Teachers Preparing Students
for the Data Revolution
Free Online Professional Learning for K–12 Teachers
and Teacher Educators to Support the Teaching
of Data and Statistics
Organized by the Joint Committee of the American Statistical Association and National Council of Teachers of Mathematics
To be held virtually Tuesday, July 29, 2025, 11 a.m. – 3:30 p.m. ET, plus continued learning all year with community-building and virtual learning options.
Stats&DataNet is a year-long professional learning effort sponsored by the ASA and coordinated by Kaycie Maddox, Rebecca Nichols, Hollylynne Lee, and Gemma Mojica, with support from HI-RiSE: A Hub for Innovation and Research in Statistics Education at the North Carolina State University William and Ida Friday Institute for Educational Innovation.
The program provides K–12 teachers and teacher educators with an opportunity to discuss and apply the data analysis, data science, and statistical concepts embodied in the National Council of Teachers of Mathematics Catalyzing Change books and American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE) Pre-K–12 Curriculum Framework.
The program includes examining what students can be expected to do at the most basic level of data analysis understanding and what can be expected of them as their skills develop and experience broadens. Teachers will learn to use strategies and technology tools that support students’ learning and empower them to investigate questions using real-world data.
Registration
The workshop is free, though space is limited, and advance registration is required. Registration deadline: July 28, 2025.
Register
Program
** All times are in the Eastern Time Zone. Certificates issued for hours of participation.
Tuesday, July 29
|
11:00 – 11:30 a.m. |
Welcome and Overview
|
|
11:30 a.m. – 12:30 p.m. |
Session 1: I Have to Teach Statistics and Data Science! How Do I Do That? (Kaycie Maddox) |
|
12:30 – 1:00 p.m. |
Break
|
|
1:00 – 2:00 p.m. |
Session 2: Choose a Session
2.1: Integrating Data Practices into Mathematics and Science Curricula for Grades 3–5 (Jo Louie, grades 3–5)
2.2: Real-World Relationships: Exploring Data with CODAP (Ronda Tate, grades 6–8)
2.3: Statistical Sleuths Wanted: Guess the Mystery Proportion with Confidence (Summer Abney and Dione Maxwell, grades 9–12)
2.4: Bringing Large, Complicated, and Messy Data into the Classroom (Anna Bargagliotti, advanced topics)
2.5: Multiple Linear Regression: An Extension to Simple Linear Regression and a Precursor to Machine Learning and AI (Jamie Perrett, advanced topics) |
|
2:00 – 2:05 p.m. |
Break |
|
2:05 – 3:05 p.m. |
Session 3: Choose a Session
3.1: Elementary Data Science Explorations: Engaging Young Learners in Doing Data Science (Debbie Leslie, Sarah Burns, and Jeanne DiDomenico, grades 3–5)
3.2: Data Visualization (Gemma Mojica and Emily Thrasher, grades 3–12)
3.3: No, Really. Who Is Taller? Introducing Data Science with CODAP (Tim Erickson)
3.4: Teaching Students to Tell Stories with Data (Dash Young-Saver, Ji Son, and Mahmoud Harding, grades 9–12)
3.5: Should You Wear Ear Plugs at a Rock Concert? (Roxy Peck, multivariable graph, randomization test, statistical significance, grades 10–12) |
|
3:05 – 3:10 p.m. |
Break
|
|
3:10 – 3:30 p.m. |
Closing |
School Year 2025–2026
Four sessions (90 minutes each) throughout the school year. Certificates will be issued upon request for hours of participation.
We are excited to continue offering professional learning sessions during the school year. Speakers will be announced soon. Each will be offered on Tuesdays from 6–7:30 p.m. ET
- Session 1: September 23, 2025
- Session 2: November 4, 2025
- Session 3: February 10, 2026
- Session 4: April 14, 2026
Contact
For questions, contact Rebecca Nichols