Archive

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

Previous Sessions

Session 13 - Part 1: Vince Geiger (Australia)

Vince Geiger (Australia)
Part 1: 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)

Devin W. Silvia (USA)
Part 2: 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)

Travis Weiland (USA)
Part 2: Reading and Writing the World with Data - Travis Weiland (USA)
  • 29.11.202317.30 Uhr
  • 02.06.202219.00 Uhr
  • (UTC+1)

Session 12 - Part 1: Henning Wachsmuth (Germany)

Henning Wachsmuth (Germany)
Part 1: NLP Research in the Age of Large Language Models – Henning Wachsmuth
  • 29.11.202316.00 Uhr
  • 02.06.202217.30 Uhr
  • (UTC+1)

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

Martin Frank and Sarah Schönbrodt (Germany)
Part 1: How much mathematical modeling is in AI? - Martin Frank and Sarah Schönbrodt (Germany)
  • 17.05.2023
  • 16.00-17.30 Uhr
  • (UTC+2)

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

Dani Ben-Zvi (Israel)
Part 2: Reasoning with Data in School-Based Citizen Science - Dani Ben-Zvi (Israel)
  • 17.05.2023
  • 17.30-19.00 Uhr
  • (UTC+2)

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

Tor Ole Odden (Norway)
Part 1: Using Computational Essays to Support Student Creativity and Agency in Science - Tor Ole Odden (Norway)
  • 18.01.2023
  • 17.00-19.30 Uhr
  • (UTC+1)

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

Tom Button and Ian Dickerson (UK)
Part 2: Design decisions in creating short data science courses for pre-university students - Tom Button and Ian Dickerson (UK)
  • 18.01.2023
  • 18.30-19.30 Uhr
  • (UTC+1)

Session 09 - Part 2: Francine Berman (USA)

Francine Berman (USA)
Part 2: Teaching Social Responsibility for a Tech-Powered World - Francine Berman (USA)
  • 18.01.2023
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 09 - Part 1: Nick Horton (USA)

Nick Horton (USA)
Part 1: Teaching reproducibility and responsible workflows - Nick Horton (USA)
  • 18.01.2023
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 08 - Part 2: Jane Waite (England)

Jane Waite (England)
Part 2: A hands-on workshop to develop a set of potential goals for learning about AI - Jane Waite (England)
  • 07.12.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 08 - Part 1: Ute Schmid (Germany)

Ute Schmid (Germany)
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)
  • 07.12.2022
  • 17.00-18.30 Uhr
  • (UTC+1)

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

Sven Hüsing, Carsten Schulte and Dan Verständig (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)
  • 02.11.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 07 - Part 1: Conrad Wolfram (England)

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

Session #06

Marc Hauer (Germany) & Michelle Hoda Wilkerson (USA)
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)
  • 02.06.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session #05

Lukas Höper and Carsten Schulte (Germany) & Orit Hazzan and Koby Mike (Israel)
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)
  • 18.05.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session #04

Arnold Pears (Sweden) & Jim Ridgway (England)
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)
  • 01.04.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session #03

Graham Dove (USA) & Rob Gould (USA)
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)
  • 02.01.2022
  • 16.00-18.30 Uhr
  • (UTC+1)

Session #02

Tobias Matzner (Germany) & Rolf Biehler and Yannik Fleischer (Germany)
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)
  • 24.11.2021
  • 16.00-18.30 Uhr
  • (UTC+1)

Jan Mokros and Bill Finzer (USA)

Data Detective Clubs in the Time of COVID-19
Data Detective Clubs in the Time of COVID-19 - Jan Mokros and Bill Finzer (USA)
  • 27.10.2021
  • 16.00-18.30 Uhr
  • (UTC+1)

Session #01

Jan Mokros and Bill Finzer (USA) & Matti Tedre and Henriikka Vartiainen (Finland)
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)
  • 27.10.2021
  • 16.00-18.30 Uhr
  • (UTC+1)
Nach oben scrollen