IASE - Statistics and data science education as a vehicle for empowering citizens
| Date | 20 May 2025 |
| Time | 12:00 GMT+02:00 - 12:00 GMT+02:00 |
| Level of instruction | Intermediate |
| Instructor |
Rolf Biehler
Takashi Kawakami
Travis Weiland
Lucía Zapata-Cardona
Erna Lampen
|
| Registration fee | |
The International Association for Statistical Education (IASE https://iase-web.org/) presents the May webinar. Rolf Biehler, Takashi Kawakami, Erna Lampen, Travis Weiland, Lucia Zapata-Cardona are presenting, and we welcome you all to join us. We also ask you to share this invitation with high school statistics teachers and other statistics education networks in your country. We welcome IASE and non-IASE members to the session.
DATE 20 May 2025; 12:00 UTC (Check here for localised date/time)
Webinar duration: 90 minutes
Introduction
The growing influence of data in society demands a shift in education to equip citizens with statistical and data literacies. Data science is interdisciplinary and dynamic, impacting daily life through AI, social media, and ethical concerns. This survey examines how education can empower citizens while balancing economic and societal needs. This presentation is based on the Survey Team Report of the authors at ICME 15, Sydney, July 2024
Citizen Education and Data Literacy
The survey identifies various frameworks for citizen education, aligning with global initiatives like the UN’s Sustainable Development Goals. It highlights multiple literacies, such as civic statistical literacy and computational literacy, while addressing the challenges of integrating them into already packed curricula. Due to the diverse range of topics related to citizen education and data literacy we break the presentation into multiple sections to highlight key topics including:
- Civic statistics in the U.S. and Europe focus on data interpretation, investigation, and use of technology.
- Critical perspectives in Latin America, drawing from Freirean pedagogy to address socio-economic inequalities.
- Mathematical modeling and data science integration support STEM literacies and critical thinking.
- AI and machine learning literacies emphasize understanding key concepts and ethical concerns such as bias and fairness.
Conclusion
Statistics education is evolving into data science education, requiring curriculum updates and interdisciplinary research to prepare citizens for a data-driven world. Furthermore the term data literacy is used so widely in so many fields it holds little meaning without explicit definition of how it is being used.
Instructors
About the instructor
Rolf Biehler is a professor emeritus for didactics of mathematics at Paderborn University, Germany. His research encompasses probability, statistics, and data science education, with a focus on integrating digital tools into learning processes. He co-directs the “Data Science and Big Data at School” project (www.prodabi.de/en), developing curricula and professional development courses for teachers to introduce data exploration and data-based machine learning at various educational levels.
About the instructor
Takashi Kawakami is an Associate Professor of Mathematics Education at the Cooperative Faculty of Education, Utsunomiya University, Japan. His research interests include mathematical modelling, statistics and data science education, STE(A)M education, and mathematics teachers’ professional learning. His current primary focus is exploring the intersection of mathematical modelling and statistics/data science education using conceptual and empirical approaches.
About the instructor
Travis Weiland is the Assistant Professor at the University of North Carolina Charlotte. My interests are at the intersection of teacher education, statistics education, data science education, and critical education. Currently much of my work is focused on studying how mathematics teachers develop critical statistical literacies for doing and teaching data investigation concepts and practices.
About the instructor
Lucía Zapata-Cardona is a full professor at the Universidad de Antioquia, Colombia. Her interests are in teacher education, statistics education and critical data science. She is currently working on the development of data science teaching materials that help citizens understand and transform critical social issues.
About the instructor
Erna Lampen is a retired senior lecturer from Stellenbosch University, South Africa. Her research interests include mathematical and statistical reasoning and implications of technological advancement on such reasoning. She focuses on teacher education and materials development to integrate STEAM subjects.