{"id":48,"date":"2024-05-23T00:32:41","date_gmt":"2024-05-23T00:32:41","guid":{"rendered":"https:\/\/research.ced.ncsu.edu\/esteemhub\/?page_id=48"},"modified":"2026-02-18T18:20:08","modified_gmt":"2026-02-18T18:20:08","slug":"esteem-news","status":"publish","type":"page","link":"https:\/\/research.ced.ncsu.edu\/esteemhub\/esteem-news\/","title":{"rendered":"Network Updates"},"content":{"rendered":"\n\n\n\n\n
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.  <\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n
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Mathematics Teacher Educators and Experts Gather for National Summit on Transforming Mathematics Teacher Preparation in Data Science and Statistics<\/h3>\n \n\n \t \t

The 2025 ESTEEM Summit on Transforming Mathematics Teacher Preparation for a Data Science and Statistics Future hosted participants and experts from around the country, including higher education faculty, the National Council of Teachers of Mathematics (NCTM), the University of Texas at Austin Charles A. Dana Center, Data Science 4 Everyone, and the Association of Mathematics Teacher Educators (AMTE).<\/p>\n\t \t \n

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K-12 Data Science Learning Progressions<\/strong><\/h3>\n \n\n \t \t

Data Science 4 Everyone is planning to release their K-12 learning progressions for data science in Fall 2025! Sign up here so you will be among the first to get them!<\/p>\n\t \t \n

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Two New Revised ESTEEM Curriculum Module Sets<\/strong><\/h3>\n \n\n \t \t

The ESTEEM II team is excited to announce that newly revised ESTEEM curriculum module sets are up in Canvas Commons! The newly revised\u00a0Foundations in Data Science and Statistics Teaching<\/em><\/strong>\u00a0supports prospective teachers in building expertise about\u00a0how students learn data and statistics<\/strong>\u00a0and\u00a0how to teach it effectively\u00a0<\/strong>and has undergone modifications during summer 2025. The\u00a0Teaching Statistical<\/em><\/strong>\u00a0Association\u00a0<\/em><\/strong>module set focuses on\u00a0the importance of statistical association\u00a0and how students learn association with categorical and quantitative variables<\/strong>. Both sets include two modules with:\u00a0brief readings and multi-media engagements, data investigations using CODAP, classroom videos and student work, and opportunities to discuss, reflect and apply.\u00a0

Materials are packaged into LMS courses to provide maximum flexibility for instructors to tailor materials for their own contexts. You can view the module at Canvas Commons and download and import materials into other LMSs.

Teaching Inferential Reasoning<\/em><\/strong> Modules are under revision and will be released later in 2025.<\/p>\n\t \t \n

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AMTE Statistics and Data Science Teacher Education Circle Meetings<\/strong><\/h3>\n \n\n \t \t

Travis Weiland organizes this group, and it is open to anyone. We meet about once a month for great conversations and often have guest speakers.\u00a0If you are interested in joining the list for the Circle announcements, add your name and email to the linked spreadsheet.<\/p>\n\t \t \n

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Integrating Data Literacy Into K\u201312 Education<\/strong><\/h3>\n \n\n \t \t

Chad Dorsey and colleagues published an article in Harvard Data Science Review that highlights the urgent need to integrate data literacy into U.S. K\u201312 education and outlines key challenges. They propose strategies such as teacher preparation, curriculum integration, tailored tools, and leadership support. The authors call for a coordinated, long-term effort from multiple stakeholders to make data literacy a fundamental skill for all students.<\/p>\n\t \t \n

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Episode 108: Farshid Safi: Collectively Moving Toward a Comprehensive, Inclusive Approach to Mathematics Teacher Education<\/strong><\/h3>\n \n\n \t \t

In this episode of Teaching Math Teaching, learn about teaching math teachers better with Dr. Farshid Safi, President of the Association of Mathematics Teacher Educators. They discuss the upcoming 2026 conference and how AMTE is continuing to live out its mission and position statements.<\/p>\n\t \t \n

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New Sampler Tool in CODAP<\/strong><\/h3>\n \n\n \t \t

Through our partnership with Bill Finzer and the amazing CODAP development team at the Concord Consortium<\/em> we have redesigned and enhanced the functionality of the Sampler plugin within CODAP. This work was inspired by functionality of the\u00a0TinkerPlots<\/em> sampler. We improved the interface for how to design mixers and spinners, and you can now build models with multiple devices for exploring more complex situations and compound probability activities. In the sampler, you will find ways to collect common measures, sample with and without replacement, hide a model, and conduct an experiment where you repeat until a specific condition occurs. For example, in the image, the sampler is designed to model a family of 3 births, repeating making families of 3 children until 3 boys are born for a family.

