Archive

Overview of all previous sessions of the colloquium and the published slides and recordings

Previous Sessions

Session 16 - Part 1: Anna Ferguson (New Zealand)

Introducing a data science perspective on predictive modelling within a large introductory statistics course: Connecting research with practice
  • 11.12.2024
  • 13.00-14.00 Uhr
  • (UTC+1)

Session 16 - Part 2: Takashi Kawakami (Japan)

Data-driven modelling approach with mathematical and statistical models at its core in school and teacher education: A focus on a societal perspective
  • 11.12.2024
  • 14.00-15.00 Uhr
  • (UTC+1)

Session 15 - Part 1: Josephine Louie (USA)

Supporting critical data literacy for civic engagement and social justice
  • 19.06.2024
  • 16.00-17.00 Uhr
  • (UTC+2)

Session 15 - Part 2: Joachim Engel (Germany)

Critical data literacy for democracy education
  • 19.06.2024
  • 17.10-18.10 Uhr
  • (UTC+2)

Session 14 - Part 2: Yasmin B. Kafai & Luis Morales-Navarro (USA)

High School Youth Peer Auditing of Machine Learning-Powered Applications to Promote Computational Literacies
  • 17.04.2024
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 14 - Part 1: Ismaila Sanusi (Finland)

The Role of Data in Artificial Intelligence Literacy in school education
  • 17.04.2024
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 13 - Part 1: Vince Geiger (Australia)

Evaluating media claims about sustainability through the use of large data sets
  • 24.01.2024
  • 16.00-17.30 Uhr
  • (UTC+1)

Session 13 - Part 2: Devin W. Silvia (USA)

A learner-centered approach to teaching computational modeling, data analysis, and programming
  • 24.01.2024
  • 17.30-19.00 Uhr
  • (UTC+1)

Session 12 - Part 2: Travis Weiland (USA)

Reading and Writing the World with Data
  • 29.11.2023
  • 17.30-19.00 Uhr
  • (UTC+1)

Session 12 - Part 1: Henning Wachsmuth (Germany)

NLP Research in the Age of Large Language Models
  • 29.11.2023
  • 16.00-17.30 Uhr
  • (UTC+1)

Session 11 - Part 1: Martin Frank and Sarah Schönbrodt (Germany)

How much mathematical modeling is in AI?
  • 17.05.2023
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 11 - Part 2: Dani Ben-Zvi (Israel)

Reasoning with Data in School-Based Citizen Science
  • 17.05.2023
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 10 - Part 1: Tor Ole Odden (Norway)

Using Computational Essays to Support Student Creativity and Agency in Science
  • 18.01.2023
  • 17.00-19.30 Uhr
  • (UTC+1)

Session 10 - Part 2: Tom Button and Ian Dickerson (UK)

Design decisions in creating short data science courses for pre-university students
  • 18.01.2023
  • 18.30-19.30 Uhr
  • (UTC+1)

Session 09 - Part 2: Francine Berman (USA)

Teaching Social Responsibility for a Tech-Powered World
  • 18.01.2023
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 09 - Part 1: Nick Horton (USA)

Teaching reproducibility and responsible workflows
  • 18.01.2023
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 08 - Part 2: Jane Waite (England)

A hands-on workshop to develop a set of potential goals for learning about AI
  • 07.12.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 08 - Part 1: Ute Schmid (Germany)

Learning About and Learning with Artificial Intelligence in School: From Understanding of Basic AI Concepts to Trustworthy and Human-centric AI Tools
  • 07.12.2022
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 07 - Part 2: Sven Hüsing, Carsten Schulte and Dan Verständig (Germany)

Epistemic Programming and Creative Coding: Programming as an Empowering Means for Self-Expression and Communication
  • 02.11.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 07 - Part 1: Conrad Wolfram (England)

Roadmap to Computational Thinking for the AI age: A challenge for Mathematics and Computer Science Education
  • 02.11.2022
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 06 - Part 1: Marc Hauer (Germany)

My AI discriminates? How could this happen and who is to blame?
  • 02.06.2022
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 06 - Part 2: Michelle Hoda Wilkerson (USA)

A Framework for Exploring the Purposes and Processes of Data Wrangling in Complex Self-Directed Analysis Tasks
  • 02.06.2022
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 05 - Part 2: Orit Hazzan and Koby Mike (Israel)

Teaching Core Principles of Machine Learning with a Simple Machine Learning Algorithm: The Case of the KNN Algorithm 
  • 18.05.2022
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 05 - Part 1: Lukas Höper and Carsten Schulte (Germany)

Data Awareness: Be aware of the data!
  • 18.05.2022
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 04 - Part 2: Jim Ridgway (England)

Education for a fast-changing world: Conceptions of Statistical Literacy and Data Science
  • 01.04.2022
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 04 - Part 1: Arnold Pears (Sweden)

Why Computing Education, and Especially CT, Needs a Broader Perspective!
  • 01.04.2022
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 03 - Part 2: Rob Gould (USA)

Why should students take a data science course?
  • 02.01.2022
  • 17.30-19.00 Uhr
  • (UTC+1)

Session 03 - Part 1: Graham Dove (USA)

Learning data science through civic engagement with open data
  • 02.01.2022
  • 16.00-17.30 Uhr
  • (UTC+1)

Session 02 - Part 2: Rolf Biehler and Yannik Fleischer (Germany)

Bringing together statistics and computer science education: Machine learning by decision trees grounded in students’ data exploration experiences
  • 24.11.2021
  • 17.30-18.30 Uhr
  • (UTC+1)

Session 02 - Part 1: Tobias Matzner (Germany)

Beyond Bias. Locating questions of injustice in Data Science and Artificial Intelligence
  • 24.11.2021
  • 16.00-17.30 Uhr
  • (UTC+1)

Session 01 - Part 2: Matti Tedre and Henriikka Vartiainen (Finland)

Teaching machine learning in school: Some emerging research trajectories
  • 27.10.2021
  • 17.30-18.30 Uhr
  • (UTC+1)

Session 01 - Part 1: Jan Mokros and Bill Finzer (USA)

Data Detective Clubs in the Time of COVID-19
  • 27.10.2021
  • 16.00-17.00 Uhr
  • (UTC+1)
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