Part 1: Evaluating media claims about sustainability through the use of large data sets

Part 2: A learner-centered approach to teaching computational modeling, data analysis, and programming

Part 2: Reading and Writing the World with Data - Travis Weiland (USA)

Part 1: NLP Research in the Age of Large Language Models – Henning Wachsmuth

Part 1: How much mathematical modeling is in AI? - Martin Frank and Sarah Schönbrodt (Germany)

Part 2: Reasoning with Data in School-Based Citizen Science - Dani Ben-Zvi (Israel)

Part 1: Using Computational Essays to Support Student Creativity and Agency in Science - Tor Ole Odden (Norway)

Part 2: Design decisions in creating short data science courses for pre-university students - Tom Button and Ian Dickerson (UK)

Part 2: Teaching Social Responsibility for a Tech-Powered World - Francine Berman (USA)

Part 1: Teaching reproducibility and responsible workflows - Nick Horton (USA)

Part 2: A hands-on workshop to develop a set of potential goals for learning about AI - Jane Waite (England)

Part 1: Learning About and Learning with Artificial Intelligence in School: From Understanding of Basic AI Concepts to Trustworthy and Human-centric AI Tools - Ute Schmid (Germany)

Part 2: Epistemic Programming and Creative Coding: Programming as an Empowering Means for Self-Expression and Communication - Sven Hüsing, Carsten Schulte and Dan Verständig (Germany)

Part 1: Roadmap to Computational Thinking for the AI age: A challenge for Mathematics and Computer Science Education - Conrad Wolfram (England)

Part 1: My AI discriminates? How could this happen and who is to blame? - Marc Hauer (Germany)
Part 2: A Framework for Exploring the Purposes and Processes of Data Wrangling in Complex Self-Directed Analysis Tasks - Michelle Hoda Wilkerson (USA)

Part 1: Data Awareness: Be aware of the data! - Lukas Höper and Carsten Schulte (Germany)
Part 2: Teaching Core Principles of Machine Learning with a Simple Machine Learning Algorithm: The Case of the KNN Algorithm  - Orit Hazzan and Koby Mike (Israel)

Part 1: Why Computing Education, and Especially CT, Needs a Broader Perspective! - Arnold Pears (Sweden)
Part 2: Education for a fast-changing world: Conceptions of Statistical Literacy and Data Science - Jim Ridgway (England)

Part 1: Learning data science through civic engagement with open data - Graham Dove (USA)
Part 2: Why should students take a data science course? - Rob Gould (USA)

Part 1: Beyond Bias. Locating questions of injustice in Data Science and Artificial Intelligence - Tobias Matzner (Germany)
Part 2: Bringing together statistics and computer science education: Machine learning by decision trees grounded in students’ data exploration experiences - Rolf Biehler and Yannik Fleischer (Germany)

Data Detective Clubs in the Time of COVID-19 - Jan Mokros and Bill Finzer (USA)

Part 1: Data Detective Clubs in the Time of COVID-19 - Jan Mokros and Bill Finzer (USA)
Part 2: Teaching machine learning in school: Some emerging research trajectories - Matti Tedre and Henriikka Vartiainen (Finland)