Data can be numbers, counts, and measurements but also images, video, sounds, or words. Students need to grapple with the fast-changing nature of data, yet a gap exists between the concepts taught in math and the data skills needed by other disciplines. All learners need opportunities to develop data literacy, knowledge, and skills.
Different disciplines may have different concepts of data and have different analysis techniques that have been developed for their specific needs. However, the approach to working through a problem and answering questions with data are consistent themes in practices used across all disciplines (Reynante et al., 2020; National Academies of Sciences, Engineering, and Medicine, 2023). Data science tools and practices can help students learn with and through data to make meaning of phenomena and issues across disciplines. A data-enabled approach affords students an opportunity to bring their personal interests, histories, cultural identities, and self into classrooms where learning is connected to their real world (e.g., Louie et al., 2021; V. Lee, Wilkerson, & Lanouette, 2021).
Accordingly, NCTM has collaborated with NSTA, ASA, NCSS, and CSTA to release a joint position statement on Data Science.
Data science bridges disciplines and thus should be introduced and taught across the curriculum in K-12 schools to help develop informed users of data. Data science captures the complexity of data and data methods that have arisen with advances in technology, including breakthroughs in artificial intelligence. It is a collaborative science that uses complex data and methods to explain trends and patterns with a critical piece being its interdisciplinary nature. K-12 education plays the critical role of scaffolding students' experiences in addressing complex data sets. All subjects in school should recognize the contribution of data to their discipline and take curricular approaches that integrate data with disciplinary lessons where appropriate.
- Data science is contextual and interdisciplinary.
- Data science is an investigative process.
- Data science understandings and experiences are for everyone.
- Data science educators must develop and practice ethical uses of data.
Read the full position statement.
About NCTM Position Statements
NCTM position statements define a particular problem, issue, or need and describe its relevance to mathematics education. These statements address important and timely policy issues relevant to mathematics education. They rest on the foundation provided by Principles and Standards for School Mathematics, Principles to Actions and research, and address issues that extend beyond the classroom. Each one defines the Council's position or answers a question central to the issue. Position statements are approved by the NCTM Board of Directors.