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Introduction
For millennia, humans have used mathematics in all aspects of their lives, from simple counting in order to conduct commerce to complex scientific discoveries that expand beyond human limitations of observation and calculation. Mathematics education is essential in a data-driven world and young people need it to succeed in life. While basic principles are timeless, mathematics education is continually changing because of new technology, educational research, and societal expectations. Advances in data science, computational thinking, and artificial intelligence (AI) have accelerated the need to reimagine what math concepts students need to learn nowadays and how to learn them. Preparing global citizens for industries and economies of the mid- to late 21st century involves much deeper and broader applications of mathematics. Thus, the instructional approaches and professional practices of K-12 mathematics educators should shift to foreground computational thinking and learning about AI and data science. Understanding these global patterns across curriculum design, teacher development, policy sequence, and implementation structures provides valuable insights for educators, school superintendents, and policy makers as they navigate decisions in a rapidly evolving educational landscape.
The importance of computational thinking in K-12 has been expanding since the 1980s, when computers and other technological tools began to be more mainstream in classrooms. And with the rapid advances of AI and ways data are produced, consumed, and utilized across industries, the need for students’ learning about and through data science and AI techniques within the context of K-12 mathematics education has rapidly caught up with the importance of computational thinking. Students’ learning of
mathematics should not merely involve numeric, algebraic, and geometric structures and applications. 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. The workshop was designed to include a broad range of international practices, including different norms and expectations of what is good education. The United States can learn from many countries that have advanced K-12 mathematics 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. Ultimately, curriculum, regardless of geography, must prepare all students with the mathematical and computational competencies needed to thrive as informed citizens and problem solvers in the 21st century.
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. Coming from 17 countries in addition to the United States, more than 50 math educators and leaders in the field with classroom, curriculum planning, teacher training, policy, and other experience gathered in person (by invitation only), while several hundred other individuals attended online (open to anyone virtually). U.S. experts moderated panels, participated in the conversations, and posed questions to the international experts, while none of the speakers were from the United States. In-person participants engaged in questions, reflections, and conversations with the speakers while virtual attendees observed.
The members of the planning committee identified four central themes of the workshop: (1) curriculum development and policy implementation, (2) assessment techniques and student learning, (3) technological tools and frameworks, and (4) instructional approaches and professional practice. In order to focus on the discussions, they proposed key questions for each theme for the speakers to address. The planning committee also identified the leading countries and the best experts to address the thematic questions. Background on issues related to each theme is provided at the beginning of each chapter.
OPENING REMARKS
Reviewing the Workshop Goals and Expected Outcomes
Ana Ferreras Fiel (National Academies) welcomed participants and outlined conditions that point to the necessity for the workshop. Fewer than 3 percent of U.S. children receive data science education. Particularly since the COVID-19 pandemic, there has been a major deficit of U.S. schoolteachers, with an insufficient number of new teachers replacing those who leave the profession. No global analysis of the current state of mathematics education related to data science, computational thinking, and artificial intelligence exists, making it hard to know how to improve. At the same time, she said, the extent to which students know or do not know these rapidly growing areas has important socioeconomic implications.
She highlighted the long-standing role of the National Academies in strengthening mathematics education in the United States. Recent efforts include the workshop Foundations of Data Science for Students in Grades K-12 and the consensus study Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors, although both were completed before recent breakthroughs in generative AI.1 A consensus study, Developing Competencies for the Future of Data and Computing: The Role of K-12, was released shortly after the workshop, and a new study, Modernizing Mathematics Education for Grades 9 to 14, was about to begin.2
The planning committee for the current workshop was specifically tasked with looking at international experiences that can inform U.S. mathematics efforts:
The National Academies of Sciences, Engineering, and Medicine will organize an international workshop to discuss how top-performing countries in primary and secondary mathematics education are modernizing their math curricula. Workshop participants will discuss processes, mechanisms, and best practices for revising K-12 mathematics curricula and identifying the necessary competencies to remain globally competitive. Invited international experts will discuss how the modernized curriculum is aligned with the technology in the classroom (learning environment), textbooks and
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1 NASEM (National Academies of Sciences, Engineering, and Medicine). 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press; NASEM. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press.
2 NASEM. 2026. Developing Competencies for the Future of Data and Computing: The Role of K-12. Washington, DC: The National Academies Press. To track the new study, see https://www.nationalacademies.org/projects/DEPS-MSEB-25-01
educational materials, and instructional techniques (teaching and learning). A rapporteur-authored proceedings will be published summarizing the workshop and an interactive page will be developed to disseminate the proceedings more broadly.
The committee, which comprised U.S. and international experts, organized presentations and discussions around four themes: (1) curriculum development and policy implementation, (2) assessment techniques and student learning, (3) technology tools and frameworks, and (4) instructional approaches and professional practice. Most of the agenda focused on high school math education, although K-8 math education was also explored. The speakers were informed that the workshop emphasized secondary mathematics education, and they were offered the choice to feature primary, secondary, or both. Session speakers had latitude to frame the sessions as they deemed appropriate from their own points of view.