Find the Sampler by looking in the Plugins menu Simulate Sample<\/p>\n\t \t \n

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ESTEEM Year 2 Report<\/strong><\/h3>\n \n\n \t \t

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.<\/p>\n\t \t \n

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First Ever Data Science Education K-12 Research to Practice Conference<\/strong><\/h3>\n \n\n \t \t

What happens when you bring together educators, researchers, and advocates passionate about data science education? Read about the first-ever Data Science Education K-12 Research to Practice Conference held from February 17-19, 2025, in San Antonio, Texas. It was a vibrant and inspiring gathering of over 265 attendees from (literally) all around the world.<\/p>\n\t \t \n

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Exploring Data in Social Studies Using Two New CODAP Plugins<\/strong><\/h3>\n \n\n \t \t

Read a blog post by Kate Miller about two new data portal plugins to support data science in social studies contexts. The plugins allow students to explore data from the World Health Organization (such as teenage obesity in different countries) and the National Agricultural Statistics Service (such as food production, farm demographics, and wages).<\/p>\n\t \t \n

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Revitalizing K-12 Mathematics Education<\/strong><\/h3>\n \n\n \t \t

In this news article, Mahmoud Harding from DS4E describes some of the national-level efforts to change the landscape of mathematics education by infusing real-world applications through data science.<\/p>\n\t \t \n

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Early Career Mathematics Teacher Research Summaries<\/strong><\/h3>\n \n\n \t \t

The ESTEEM team explored the\u00a0attitudes,\u00a0confidence,\u00a0instructional practices,\u00a0pedagogical content knowledge, and\u00a0statistical knowledge\u00a0of 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.<\/p>\n\t \t \n

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Data Moves as a Focusing Lens for Learning to Teaching with CODAP<\/strong><\/h3>\n \n\n \t \t

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.\u00a0Computers in the Schools<\/em>, 1-26.\u00a0
https:\/\/doi.org\/10.1080\/07380569.2024.2411705<\/p>\n\t \t \n

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The Teaching of Introductory Statistics: Results of a National Survey<\/h3>\n \n\n \t \t

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<\/p>\n\t \t \n

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#Chart the Course: Vote by October 15<\/h3>\n \n\n \t \t

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.<\/p>\n\t \t \n

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Consider the 5 Practices
Through a Statistical Lens<\/h3>\n \n\n \t \t

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\u2019s MTLT journal. It includes videos from the ESTEEM curriculum materials to illustrate the adaptations.<\/p>\n\t \t \n

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NCTM’s Position Statement on High School Data Science Courses is Out!<\/strong><\/h3>\n \n\n \t \t

Read the National Council of Teachers of Mathematics’ latest recommendations and insights on integrating data science into high school curricula.<\/p>\n\t \t \n

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Beyond Borders 2024: Primary and Secondary Data Science Education Around the World<\/h3>\n \n\n \t \t

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.
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Newsletter<\/h2>\n\n\n\n

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.<\/p>\n\n\n\n

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Newsletter Archive<\/strong><\/span><\/h2>\n <\/div>\n
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ESTEEM Newsleter<\/h3>\n \n\n \t \t

February 2026<\/p>\n\t \t \n

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ESTEEM Newsleter<\/h3>\n \n\n \t \t

August 2025<\/p>\n\t \t \n

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ESTEEM Newsletter<\/h3>\n \n\n \t \t

Spring 2025<\/p>\n\t \t \n

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ESTEEM Newsletter<\/h3>\n \n\n \t \t

Fall 2024<\/p>\n\t \t \n

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ESTEEM Newsletter <\/h3>\n \n\n \t \t

Spring 2024<\/p>\n\t \t \n

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Join the ESTEEM Network Slack Channel<\/h2>

Connect with peers in our Slack workspace for lively discussions and shared insights.<\/p>\n

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Join here<\/span>\n<\/svg>\n<\/span><\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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\"Slack<\/figure>\n<\/div>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

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.   Newsletter The ESTEEM Network Newsletter intends to share resources, upcoming opportunities, and key efforts in the field. We aim to connect educators, researchers,…<\/p>\n","protected":false},"author":67,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"ncst_custom_author":"","ncst_show_custom_author":false,"ncst_dynamicHeaderBlockName":"ncst\/default-header","ncst_dynamicHeaderData":"{\"pageIntro\":\"Newsletters, Articles and Announcements\"}","ncst_content_audit_freq":"","ncst_content_audit_date":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-48","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/pages\/48","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/users\/67"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/comments?post=48"}],"version-history":[{"count":47,"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/pages\/48\/revisions"}],"predecessor-version":[{"id":1345,"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/pages\/48\/revisions\/1345"}],"wp:attachment":[{"href":"https:\/\/research.ced.ncsu.edu\/esteemhub\/wp-json\/wp\/v2\/media?parent=48"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}