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ACM; 2023. doi:<a href=\"https://doi.org/10.1145/3631802.3631824\">10.1145/3631802.3631824</a>"},"date_updated":"2024-04-11T12:30:59Z","publisher":"ACM","date_created":"2024-03-08T08:02:10Z","author":[{"last_name":"Sparmann","id":"63216","full_name":"Sparmann, Sören","first_name":"Sören"},{"first_name":"Sven","last_name":"Hüsing","full_name":"Hüsing, Sven","id":"58465"},{"last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten","first_name":"Carsten"}],"title":"JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks","doi":"10.1145/3631802.3631824"},{"status":"public","publication":"Computer Science Education","type":"book_chapter","language":[{"iso":"eng"}],"_id":"40511","department":[{"_id":"67"}],"user_id":"58465","year":"2023","citation":{"ieee":"S. Hüsing, C. Schulte, and F. Winkelnkemper, “Epistemic Programming,” in <i>Computer Science Education</i>, Bloomsbury Academic, 2023.","chicago":"Hüsing, Sven, Carsten Schulte, and Felix Winkelnkemper. “Epistemic Programming.” In <i>Computer Science Education</i>. Bloomsbury Academic, 2023. <a href=\"https://doi.org/10.5040/9781350296947.ch-022\">https://doi.org/10.5040/9781350296947.ch-022</a>.","ama":"Hüsing S, Schulte C, Winkelnkemper F. Epistemic Programming. In: <i>Computer Science Education</i>. Bloomsbury Academic; 2023. doi:<a href=\"https://doi.org/10.5040/9781350296947.ch-022\">10.5040/9781350296947.ch-022</a>","apa":"Hüsing, S., Schulte, C., &#38; Winkelnkemper, F. (2023). Epistemic Programming. In <i>Computer Science Education</i>. Bloomsbury Academic. <a href=\"https://doi.org/10.5040/9781350296947.ch-022\">https://doi.org/10.5040/9781350296947.ch-022</a>","mla":"Hüsing, Sven, et al. “Epistemic Programming.” <i>Computer Science Education</i>, Bloomsbury Academic, 2023, doi:<a href=\"https://doi.org/10.5040/9781350296947.ch-022\">10.5040/9781350296947.ch-022</a>.","short":"S. Hüsing, C. Schulte, F. Winkelnkemper, in: Computer Science Education, Bloomsbury Academic, 2023.","bibtex":"@inbook{Hüsing_Schulte_Winkelnkemper_2023, title={Epistemic Programming}, DOI={<a href=\"https://doi.org/10.5040/9781350296947.ch-022\">10.5040/9781350296947.ch-022</a>}, booktitle={Computer Science Education}, publisher={Bloomsbury Academic}, author={Hüsing, Sven and Schulte, Carsten and Winkelnkemper, Felix}, year={2023} }"},"publication_identifier":{"isbn":["9781350296916","9781350296909","9781350296930","9781350296923","9781350296947"]},"publication_status":"published","title":"Epistemic Programming","doi":"10.5040/9781350296947.ch-022","date_updated":"2023-01-27T12:26:06Z","publisher":"Bloomsbury Academic","author":[{"first_name":"Sven","id":"58465","full_name":"Hüsing, Sven","last_name":"Hüsing"},{"last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten","first_name":"Carsten"},{"full_name":"Winkelnkemper, Felix","id":"3117","last_name":"Winkelnkemper","first_name":"Felix"}],"date_created":"2023-01-27T12:25:37Z"},{"abstract":[{"lang":"eng","text":"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."}],"status":"public","publication":"STATISTICS EDUCATION RESEARCH JOURNAL","type":"journal_article","keyword":["Education","Statistics and Probability"],"article_number":"6","language":[{"iso":"eng"}],"_id":"32335","department":[{"_id":"67"}],"user_id":"58465","year":"2022","intvolume":"        21","citation":{"ama":"PODWORNY S, Hüsing S, SCHULTE C. A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>. 2022;21(2). doi:<a href=\"https://doi.org/10.52041/serj.v21i2.46\">10.52041/serj.v21i2.46</a>","ieee":"S. PODWORNY, S. Hüsing, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>, vol. 21, no. 2, Art. no. 6, 2022, doi: <a href=\"https://doi.org/10.52041/serj.v21i2.46\">10.52041/serj.v21i2.46</a>.","chicago":"PODWORNY, SUSANNE, Sven Hüsing, and CARSTEN SCHULTE. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i> 21, no. 2 (2022). <a href=\"https://doi.org/10.52041/serj.v21i2.46\">https://doi.org/10.52041/serj.v21i2.46</a>.","apa":"PODWORNY, S., Hüsing, S., &#38; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>, <i>21</i>(2), Article 6. <a href=\"https://doi.org/10.52041/serj.v21i2.46\">https://doi.org/10.52041/serj.v21i2.46</a>","short":"S. PODWORNY, S. Hüsing, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL 21 (2022).","mla":"PODWORNY, SUSANNE, et al. “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING.” <i>STATISTICS EDUCATION RESEARCH JOURNAL</i>, vol. 21, no. 2, 6, International Association for Statistical Education, 2022, doi:<a href=\"https://doi.org/10.52041/serj.v21i2.46\">10.52041/serj.v21i2.46</a>.","bibtex":"@article{PODWORNY_Hüsing_SCHULTE_2022, title={A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}, volume={21}, DOI={<a href=\"https://doi.org/10.52041/serj.v21i2.46\">10.52041/serj.v21i2.46</a>}, number={26}, journal={STATISTICS EDUCATION RESEARCH JOURNAL}, publisher={International Association for Statistical Education}, author={PODWORNY, SUSANNE and Hüsing, Sven and SCHULTE, CARSTEN}, year={2022} }"},"publication_identifier":{"issn":["1570-1824"]},"publication_status":"published","issue":"2","title":"A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING","doi":"10.52041/serj.v21i2.46","date_updated":"2022-07-08T12:07:46Z","publisher":"International Association for Statistical Education","volume":21,"author":[{"first_name":"SUSANNE","full_name":"PODWORNY, SUSANNE","last_name":"PODWORNY"},{"last_name":"Hüsing","full_name":"Hüsing, Sven","id":"58465","first_name":"Sven"},{"full_name":"SCHULTE, CARSTEN","last_name":"SCHULTE","first_name":"CARSTEN"}],"date_created":"2022-07-08T12:06:48Z"},{"language":[{"iso":"eng"}],"_id":"35674","department":[{"_id":"363"},{"_id":"67"}],"user_id":"37888","abstract":[{"lang":"eng","text":"<jats:p>We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.</jats:p>"}],"editor":[{"first_name":"S. A.","full_name":"Peters, S. A.","last_name":"Peters"},{"last_name":"Zapata-Cardona","full_name":"Zapata-Cardona, L.","first_name":"L."},{"last_name":"Bonafini","full_name":"Bonafini, F.","first_name":"F."},{"first_name":"A.","full_name":"Fan, A.","last_name":"Fan"}],"status":"public","publication":"Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics","type":"conference","title":"Jupyter Notebooks for Teaching, Learning, and Doing Data Science","doi":"10.52041/iase.icots11.t10e3","publisher":"International Association for Statistical Education","date_updated":"2024-08-21T10:03:47Z","date_created":"2023-01-10T08:50:47Z","author":[{"full_name":"Fleischer, Franz Yannik","id":"42660","last_name":"Fleischer","orcid":"https://orcid.org/0000-0003-0318-0329","first_name":"Franz Yannik"},{"last_name":"Hüsing","id":"58465","full_name":"Hüsing, Sven","first_name":"Sven"},{"first_name":"Rolf","id":"16274","full_name":"Biehler, Rolf","last_name":"Biehler"},{"first_name":"Susanne","id":"30619","full_name":"Podworny, Susanne","orcid":"0000-0002-6313-5987","last_name":"Podworny"},{"first_name":"Carsten","last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten"}],"year":"2022","citation":{"ama":"Fleischer FY, Hüsing S, Biehler R, Podworny S, Schulte C. Jupyter Notebooks for Teaching, Learning, and Doing Data Science. In: Peters SA, Zapata-Cardona L, Bonafini F, Fan A, eds. <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>. International Association for Statistical Education; 2022. doi:<a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">10.52041/iase.icots11.t10e3</a>","ieee":"F. Y. Fleischer, S. Hüsing, R. Biehler, S. Podworny, and C. Schulte, “Jupyter Notebooks for Teaching, Learning, and Doing Data Science,” in <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>, 2022, doi: <a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">10.52041/iase.icots11.t10e3</a>.","chicago":"Fleischer, Franz Yannik, Sven Hüsing, Rolf Biehler, Susanne Podworny, and Carsten Schulte. “Jupyter Notebooks for Teaching, Learning, and Doing Data Science.” In <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>, edited by S. A. Peters, L. Zapata-Cardona, F. Bonafini, and A. Fan. International Association for Statistical Education, 2022. <a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">https://doi.org/10.52041/iase.icots11.t10e3</a>.","apa":"Fleischer, F. Y., Hüsing, S., Biehler, R., Podworny, S., &#38; Schulte, C. (2022). Jupyter Notebooks for Teaching, Learning, and Doing Data Science. In S. A. Peters, L. Zapata-Cardona, F. Bonafini, &#38; A. Fan (Eds.), <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>. International Association for Statistical