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Technical University of Munich

Data & AI Literacy

In recent years, the handling, processing, and analysis of data, e.g. in the context of Big Data and machine learning, has developed enormously - due to the transformation processes of digitalization. The increasing collection, storage, and automated processing and evaluation of data in all areas of human life also have an enormous impact on everyday life, society, and politics. Today, everyone needs the skills to store, use and analyze data competently, but also to assess the consequences and effects on our society. Teaching the corresponding competencies - so-called "data literacy" - is a major challenge for schools, universities, and education in general. Artificial intelligence, the most emergent topic of recent years, is of particular importance in this context. It is essential to prepare learners for a life in the digital world. Therefore, it is crucial to impart competencies that - independent of current technologies and "hypes" - enable students to understand and shape the so-called digital world in the long term. In this research area, underlying ideas and principles will be identified that are independent of concrete technologies or applications and thus contribute to sustainable teaching. These ideas and principles are prepared and evaluated in the form of teaching-learning concepts for learners, and their transfer into teaching practice is investigated.

Selected Projects in this Research Area

Selected Publications

  • Losch, Daniel; Jaschke, Steffen; Michaeli, Tilman; Opel, Simone; Schmid, Ute; Seegerer, Stefan; Stechert, Peer: Was alle über Künstliche Intelligenz wissen sollen und wie KI-bezogene Kompetenzen in der Schule entwickelt werden können. Informatik Spektrum, 2025, 1--9 more… BibTeXWWW
  • Kafai, Y., Shapiro, R. B., Jetzinger, F., Michaeli, T., Tedre, M., Vartiainen, H., Iivari, N., Musaeus, L. H., Iversen, O. S., Ali, S., Bodon, H., Butler, M., Kshirsagar, K., Smith, M., Quiterio, A., Worsley, M., Kumar, V., Morales-Navarro, L., Noh, D., Pea, R., & Philip, T. M.: Youth as Designers of Artificial Intelligence and Machine Learning Technologies: What do we Know About the Opportunities and Challenges of K-12 Students Creating Their Own Applications? Proceedings of the 19th International Conference of the Learning Sciences - ICLS 2025, International Society of the Learning Sciences, 2025, 2260-2268 more… BibTeXWWW
  • Hügle, Jadga; Michaeli, Tilman; Seegerer, Stefan: Exploring the World of AI: Experiences from a MOOC on Artificial Intelligence for a Broad Audience. 2024 IEEE 3rd German Education Conference (GECon), IEEE, 2024, 1-6 more… BibTeXWWW
  • Jetzinger, F., Baumer, S. & Michaeli, T.: Artificial Intelligence in Compulsory K-12 Computer Science Classrooms: A Scalable Professional Development Offer for Computer Science Teachers. Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE 2024), Association for Computing Machinery, 2024, 590-596 more… BibTeXWWW
  • Hartl, A., Starke, E., Voggenreiter, A., Holzberger, D., Michaeli, T. & Pfeffer, J.: Empowering Digital Natives: InstaClone – a Novel Approach to Data Literacy Education in the Age of Social Media. Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE 2024), Association for Computing Machinery, 2024, 484-490 more… BibTeXWWW
  • Elhashemy, Hanya; Abelson, Harold; Michaeli, Tilman: Adapting Computational Skills for AI Integration. 2024 IEEE 36th International Conference on Software Engineering Education and Training (CSEE&T), IEEE, 2024, 1-5 more… BibTeXWWW
  • Jetzinger, Franz: Evidence-based advancement of teaching AI in K-12: an action research approach. Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research (WiPSCE '24), Association for Computing Machinery, 2024, 1-2 more… BibTeXWWW
  • Kasneci, Enkelejda; Sessler, Kathrin; Küchemann, Stefan; Bannert, Maria; Dementieva, Daryna; Fischer, Frank; Gasser, Urs; Groh, Georg; Günnemann, Stephan; Hüllermeier, Eyke; Krusche, Stepha; Kutyniok, Gitta; Michaeli, Tilman; Nerdel, Claudia; Pfeffer, Jürgen; Poquet, Oleksandra; Sailer, Michael; Schmidt, Albrecht; Seidel, Tina; Stadler, Matthias; Weller, Jochen; Kuhn, Jochen; Kasneci, Gjergji: ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences 103, 2023, 1-9 more… BibTeXWWW
  • Michaeli, T., Romeike, R. & Seegerer, S.: What students can learn about artificial intelligence - recommendations for K12 computing education. Proceedings of World Conference on Computers in Education, WCCE 2022, 2023, 196-208 more… BibTeXWWW
  • Baumer S.,Jetzinger F., Michaeli T.: Künstliche Intelligenz im verpflichtenden Informatikunterricht: Ein skalierbares Fortbildungsangebot für Informatikehrkräfte. INFORMATIK 2023, Workshop KI Bildung, Gesellschaft für Informatik, 2023, 399-402 more… BibTeXWWW
  • Morales-Navarro, L., Kafai, Y. Kahn, K., Romeike, R., Michaeli, T., DiPaola, D., Ali, S., Williams, R., Breazeal, C., Castro, F., Desportes, K., Stager, G., Kumar, V., Bodon, H., Worsley, M., Lee, V., Sarin, P., Xie, B., Wolf, J., Sieh, I., Dennison, D., Garcia, R. & Solomon, C.: Constructionist Approaches to Learning Artificial Intelligence/Machine Learning: Past, Present, and Future. Proceedings of Constructionism 2023, 2023, 245-254 more… BibTeXWWW
  • Diethelm, Ira; Fandrich, Anatolij; Michaeli, Tilman; Pancratz, Nils; Romeike, Ralf; Seegerer, Stefan: Gemeinsam KI entdecken! INFOS 2021 – 19. GI-Fachtagung Informatik und Schule, Gesellschaft für Informatik, Bonn, 2021, 339 more… BibTeXWWW
  • Michaeli, Tilman; Seegerer, Stefan; Romeike, Ralf: Alexa, was ist eigentlich Künstliche Intelligenz? Einblicke in KI als Gegenstand und Methode fachdidaktischer Forschung. GFD Tagungsband 2020: Fachliche Bildung und digitale Transformation - Fachdidaktische Forschung und Diskurse, 2021, 72-75 more… BibTeXWWW
  • Seegerer, Stefan; Michaeli, Tilman; Lindner, Annabel; Romeike, Ralf; Koerber, Bernhard: EDITORIAL: Jetzt ist KI-Sommer! LOG IN - Informatische Bildung und Computer in der Schule, 2020, 3 more… BibTeXWWW
  • Michaeli, Tilman; Seegerer, Stefan; Jatzlau, Sven: Kein Hexenwerk – Ideen des maschinellen Lernens in Snap! LOG IN - Informatische Bildung und Computer in der Schule, 2020, 66-70 more… BibTeXWWW
  • Michaeli, Tilman; Seegerer, Stefan; Jatzlau, Sven; Romeike, Ralf: Looking Beyond Supervised Classification and Image Recognition – Unsupervised Learning with Snap! Constructionism 2020: Exploring, Testing and Extending our Understanding of Constructionism conference proceedings, 2020, 395-402 more… BibTeXWWW
  • Jatzlau, Sven; Michaeli, Tilman; Seegerer, Stefan; Romeike, Ralf: It’s not Magic After All - Machine Learning in Snap! using Reinforcement Learning. 2019 IEEE Blocks and Beyond Workshop (Blocks and Beyond), IEEE, 2019, 37-41 more… BibTeXWWW

Teaching material

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