACM, 2019.","ieee":"S. A. Opel, M. Schlichtig, and C. Schulte, “Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress),” in <i>WiPSCE</i>, 2019, p. 11:1-11:2.","ama":"Opel SA, Schlichtig M, Schulte C. Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress). In: <i>WiPSCE</i>. ACM; 2019:11:1-11:2."},"_id":"15643","department":[{"_id":"67"}],"user_id":"32312","language":[{"iso":"eng"}],"publication":"WiPSCE","type":"conference","status":"public"},{"language":[{"iso":"ger"}],"_id":"14848","department":[{"_id":"67"},{"_id":"97"}],"user_id":"21241","abstract":[{"lang":"ger","text":"Data Science und Big Data durchdringt in ihren diversen Facetten unser tägliches Leben– kaum ein Tag, an dem nicht verschiedene Meldungen über technische Innovationen, Einsatzmöglichkeiten von Künstlicher Intelligenz (KI) und Maschinelles Lernen (ML) und ihre ethischen sowie gesellschaftlichen Implikationen in den unterschiedlichen Medien diskutiert werden. Aus diesem Grund erscheint es uns immens wichtig, diese Fragestellungen und Technologien auch in den Unterricht der Sekundarstufe II zu integrieren. Um diesem Anspruch gerecht zu werden, entwickelten wir im Rahmen eines Forschungsprojekts ein Curriculum, welches wir als konkretes Unterrichtskonzept innerhalb eines Projektkurses erprobt, evaluiert weiterentwickelt wird. Bei der Implementierung entschieden wir uns, zur aktiven Umsetzung von Konzepten von ML als Plattform Jupyter Notebook mit Python zu verwenden, da diese Umgebung durch die Verbindung von Code und Hypertext zur Dokumentation und Erklärung Medienbrüche im Lernprozess verringern kann. Zudem ist Python zur Implementierung der Methoden von ML sehr gut geeignet. Im Themenfeld des ML als Teilgebiet der KI legen wir den Fokus auf zwei unterschiedliche Lernverfahren um verschieden Aspekte von ML, u.A. wie Nachvollziehbarkeit unter gesellschaftlichen Gesichtspunkten zu vermitteln. Diese sind Künstliche Neuronale Netze (bei denen die Berechnung und Bedeutung der Kantengewichte zwischen den Neuronen für den Menschen insbesondere bei komplexeren Netzen kaum nachvollziehbar erschienen) und Entscheidungsbäume (strukturierte und gerichtete Bäume zur Darstellung von Entscheidungsregeln, welche auch für Schülerinnen und Schüler meist gut nachvollziehbares und verständliches KI-Modell darstellen). In diesem Workshop stellen wir konkrete Umsetzungsbeispiele inklusive der Programmierung für beide Verfahren mit Jupyter Notebook und Python als Teil einer Unterrichtssequenz vor und diskutieren diese."}],"editor":[{"first_name":"Arno","last_name":"Pasternak","full_name":"Pasternak, Arno"}],"status":"public","publication":"Informatik für alle","type":"conference","title":"Maschinelles Lernen im Unterricht mit Jupyter Notebook","conference":{"location":"Dortmund, Germany","end_date":"2019-09-18","start_date":"2019-09-16","name":"INFOS 2019"},"main_file_link":[{"url":"https://dl.gi.de/handle/20.500.12116/28964"}],"date_updated":"2025-05-25T20:01:30Z","publisher":"Gesellschaft für Informatik","author":[{"first_name":"Michael","full_name":"Schlichtig, Michael","id":"32312","last_name":"Schlichtig","orcid":"0000-0001-6600-6171"},{"last_name":"Opel","full_name":"Opel, Simone","first_name":"Simone"},{"full_name":"Schulte, Carsten","last_name":"Schulte","first_name":"Carsten"},{"last_name":"Biehler","full_name":"Biehler, Rolf","first_name":"Rolf"},{"first_name":"Daniel","full_name":"Frischemeier, Daniel","last_name":"Frischemeier"},{"first_name":"Susanne","full_name":"Podworny, Susanne","last_name":"Podworny"},{"id":"21241","full_name":"Wassong, Thomas","last_name":"Wassong","first_name":"Thomas"}],"date_created":"2019-11-07T14:08:13Z","year":"2019","place":"Bonn","page":" 385 ","citation":{"chicago":"Schlichtig, Michael, Simone Opel, Carsten Schulte, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, and Thomas Wassong. “Maschinelles Lernen im Unterricht mit Jupyter Notebook.” In <i>Informatik für alle</i>, edited by Arno Pasternak, 385. Bonn: Gesellschaft für Informatik, 2019.","ieee":"M. Schlichtig <i>et al.