Education. <a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">https://doi.org/10.52041/iase.icots11.t10e3</a>","mla":"Fleischer, Franz Yannik, et al. “Jupyter Notebooks for Teaching, Learning, and Doing Data Science.” <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>, edited by S. A. Peters et al., International Association for Statistical Education, 2022, doi:<a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">10.52041/iase.icots11.t10e3</a>.","bibtex":"@inproceedings{Fleischer_Hüsing_Biehler_Podworny_Schulte_2022, title={Jupyter Notebooks for Teaching, Learning, and Doing Data Science}, DOI={<a href=\"https://doi.org/10.52041/iase.icots11.t10e3\">10.52041/iase.icots11.t10e3</a>}, 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}, author={Fleischer, Franz Yannik and Hüsing, Sven and Biehler, Rolf and Podworny, Susanne and Schulte, Carsten}, editor={Peters, S. A. and Zapata-Cardona, L. and Bonafini, F. and Fan, A.}, year={2022} }","short":"F.Y. Fleischer, S. Hüsing, R. Biehler, S. Podworny, C. Schulte, in: S.A. Peters, L. Zapata-Cardona, F. Bonafini, A. Fan (Eds.), Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, International Association for Statistical Education, 2022."},"publication_status":"published"},{"status":"public","abstract":[{"lang":"eng","text":"<jats:p>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.</jats:p>"}],"publication":"Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics","type":"conference","language":[{"iso":"eng"}],"department":[{"_id":"67"}],"user_id":"58465","_id":"40510","citation":{"ama":"Podworny S, Fleischer Y, Hüsing S. Grade 6 Students’ Perception and Use of Data-Based Decision Trees. In: <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>. International Association for Statistical Education; 2022. doi:<a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">10.52041/iase.icots11.t2h3</a>","chicago":"Podworny, Susanne, Yannik Fleischer, and Sven Hüsing. “Grade 6 Students’ Perception and Use of Data-Based Decision Trees.” In <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>. International Association for Statistical Education, 2022. <a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">https://doi.org/10.52041/iase.icots11.t2h3</a>.","ieee":"S. Podworny, Y. Fleischer, and S. Hüsing, “Grade 6 Students’ Perception and Use of Data-Based Decision Trees,” 2022, doi: <a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">10.52041/iase.icots11.t2h3</a>.","short":"S. Podworny, Y. Fleischer, S. Hüsing, in: Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, International Association for Statistical Education, 2022.","bibtex":"@inproceedings{Podworny_Fleischer_Hüsing_2022, title={Grade 6 Students’ Perception and Use of Data-Based Decision Trees}, DOI={<a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">10.52041/iase.icots11.t2h3</a>}, 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}, author={Podworny, Susanne and Fleischer, Yannik and Hüsing, Sven}, year={2022} }","mla":"Podworny, Susanne, et al. “Grade 6 Students’ Perception and Use of Data-Based Decision Trees.” <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>, International Association for Statistical Education, 2022, doi:<a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">10.52041/iase.icots11.t2h3</a>.","apa":"Podworny, S., Fleischer, Y., &#38; Hüsing, S. (2022). Grade 6 Students’ Perception and Use of Data-Based Decision Trees. <i>Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics</i>. <a href=\"https://doi.org/10.52041/iase.icots11.t2h3\">https://doi.org/10.52041/iase.icots11.t2h3</a>"},"year":"2022","publication_status":"published","doi":"10.52041/iase.icots11.t2h3","title":"Grade 6 Students’ Perception and Use of Data-Based Decision Trees","date_created":"2023-01-27T12:23:45Z","author":[{"first_name":"Susanne","last_name":"Podworny","full_name":"Podworny, Susanne"},{"last_name":"Fleischer","full_name":"Fleischer, Yannik","first_name":"Yannik"},{"first_name":"Sven","last_name":"Hüsing","full_name":"Hüsing, Sven","id":"58465"}],"date_updated":"2023-01-27T12:24:33Z","publisher":"International Association for Statistical Education"},{"language":[{"iso":"eng"}],"_id":"30937","user_id":"58465","department":[{"_id":"67"}],"abstract":[{"lang":"eng","text":"<jats:p>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.