Resources

Our community has an impressive collection of materials and tools that can be useful in assisting faculty and programs in transforming the teacher preparation courses in which future teachers learn to teach statistics and data science. This collection of resources will continue to grow!

Our resources are organized into categories to help you find materials that best meet your needs. These categories include ESTEEM-Created Materials, Teacher Education Curricular Resources, K-12 Curriculum Resources, Technology Tools, and Open-Access Journals.

We’re always looking to strengthen our community through collaboration! If you have a resource that could benefit others, we’d love for you to share it! Please see the information at the bottom of the page to get involved.

ESTEEM-Created Materials

Enhancing Statistics Teacher Education with
E-Modules

The initial Enhancing Statistics Teacher Education with E-Modules (ESTEEM) project produced more than 40 hours of teacher education curriculum materials for preparing to teach statistics in grades 6-12. Modules (last updated in 2021) include videos, brief readings, data investigations with CODAP, activities, assessments, and discussion prompts:
– Foundations in Statistics Teaching
– Teaching Association
– Teaching Inferential Reasoning

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Preparing to Teach Mathematics with Technology: Teaching Statistical Investigations

In 2017, the ESTEEM team released 4 sets of materials to introduce secondary teachers to core concepts such distribution, comparing groups, measures of center and spread and linear regression with technology. The lessons emphasize statistical investigations using large multivariate datasets and take advantage of linked representations across tables, graphs, and maps in CODAP.

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AMTE Standards Supplemental Materials: Roller Coaster Investigation in a Statistics Classroom

These materials are shared as Supplemental Materials for implementing the AMTE Standards for Preparing Mathematics Teachers.  The selected activities use a roller coaster investigation and 3 classroom-based videos of students and teachers to illustrate key ideas and experiences that set the stage for teacher learners to begin developing strong statistics pedagogy. Materials connect to frameworks used in mathematics teacher education such as professional noticing and practices for productive classroom discussions.

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Teacher Education Curricular Resources

MODULE(S2)

The NSF-funded MODULE(S2) project has published free curriculum materials that develop prospective teachers’ statistical knowledge for teaching secondary mathematics.

Intended for use in university content courses that include statistics, the materials are organized into 3 modules:
– Module 1: Study Design & Exploratory Data Analysis
– Module 2: Statistical Inference
– Module 3: Statistical Association

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Statistics and Data Science for Teachers

This book provides teacher educators with a resource to guide courses and professional development when preparing teachers of all grade levels to teach the foundations of statistics and data science in their classrooms.

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Score Network

This national network creates and shares sports datasets and modules specifically designed for teaching statistics and data science.

Content is organized by sports as well as by statistics and data science concepts.

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Introduction to Statistical Investigations

The text differs from traditional texts in both content and pedagogy.  Statistical inference is introduced using simulation-based methods in Chapter 1. Students are actively engaged in the material through numerous activities in which they flip coins, draw cards, use real data, do simulations with free applets and run experiments. 

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Statistical Investigations of Systemic Racism

Two modules engage learners in using statistical software (CODAP) to analyze large publicly available datasets related to the contexts. modules have been used to engage middle and secondary (6-12) preservice and in-service teachers. They could be adapted for use with middle and secondary students, and with university students in general statistics courses.

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ICUCARE Equity Framework

A framework to use as a lens when making instructional decisions to better meet the needs of marginalized math learners.

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K-12 Curriculum Resources

Introduction to Data Science

The IDS Curriculum teaches students to reason with, and think critically about, data in all forms. The Common Core State Standards (CCSS) for High School Statistics and Probability relevant to data science are taught along with the data demands of good citizenship in the 21st century. Additionally, IDS provides access to rigorous learning that fuses mathematics with computer science through the use of R/RStudio.

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Enhancing Statistical Thinking And Reasoning in Schools (ESTARS)

ESTARS developed modules that integrate the statistical investigation process, data visualization, and simulation into high school statistics.

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Fourth-Year Math Course Frameworks

Explore new fourth-year math course frameworks, designed by the Charles A. Dana Center, to equip students with essential skills in Data Science, Statistics, and Quantitative Reasoning. These frameworks prioritize real-world applications and critical thinking for our data-driven world, preparing students for both higher education and the workforce. Whether you’re an educator or policymaker, our resources offer the tools and insights needed to create a lasting impact.

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Illuminations Project

An NCTM  collection of vetted activities incorporating data into earlier grades with accompanying technology tools. Can search on statistics/data.

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Investigating US Society with Data

Two curriculum modules are designed to promote high school students’ statistical thinking and data literacy skills through investigations of social and economic conditions in the U.S. To conduct these investigations, students analyze large-scale U.S. population data using CODAP. Students learn and apply fundamental data practices as they examine questions of relevance and social importance to themselves, their families, and their communities.

Investigating Income
Investigating Immigration

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Technology Tools

CODAP

CODAP (Common Online Data Analysis Platform) is an easy­-to-­use data analysis environment designed for grades 5 through 14. CODAP can be used across the curriculum to help students summarize, visualize, and interpret data, advancing their skills to use data as evidence to support a claim.

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Open-Access Journals

Statistics Teacher

An online journal and news from ASA & NCTM that promotes the growth and knowledge of teachers of statistics through articles, opportunities, and lesson plans. This is targeted at PreK-12+ teachers.

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Journal of Statistics and Data Science Education

The Journal of Statistics and Data Science Education (JSDSE) is an open-access peer-reviewed journal published by the American Statistical Association. It disseminates accessible knowledge for the improvement of data science and statistics education at all levels, including: elementary, secondary, post-secondary, post-graduate, continuing, and workplace education. Although JSDSE is a journal of the American Statistical Association, submissions are welcome from educators, practitioners, and researchers around the world.

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Harvard Data Science Review

As an open-access platform of the Harvard Data Science Initiative, Harvard Data Science Review (HDSR) features foundational thinking, research milestones, educational innovations, and major applications, with a primary emphasis on reproducibility, replicability, and readability. We aim to publish content that helps define and shape data science as a scientifically rigorous and globally impactful multidisciplinary field based on the principled and purposed production, processing, parsing, and analysis of data. By uniting the strengths of a premier research journal, a cutting-edge educational publication, and a popular magazine, HDSR provides a crossroads at which fundamental data science research and education intersect directly with societally-important applications from industry, governments, NGOs, and others. By disseminating inspiring, informative, and intriguing articles and media materials, HDSR aspires to be a global forum on everything data science and data science for everyone.

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