</i>, “Maschinelles Lernen im Unterricht mit Jupyter Notebook,” in <i>Informatik für alle</i>, Dortmund, Germany, 2019, p. 385.","ama":"Schlichtig M, Opel S, Schulte C, et al. Maschinelles Lernen im Unterricht mit Jupyter Notebook. In: Pasternak A, ed. <i>Informatik für alle</i>. Gesellschaft für Informatik; 2019:385.","apa":"Schlichtig, M., Opel, S., Schulte, C., Biehler, R., Frischemeier, D., Podworny, S., &#38; Wassong, T. (2019). Maschinelles Lernen im Unterricht mit Jupyter Notebook. In A. Pasternak (Ed.), <i>Informatik für alle</i> (p. 385). Gesellschaft für Informatik.","short":"M. Schlichtig, S. Opel, C. Schulte, R. Biehler, D. Frischemeier, S. Podworny, T. Wassong, in: A. Pasternak (Ed.), Informatik für alle, Gesellschaft für Informatik, Bonn, 2019, p. 385.","bibtex":"@inproceedings{Schlichtig_Opel_Schulte_Biehler_Frischemeier_Podworny_Wassong_2019, place={Bonn}, title={Maschinelles Lernen im Unterricht mit Jupyter Notebook}, booktitle={Informatik für alle}, publisher={Gesellschaft für Informatik}, author={Schlichtig, Michael and Opel, Simone and Schulte, Carsten and Biehler, Rolf and Frischemeier, Daniel and Podworny, Susanne and Wassong, Thomas}, editor={Pasternak, Arno}, year={2019}, pages={385} }","mla":"Schlichtig, Michael, et al. “Maschinelles Lernen im Unterricht mit Jupyter Notebook.” <i>Informatik für alle</i>, edited by Arno Pasternak, Gesellschaft für Informatik, 2019, p. 385."},"publication_identifier":{"isbn":["978-3-88579-682-4"]},"publication_status":"published"},{"abstract":[{"lang":"ger","text":"Die Bereiche „Data Science“ und „Big Data“ sowie ihre technischen, ethischen und gesellschaftlichen Auswirkungen werden zunehmend nicht nur in der Wissenschaft, sondern auch in diversen Medien diskutiert und somit verstärkt auch zu einem wichtigen Thema für alle. Um den Schülerinnen und Schülern der Sekundarstufe II einen theoretisch und fachwissenschaftlich fundierten Einstieg in diesen Themenbereich zu ermöglichen, wurde ein erster Entwurf eines interdisziplinären Curriculums entwickelt, das neben fachlichen Aspekten von Data Science einen Fokus auf sich hieraus ergebende gesellschaftliche Fragestellungen legt. Es werden neben der Konzeption des Kurses die bisherigen Erfahrungen aus der Durchführung – insbesondere in Hinsicht der darin enthaltenen Unterrichtseinheit zum Maschinellen Lernen - berichtet, sowie die sich hieraus ergebenden Implikationen für die Weiterentwicklung dargestellt und diskutiert."}],"publication":"Informatik für alle","language":[{"iso":"ger"}],"year":"2019","title":"Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II","publisher":"Gesellschaft für Informatik","date_created":"2019-11-07T14:07:30Z","editor":[{"last_name":"Pasternak","full_name":"Pasternak, Arno","first_name":"Arno"}],"status":"public","type":"conference","_id":"14847","user_id":"21241","department":[{"_id":"67"},{"_id":"97"}],"place":"Bonn","citation":{"ama":"Opel S, Schlichtig M, Schulte C, et al. Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II. In: Pasternak A, ed. <i>Informatik für alle</i>. Gesellschaft für Informatik; 2019:285-294.","ieee":"S. Opel <i>et al.</i>, “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II,” in <i>Informatik für alle</i>, Dortmund, Germany, 2019, pp. 285–294.","chicago":"Opel, Simone, Michael Schlichtig, Carsten Schulte, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, and Thomas Wassong. “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II.” In <i>Informatik für alle</i>, edited by Arno Pasternak, 285–94. Bonn: Gesellschaft für Informatik, 2019.","apa":"Opel, S., Schlichtig, M., Schulte, C., Biehler, R., Frischemeier, D., Podworny, S., &#38; Wassong, T. (2019). Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II. In A. Pasternak (Ed.), <i>Informatik für alle</i> (pp. 285–294). Gesellschaft für Informatik.","mla":"Opel, Simone, et al. “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II.” <i>Informatik für alle</i>, edited by Arno Pasternak, Gesellschaft für Informatik, 2019, pp. 285–94.","bibtex":"@inproceedings{Opel_Schlichtig_Schulte_Biehler_Frischemeier_Podworny_Wassong_2019, place={Bonn}, title={Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II}, booktitle={Informatik für alle}, publisher={Gesellschaft für Informatik}, author={Opel, Simone and Schlichtig, Michael and Schulte, Carsten and Biehler, Rolf and Frischemeier, Daniel and Podworny, Susanne and Wassong, Thomas}, editor={Pasternak, Arno}, year={2019}, pages={285–294} }","short":"S. Opel, M. Schlichtig, C. Schulte, R. Biehler, D. Frischemeier, S. Podworny, T. Wassong, in: A. Pasternak (Ed.), Informatik für alle, Gesellschaft für Informatik, Bonn, 2019, pp. 285–294."},"page":" 285-294 ","publication_status":"published","publication_identifier":{"isbn":["978-3-88579-682-4"]},"main_file_link":[{"url":"https://dl.gi.de/handle/20.500.12116/28935"}],"conference":{"start_date":"2019-09-16","name":"INFOS 2019","location":"Dortmund, Germany","end_date":"2019-09-18"},"date_updated":"2025-05-25T20:01:40Z","author":[{"first_name":"Simone","full_name":"Opel, Simone","last_name":"Opel"},{"last_name":"Schlichtig","orcid":"0000-0001-6600-6171","id":"32312","full_name":"Schlichtig, Michael","first_name":"Michael"},{"full_name":"Schulte, Carsten","last_name":"Schulte","first_name":"Carsten"},{"full_name":"Biehler, Rolf","last_name":"Biehler","first_name":"Rolf"},{"full_name":"Frischemeier, Daniel","last_name":"Frischemeier","first_name":"Daniel"},{"last_name":"Podworny","full_name":"Podworny, Susanne","first_name":"Susanne"},{"first_name":"Thomas","id":"21241","full_name":"Wassong, Thomas","last_name":"Wassong"}]},{"language":[{"iso":"ger"}],"_id":"20839","user_id":"21145","department":[{"_id":"67"}],"status":"public","type":"journal_article","publication":"MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung","title":"Kritische Entgegnung auf die Studie \"Zur Relevanz informatischer Bildung in der Schule für den Erwerb computer- bzw. informationsbezogener Kompetenzen\"","doi":"10.21240/mpaed/33/2018.10.29.X","date_updated":"2022-01-06T06:54:40Z","date_created":"2020-12-23T09:08:57Z","author":[{"last_name":"Brinda","full_name":"Brinda, Torsten","first_name":"Torsten"},{"last_name":"Diethelm","full_name":"Diethelm, Ira","first_name":"Ira"},{"last_name":"Hellmig","full_name":"Hellmig, Lutz","first_name":"Lutz"},{"first_name":"Johannes","last_name":"Magenheim","full_name":"Magenheim, Johannes"},{"first_name":"Ralf","full_name":"Romeike, Ralf","last_name":"Romeike"},{"first_name":"Ulrik","last_name":"Schroeder","full_name":"Schroeder, Ulrik"}],"volume":33,"year":"2018","citation":{"ama":"Brinda T, Diethelm I, Hellmig L, Magenheim J, Romeike R, Schroeder U. Kritische Entgegnung auf die Studie “Zur Relevanz informatischer Bildung in der Schule für den Erwerb computer- bzw. informationsbezogener Kompetenzen.” <i>MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung</i>. 2018;33(Didaktik der Informatik):1-10. doi:<a href=\"https://doi.org/10.21240/mpaed/33/2018.10.29.X\">10.21240/mpaed/33/2018.10.29.X</a>","chicago":"Brinda, Torsten, Ira Diethelm, Lutz Hellmig, Johannes Magenheim, Ralf Romeike, and Ulrik Schroeder. “Kritische Entgegnung auf die Studie ‘Zur Relevanz informatischer Bildung in der Schule für den Erwerb computer- bzw. informationsbezogener Kompetenzen.’” <i>MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung</i> 33, no. Didaktik der Informatik (2018): 1–10. <a href=\"https://doi.org/10.21240/mpaed/33/2018.10.29.X\">https://doi.org/10.21240/mpaed/33/2018.10.29.X</a>.","ieee":"T. Brinda, I. Diethelm, L. Hellmig, J. Magenheim, R. Romeike, and U. 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