Asynchronous

​Tuva's Data Literacy Microcredentials Workshops are designed to empower educators with the skills and knowledge to integrate data literacy into their teaching practices. These workshops provide hands-on experience with Tuva's intuitive data and graphing tools, enabling teachers to engage students in authentic problem-solving and develop a deeper conceptual understanding of mathematics and science. Participants will learn how to explore, visualize, and analyze data, fostering critical data literacy skills essential for navigating today's information-rich world.

July 7-11`

In addition to our demonstrations of lesson plans and hands-on activities focused on teaching science, we are excited to partner with DataClassroom to help STEM educators build confidence with data collection, formatting, graphing, and statistical analysis. No prior experience is necessary - we will begin with the basics to help you discover exciting new possibilities for teaching data skills - from learning with curated datasets to the analysis of new data collected right in your classroom! During the workshop, we will start with Classroom-Ready lesson plans based on real datasets, then conduct our own studies in the classroom (and outdoors!) to build confidence in a variety of different ways to teach data collection, analysis, and graphing.

July 28-30

The 7th Annual STEM Summer Institute is a one-of-a-kind, Montana-made showcase for STEM integration across all grades and subject areas. You’ll enjoy exemplary K-12 STEM instruction and resources, inspiring national speakers, and the best of Montana!

Stay tuned for more details coming soon!
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Registration will open in January, 2025.

July 29

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 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.

Asynchronous

This course is designed to help anyone learn and teach with a 21st-century approach to knowledge and teaching. We hope the ideas will help you as a person and help you learn new teaching ideas to share with learners. The course includes a focus on data literacy, and shares content knowledge and teaching ideas for that area. If you are having thoughts of "I don’t know a lot about data" or "That sounds very maths-ey and I don’t like maths," don't worry -- this course is designed to be accessible to you. Whether you are a kindergarten teacher, a high school history or maths teacher, an administrator or parent, or someone just curious about data, there will be ideas for you. By taking this course, you are agreeing to participate in studies that we may conduct as part of our ongoing research into online learning.

Asynchronous

If you’re a grades 4-10 science, social studies or math teacher looking to uplevel your graphing while working less hard at it so that it can work better for your students than you already know that…practice makes progress!

By the end of this course,
you will confidently…


Know each data visualization type forwards-and-backwards.
Knowing what the various graph, chart, plot, and map types are that we are asking our K-12 students to know is HUGE for us being able to teach our students about them.
Easily identify when and why to make each data visualization type.
Knowing what they are is only a first step with data visualizations. Knowing that you can easily and quickly pick the best graph, chart, plot, map type for your dataset and students need is CRITICAL.
Make each data visualization -- using free software -- like the rockstar you are!
Knowing what, why, and when are important but...the meat of it all is being able to make whichever graph, chart, plot, map that you want with ease and success yourself so that you can teach them to your students

July 14-19

We're thrilled to once again partner with Cleveland State University and CSforCLE, bringing Bootstrap:Data Science to educators from across the state of Ohio. You can find more about the Teach CS program here. Registration for this professional development workshop will open soon, so save the date and stay tuned!