CATALYZING Teacher Professional Development: Agricultural Data Science

Program Overview

On Friday July 31, 2026, faculty from two Texas universities engaged 12 West Texas middle grade mathematics teachers in a full-day PD event that integrated agricultural literacy, STEM concepts, with training in data-driven advocacy for an applied experience focused on agricultural data science.

Agriculture is one of the most data-intensive domains in contemporary life, and one of the most underutilized contexts for rigorous middle school mathematics instruction. By anchoring mathematical investigation in real agricultural datasets drawn from Texas-based and national sources, the materials from this PD provide teachers with a practical, curriculum-aligned pathway for connecting their agriscience content to middle school TEKS in mathematics, the National Agricultural Literacy Outcomes (NALOs), and the K-12 Data Science Education (DSE-K12) learning progressions.

Resources:

Access teacher’s lesson plans developed by the participants for middle grades mathematics that utilize data science techniques.

Want to make your OWN Lessons using agriculture data? Access a Step-by-Step guide for Agricultural Data Science in the Classroom, a Graphic Organizer of Data Science Learning and Guide to the free and browser-based Common Online Data Analysis Platform (CODAP), and curated Data Sets for you to use in your classroom.

Key Accomplishments:

1. Full-day PD for 12 middle school math teachers.
2. Conducting research on teacher professional development.
3. Creation of Place-Based Lesson Plans, by teachers for teachers in West Texas.

Funding:

This professional development session was graciously supported by the Helen Jones Foundation. Learn more about Mrs. Jones and her foundation here.

Collaborators:

Research:

• SMU IRB # 26-81: Cultivating Data Science Through Agricultural Inquiry: Designing Professional Development for Middle School Mathematics Teachers 
  
  • Sager, M. T., Darwin, T., & Hite, R. (Submitted). Developing middle school math teachers’ data science competency through agricultural inquiry. In N. Wong & L. Perez (Chairs), How teacher professional development can build capacity for data science education [Structured poster session]. For the 2027 American Educational Research Association (AERA) Conference in Toronto, Ontario, Canada.
  • Sager, M.T. & Darwin, T. (Submitted). Agricultural data science professional development for middle school mathematics: A design narrative.
• TTU IRB2025-865: Studying the Impacts of Professional Development on Teachers’ Conceptualizations, Design, and Enactment of Place Based Education (Ongoing)

Faculty Contacts: