Full Description
The integration of data science, computational thinking, and artificial intelligence into K-12 math education has become a global imperative. Yet, curriculum design approaches vary widely across international contexts, making cross-cultural study essential for educators and policy makers. As nations from Singapore to Finland and from Estonia to South Korea craft frameworks for an increasingly data-driven world, understanding how different systems structure learning progressions, sequence concepts within math standards, and design assessments is critical to building effective curricula. Learning from global innovations, implementation challenges, and research enables educators to move beyond siloed standards and design experiences that not only teach students to apply these technologies within mathematical contexts but also foster critical thinking.
On February 23 and 24, 2026, the National Academies of Sciences, Engineering, and Medicine convened a workshop to learn how leading countries in mathematics education are modernizing their curricula to incorporate data science, computational thinking, and AI. Math educators and leaders in the field with classroom, curriculum planning, and teacher training, and policy explored a broad range of international practices, including different norms and expectations of what is good education.
Contents
Front Matter
1 Introduction
2 Keynote 1: Fixing Human Education for the AI Age
3 Curriculum Development and Policy Implementation
4 Assessment Techniques and Student Learning
5 Mini-Session: Across the Four Themes
6 Keynote 2: Mathematics Education in the Age of AI
7 Technology Tools and Frameworks
8 Instructional Approaches and Professional Practice
9 Reflections and Concluding Remarks
Appendix A: Workshop Program
Appendix B: List of Speakers and In-Person Attendees
