Topic 2

Statistics education at the school level

Convenors

• Andee Rubin (United States)
• Dani Ben-Zvi (Israel)
• Yilton Riascos Forero (Colombia)
• Daniel Frischemeier (Germany)
• Hugo Hernández (México)

Abstract

In today’s data-driven society, vibrant democracies need well-informed citizens who can reason about data and probability critically when discussing relevant social issues and engaging in public decision-making processes. To achieve this, there must be a coordinated program of education in statistical and probabilistic reasoning that begins when students are young and continues throughout their school years. Papers in Topic 2 will explore the latest developments and approaches to teaching and learning of statistics, probability and data science for students from pre-school through secondary school, approximately ages 3 through 17. In addition to studies of experiences in school contexts, this topic is interested in out-of-school learning opportunities for youth in this age range. Papers may report on students’ engagement with data in a variety of contexts, including math/statistics/data science courses, but also in subject matter courses (e.g. science or social science) that integrate data.

Papers in Topic 2 may address any of the following (or related) topics:

• theories of how statistical and probabilistic reasoning develop;
• pedagogical techniques to support the development of such reasoning;
• design of learning environments for statistical and probabilistic reasoning;
• the design and use of digital tools to enhance data exploration and statistical modelling, including simulations;
• assessment techniques;
• policy issues regarding early statistical and probabilistic learning;
• issues of equity and diversity as they relate to the learning of statistics and probability;
• considerations of how the growth of data science and the increasing availability of large data sets will impact education in statistics and probability at the school level.

Papers can identify current best practices, place them within the overall context of current trends in statistics and data science education research and practice, and consider the implications for both theory and pedagogy.