The workshop agenda can be found in Appendix A. Appendix B presents the list of speakers, moderators, and in-person attendees that participated in the workshop.
The workshop is one part of an overall project sponsored by Data Science 4 Everyone (DS4E), Gates Foundation, and University of Chicago. Ferreras Fiel said that, besides the workshop, a webinar series is planned for spring and fall 2026 and a distribution list is also available to stay informed. Expected outcomes include advancing the body of knowledge about mathematics education in regard to data science, computational thinking, and AI; increasing global understanding of best practices; building new collaborations and partnerships, including possibly a national plan and/or consortium of stakeholders; and revising old policies and/or developing new. She concluded by highlighting that the project website serves as a repository and all the workshop and webinar recordings and other material are freely open and available.3
View from a Sponsor: Value of a Global Convening
Zarek Drozda (DS4E) explained that DS4E sponsored the workshop because of the rare opportunity of, and value in, convening in person to consider how data science, computational thinking, and AI fit within curricula in countries across the world.
DS4E is based at the University of Chicago and pursues four pillars: raising awareness, community building, providing resources and support to help school leaders and educators, and policy advocacy. When it began in
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3 The workshop recordings are available at https://www.nationalacademies.org/projects/PGA-NETWORKS-25-02/event/46363
2019, only one state (Ohio) had a pilot program for data science. By 2024, the number had expanded to 29 states, and by 2025, to 35 states. The involvement ranges from adding data science to course catalogs (Tier 1), to state-supported course pilots, course sequences, and/or teacher professional development (Tier 2), to adoption of state standards or frameworks (Tier 3). Recognizing the growth, Drozda also stressed that only a small number of students benefit (2 to 3 percent of high school students), and a landscape scan reveals that the United States is in very early stages when compared with other countries.
Where data science, computational thinking, and AI fit in the curriculum is still a puzzle, Drozda commented. It may be within mathematics, but these topics are relevant to many school subjects, and he expressed interest in learning what other countries are doing.
Reimagining Mathematics Education
Padhu Seshaiyer (George Mason University), workshop planning committee chair, added his welcome and stressed the importance of reimagining mathematics education in the context of data science, computational thinking, and artificial intelligence. “At this stage, we are not asking whether we should teach students to use AI, but how they can become critical thinkers and creative problem solvers with AI,” he commented. According to Future of Jobs 2025 published by the World Economic Forum,4 he noted, the fastest-growing jobs in 2030 will be big data specialists, fintech (data and finance) engineers, and AI and machine learning specialists. Core skills for the future, as identified in the report, include analytical thinking; resilience, flexibility, and agility; creative thinking; technological literacy; and AI and big data.
Seshaiyer elaborated that 21st-century skills identified by the World Economic Forum5 consist of foundational literacies (how students apply core skills to everyday tasks), such as literacy and numeracy; competencies (how students approach complex challenges), such as creative thinking and communication; and character qualities (how students approach their changing environment), such as curiosity and initiative.
Seshaiyer next launched a series of “lightning talks.” In-person participants introduced themselves and, on a one-panel slide, highlighted what
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4 World Economic Forum. 2025. Future of Jobs 2025. Geneva: World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2025/
5 World Economic Forum. 2016. New Vision for Education: Fostering Social and Emotional Learning through Technology. Geneva. http://www3.weforum.org/docs/WEF_New_Vision_for_Education.pdf
they want to learn from the workshop and what resources they can share with others.6
ORGANIZATION OF THIS PROCEEDINGS
The remainder of this publication generally follows the agenda of the workshop (Appendix A). Chapter 2 begins with challenging perspectives from keynote speaker Conrad Wolfram on fixing human education for the AI age. Chapters 3 and 4 summarize the first day’s panels on the themes of curriculum development and policy implementation, and on assessment techniques and student learning. The first day also featured a “mini-session” that spanned the workshop themes; highlights appear in Chapter 5. The following day of the workshop began with a second keynote by Junaid Mubeen on mathematics education in the age of AI, captured in Chapter 6. Chapters 7 and 8 return to the last two of the workshop themes, with panels on technology tools and frameworks, and on instructional approaches and professional practice. The final chapter captures closing reflections from the end of each day of the workshop.
In accordance with the policies of the National Academies, workshop participants did not attempt to establish any conclusions or recommendations about needs and future directions. In addition, the planning committee’s role was limited to planning the workshop. This proceedings of a workshop was prepared by rapporteurs as a factual summary of what occurred at the workshop.
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6 The “lightning talk” slides are available on the workshop webpage: https://www.nationalacademies.org/projects/PGA-NETWORKS-25-02/event/46363
