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 -