</jats:p>"}],"status":"public","type":"conference","publication":"Proceedings of the IASE 2021 Satellite Conference","title":"Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School","main_file_link":[{"url":"https://iase-web.org/documents/papers/sat2021/IASE2021%20Satellite%20156_HUSING.pdf?1649974216"}],"doi":"10.52041/iase.zwwoh","date_updated":"2023-01-30T12:10:57Z","publisher":"International Association for Statistical Education","date_created":"2022-04-22T08:30:59Z","author":[{"first_name":"Sven","last_name":"Hüsing","full_name":"Hüsing, Sven","id":"58465"},{"first_name":"Susanne","full_name":"Podworny, Susanne","last_name":"Podworny"}],"year":"2022","citation":{"ieee":"S. Hüsing and S. Podworny, “Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School,” 2022, doi: <a href=\"https://doi.org/10.52041/iase.zwwoh\">10.52041/iase.zwwoh</a>.","chicago":"Hüsing, Sven, and Susanne Podworny. “Computational Essays as an Approach for Reproducible Data Analysis in Lower Secondary School.” In <i>Proceedings of the IASE 2021 Satellite Conference</i>. International Association for Statistical Education, 2022. <a href=\"https://doi.org/10.52041/iase.zwwoh\">https://doi.org/10.52041/iase.zwwoh</a>.","ama":"Hüsing S, Podworny S. Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School. In: <i>Proceedings of the IASE 2021 Satellite Conference</i>. International Association for Statistical Education; 2022. doi:<a href=\"https://doi.org/10.52041/iase.zwwoh\">10.52041/iase.zwwoh</a>","apa":"Hüsing, S., &#38; Podworny, S. (2022). Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School. <i>Proceedings of the IASE 2021 Satellite Conference</i>. <a href=\"https://doi.org/10.52041/iase.zwwoh\">https://doi.org/10.52041/iase.zwwoh</a>","mla":"Hüsing, Sven, and Susanne Podworny. “Computational Essays as an Approach for Reproducible Data Analysis in Lower Secondary School.” <i>Proceedings of the IASE 2021 Satellite Conference</i>, International Association for Statistical Education, 2022, doi:<a href=\"https://doi.org/10.52041/iase.zwwoh\">10.52041/iase.zwwoh</a>.","short":"S. Hüsing, S. Podworny, in: Proceedings of the IASE 2021 Satellite Conference, International Association for Statistical Education, 2022.","bibtex":"@inproceedings{Hüsing_Podworny_2022, title={Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School}, DOI={<a href=\"https://doi.org/10.52041/iase.zwwoh\">10.52041/iase.zwwoh</a>}, booktitle={Proceedings of the IASE 2021 Satellite Conference}, publisher={International Association for Statistical Education}, author={Hüsing, Sven and Podworny, Susanne}, year={2022} }"},"publication_status":"published"},{"editor":[{"last_name":"Seppälä","full_name":"Seppälä, Otto","first_name":"Otto"},{"full_name":"Petersen, Andrew","last_name":"Petersen","first_name":"Andrew"}],"status":"public","publication":"Koli Calling '21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021","type":"conference","language":[{"iso":"eng"}],"_id":"27494","department":[{"_id":"67"}],"user_id":"21145","year":"2021","page":"42:1-42:3","citation":{"ama":"Hüsing S. Epistemic Programming - An insight-driven programming concept for Data Science. In: Seppälä O, Petersen A, eds. <i>Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021</i>. ACM; 2021:42:1-42:3. doi:<a href=\"https://doi.org/10.1145/3488042.3490510\">10.1145/3488042.3490510</a>","ieee":"S. Hüsing, “Epistemic Programming - An insight-driven programming concept for Data Science,” in <i>Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021</i>, 2021, p. 42:1-42:3, doi: <a href=\"https://doi.org/10.1145/3488042.3490510\">10.1145/3488042.3490510</a>.","chicago":"Hüsing, Sven. “Epistemic Programming - An Insight-Driven Programming Concept for Data Science.” In <i>Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021</i>, edited by Otto Seppälä and Andrew Petersen, 42:1-42:3. ACM, 2021. <a href=\"https://doi.org/10.1145/3488042.3490510\">https://doi.org/10.1145/3488042.3490510</a>.","apa":"Hüsing, S. (2021). Epistemic Programming - An insight-driven programming concept for Data Science. In O. Seppälä &#38; A. Petersen (Eds.), <i>Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021</i> (p. 42:1-42:3). 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