Network Updates

Newsletters, Articles and Announcements

The power of our ESTEEM Network is in our collaborative approach as a community. We have a common aim to improve undergraduate preparation programs for teachers of data science and statistics.

ESTEEM Year 2 Report

As we begin the third year of this project, we wanted to share a brief report about progress made in Year 2, including highlights of research results, actions made by our Networked Improvement Community, and links to slides and proceedings from recent presentations. Please feel free to share with others.

Early Career Mathematics Teacher Research Summaries

The ESTEEM team explored the attitudes, confidence, instructional practices, pedagogical content knowledge, and statistical knowledge of early-career mathematics teachers in teaching data science and statistics (DS&S). We share five summaries to inform the work of teacher educators who prepare secondary teachers to teach data and statistics.

Data Moves as a Focusing Lens for Learning to Teaching with CODAP

The ESTEEM team has a new open-access publication:

Hudson, R. A., Mojica, G. F., Lee, H. S., & Casey, S. (2024). Data Moves as a Focusing Lens for Learning to Teach with CODAP. Computers in the Schools, 1-26.
https://doi.org/10.1080/07380569.2024.2411705

The Teaching of Introductory Statistics: Results of a National Survey

Learn about the landscape of college statistics education with this study, which examines teaching practices of college-level introductory statistics instructors (n=228) across the U.S. Curricular and instructional practices were assessed to evaluate how well courses align with recommendations from the 2016 GAISE College Report. Findings suggest many are following core content guidelines, but there is room for improvement in areas like multivariate data analysis and student-centered teaching methods. LINK

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Chart the Course: We need your help to shape the future of K-12 Data Science Education! Vote August 29-October 15. datascience4everyone.org/vote

#Chart the Course: Vote by October 15

The #ChartTheCourse campaign has launched, and Data Science 4 Everyone invites you to help shape the future of K-12 data science education. Vote now to ensure the framework reflects the data skills students need in a data-driven world. Learn more, cast your vote, and hear from leaders at NCTM, NSTA, CSTA, and ADSA about why they support #ChartTheCourse.

Vote Now

Consider the 5 Practices
Through a Statistical Lens

A new article about how the 5 Practices framework can be adapted for teaching statistics in a way that accounts for differences between mathematics and statistics was recently published in NCTM’s MTLT journal. It includes videos from the ESTEEM curriculum materials to illustrate the adaptations.

NCTM’s Position Statement on High School Data Science Courses is Out!

Read the National Council of Teachers of Mathematics’ latest recommendations and insights on integrating data science into high school curricula.

Beyond Borders 2024: Primary and Secondary Data Science Education Around the World

Sean Sukol, Data and Policy Analyst,
Data Science 4 Everyone
March 2024

The US has only just begun to lay the foundation for data science education with surveys of the current education landscape and investigations into the implication of AI for our society. But our peers and competitors have already made data science, machine learning, and AI required components of their K-12 curricula. This report focuses on data science education and education advocacy in Canada, the UK, Germany, China, India, and New Zealand.

The ESTEEM Network Newsletter intends to share resources, upcoming opportunities, and key efforts in the field. We aim to connect educators, researchers, and practitioners, fostering a community dedicated to continuously improving statistics and data science education.