What Is Data-Rich Instruction?
Data-rich instruction helps students develop data fluency, or the ability to understand, interpret, and use data effectively. Data fluency strengthens students’ STEM skills, encourages them to participate in STEM career paths, and empowers them to think critically and solve problems in everyday life.
With data-rich instruction, teachers help students build their data fluency by exploring, collecting, questioning, interpreting, and sharing data to investigate topics and solve real-world problems.
Data Fluency Offerings
Boost your students’ data fluency. Our professional learning and classroom resources help science and math educators bring data-rich instruction into their classrooms.
These experiences invite teachers to engage in hands-on data investigations, explore classroom examples and student work, and plan data-rich instruction.
Professional Learning
In-person or virtual | 2–3 full days with PLCs
For math and science teachers grades 6–9
Technical Assistance
Need help designing lessons, curating datasets, or using data tools? Ask our experts!
District-Level Planning
Need a comprehensive plan for data in K–12? We provide leadership support for strategic planning.
The data fluency course zaps the gap between engagement and learning for students who are tech natives.
—Arlene Nicolas, middle school teacher. Read the case story
Resources
Principles of Data-Rich Instruction
Support data-rich learning for middle and high school students and provides examples of how they may be incorporated in classrooms.
Data Biographies (Data and Guidance)
Introduces educators to curated datasets and data visualizations that can be used in math and science classrooms.
Data Sentence Starter Classroom Posters
Helps guide student discussions on questioning, exploring, analyzing, interpreting, and communicating data while engaging peers about findings.
Entryways to Data (Diagram)
Provides pathways to integrate data in learning: exploring, gathering, questioning, designing solutions, interpreting, and communicating data.
About the Project
The Boosting Data Fluency course combines WestEd’s proven Making Sense of SCIENCE professional learning approach with The Concord Consortium’s user-friendly data analysis tool, CODAP, and is now available for districts. This professional learning was developed as part of the Boosting Data Science Teaching and Learning in STEM project (2021–2026), which aims to improve data skills for teachers and students in grades 6–9.
This work is supported by the National Science Foundation under Grant No. 2101049. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Our Team >
Kirsten Daehler, Principal Investigator
Nicole Wong, Co-PI, Research Lead
Leticia Perez, Co-PI, Development Lead
Pai-Rou Chen, Researcher and Project Manager
Rasha Elsayed, Researcher
Sara Salisbury, Researcher and Developer
Corynn Del Core, Graphic Designer
Karen Lionberger, Associate Director of Making Sense of SCIENCE
Our Partners at Concord Consortium
Bill Finzer, Co-PI
Frieda Reichsman, Co-PI
Annie Flores, Administrative Assistant
Publications and Resources >
Journals and Conference Papers
Arnold, P., Perez. L., & Johnson, S. (2024). Why does wonder work? [Paper presentation]. Meeting Within a Meeting: American Statistical Association. Virtual.
Elsayed, R., Wong, N., Perez, L. R., Daehler, K. R., Chen, P., & Del Core, C. A. (2024, March 17–21). Assessing pedagogical content knowledge for data fluency for middle school STEM teachers [Paper presentation]. Ninety-Seventh Annual International Conference of the National Association for Research in Science Teaching, Denver, CO, United States.
Perez, L. R. (2024). Understanding my location by exploring data in CODAP [Paper presentation]. Auckland Mathematics Association.
Perez, L., & Lionberger, K. (2023). Opening the door to data science in STEM classrooms. NextGenScience. https://ngs.wested.org/doortodatascience/
Perez, L. R., Salisbury, S., & Daehler, K. R. (2024, March 20–23). Using photographs and data stories to support data science in STEM [Workshop]. National Science Teaching Association Annual Conference, Denver, CO, United States.
Wong N., Elsayed, R., Perez, L. R., Daehler, K. R., & Chen, P. (2024, March 17–21). Toward a theoretical framework for data fluency teaching and learning in middle school STEM [Paper presentation]. Ninety-Seventh Annual International Conference of the National Association for Research in Science Teaching, Denver, CO, United States.
Papers and Presentations in Progress
Chen, P., Wong, N., Elsayed, R., Perez, L., & Daehler, K. R. (2025, March 23–25). Building teachers’ capacity for data-rich instruction: Impact from a professional learning course [Paper presentation]. Ninety-Eighth Annual International Conference of the National Association for Research in Science Teaching, National Harbor, MD, United States.
Perez, L. R., Wong, N., Salisbury, S., Daehler, K., & Reichsman, F. (2025). Creating usable datasets for K–12 STEM education: A path to classroom data fluency.
Perez, L. R., Wong, N., Salisbury, S., Rizzi, A., Hunter Thomson, K., & Chin, C. (2025). Bring or build your own dataset [Workshop]. Data Science Education K–12: Research to Practice Conference. San Antonio, TX, United States.
Wong, N., Elsayed, R., Perez, L. R., Del Core, C. A., & Daehler, K. R. (2025, March 23–25). The data fluency framework for teaching: A conceptual model of teacher knowledge for data-rich instruction [Paper presentation]. Ninety-Eighth Annual International Conference of the National Association for Research in Science Teaching, National Harbor, MD, United States.
Wong, N., Perez., L. R., & Daehler, K. R. (2025). Data doulas: Supporting educators to facilitate data-rich instruction in STEM classrooms. Harvard Data Science Review.
Techniques, Technologies, and Websites >
CODAP Color Class
This technology augments the capacity native within CODAP V3 (beta release, Spring 2025) to treat color types as a class of data. This capacity improves the tool’s ability to create subgroups of data, increases control in data representation and analysis, and increases the types of data science lessons that can be created with the tool (e.g., photo/pixel analysis, connections to art, computer vision).
This plugin includes a simulation to help students examine the relationship between day length, seasonality, and solar intensity.
NASA Earth, Air, Water CODAP Plugin
This plugin retrieves dynamic data from the NASA POWER API for 19 attributes anywhere in the world. This tool is helpful for students engaged in Citizen Science programs and classroom primary data collection events.
Updated NOAA Weather Data Plugin
The NOAA weather data plugin allows students to access historical NOAA weather station data.
Data Biographies are a digital resource designed to introduce educators to a curated dataset or data visualizations within a webpage.
Contact Us
Are you interested in implementing data-rich instruction in your school or district? Do you need technical assistance, or do you want to learn more about our research? We’d love to connect with you. Please share your interests, and let’s start a conversation.
Contact Us to Get StartedI definitely was able to do a better job explaining some habits of mind and data analysis tools. My students were more prepared and more successful in engaging with data lessons this year.
—Middle school teacher