Symposium on Integrating AI and Data Science into School Education Across Disciplines

AIDEA
24. – 28. February 2025
Salzburg, Austria

2 minutes

The symposium provides a platform to present and discuss ongoing research projects, findings, ideas and initiatives in the field of AI and Data Science education. It provides opportunities to initiate new interdisciplinary projects.

Landscape

Image generated with DreamStudio by stability.ai

Idea of the Symposium

AI technologies affect our daily lives and especially the lives of young people in almost all areas of life and are predicted to do so even more in the future. Therefore, AI education should be discussed from different educational perspectives and implemented at an early stage. This should include promoting an understanding of how AI systems work, as well as their limitations, opportunities, risks and creative potentials.

AI and Data Science literacy are increasingly essential subjects that need to be addressed in school curricula. In today’s digital age, data is being generated at an unprecedented rate. Thus, understanding how to analyze and interpret data is crucial to making informed decisions in a variety of fields. Data science literacy enables students to extract valuable insights from vast amounts of data and to make evidence-based decisions and solve complex problems. In addition, AI literacy is vital as AI becomes ubiquitous in our lives, influencing everything from the products we use to the way we work and live. Familiarity with AI concepts and applications enables students to understand and engage with the rapidly evolving technology landscape, fostering innovation and ensuring they can navigate the future with confidence and adaptability.

The symposium aims to promote a broad understanding of the educational opportunities and challenges of AI as part of school subjects and of how to equip individuals, especially students at school level, with the knowledge and skills needed to navigate effectively in the AI-driven world. It focuses on education for learning AI and data science and the development of mathematical, statistical and computer science skills that can be linked to AI and data literacy. The mere use of AI technologies in an educational context is not the focus of the symposium.

Scientific Program Committee

    Related Projects

    Sponsors

    We thank the Deutsche Telekom Stiftung as the main sponsor of this symposium.
    Further sponsors are the Institute of Mathematics at the Paris Lodron University Salzburg and the Federal State Salzburg (Nr. F2400744-KOV).

Collections

Pages

January 0001

Timetable

Sunday, 23.02.2025 Monday, 24.02.2025 Tuesday, 25.02.2025 Wednesday, 26.02.2025 Thursday, 27.02.2025 Friday, 28.02.2025 09:00 – 10:30 TBA TBA TBA TBA TBA 10:30 – 11:00 Coffee Break Coffee Break Coffee Break Coffee Break TBA 10:30 – 12:30 TBA TBA TBA TBA 12:30 – 14:00 Lunch Lunch Lunch Lunch 14:00 – 15:30 TBA TBA Social Event TBA 16:00 – 18:00 TBA TBA Social Event TBA Evening Pre-conference dinner Symposium dinner Participation throughout the entire symposium is encouraged.

1 minute

Timetable

Start: 24 February 2025, 9am! End: 28 February 2025, 6pm Participation throughout the entire symposium is encouraged. Activities Plenary talks (approx. 50’) Short talks (approx. 25’) Poster sessions Discussion rounds (daily); results are presented in plenary phases Social activities for community building Sponsored by Deutsche Telekom Stiftung.

1 minute

Participants

Juliane Ahlborn (Germany) Christian Andersson (Sweden) Katharina Bata (Germany) Arne Bathke (Austria) Marc Berges (Germany) Rolf Biehler (Germany) Karin Binder (Germany) Zarek Drozda (USA) Jakim Eckert (Germany) Joachim Engel (Germany) Tim Erickson (USA) Yannik Fleischer (Germany) Martin Frank (Germany) Iddo Gal (Isreal) Harald Gapski (Germany) Martin Geroldinger (Austria) Anja Gärtig-Daugs (Germany) Orit Hazzan (Isreal) Hannes Heusel (Germany) Lukas Höper (Germany) Sven Hüsing (Germany) Karl-Emil Kjær Bilstrup (Denmark) Kate Miller (USA) Andreas Mühling (Germany) Arnold Pears (Sweden) Susanne Podworny (Germany) Sue Sentance (UK) Steffen Schneider (Germany) Sarah Schönbrodt (Austria) Katharina Schüller (Germany) Carsten Schulte (Germany) Gerald Steinbauer-Wagner (Austria) Matti Tedre (Finland) Henriikka Vartiainen (Finland) Dan Verständig (Germany) Jane Waite (UK) Travis Weiland (USA) Michelle Wilkerson (USA) The list is updated continuously.

1 minute

Location

The workshop takes place at the Paris Lodron University of Salzburg, Austria. The venue address is Hellbrunnerstraße 34, 5020 Salzburg (Google Maps). Sponsored by Deutsche Telekom Stiftung.

1 minute

Focus topics

The following focus topics will be addressed and discussed in various sessions: Data and Problems What data and related contextual problems are appropriate for designing learning opportunities related to AI? What do students need to know about the concept of data to do data science and understand AI? Tools Which (digital) tools are suitable or adaptable for teaching, learning and doing data science and AI at school level? Explanatory Models What kind of educational and explanatory models–on which level of detail and abstraction–are suitable for what learners?

2 minutes