STEM Summer Institute 2026

Data investigations provide meaningful opportunities for students to reason, communicate, and make sense of the world around them. In this interactive session, educators will experience research-based instructional routines that promote mathematical discourse, curiosity, and critical thinking through authentic data. Participants will engage as learners, explore adaptable routines for grades K–5, create a slow reveal graph, and receive ready-to-use lessons, templates, and printable resources designed to support immediate classroom implementation.

Looking for ways to integrate data science skills into your classroom but not sure where to start - or need new resources to add to your existing toolkit? In this hands-on session, educators will discover a curated selection of practical, classroom-ready resources designed to bring engaging data science experiences to K-12 students. We’ll introduce three distinct sets of tools and materials, each focused on fostering high-level data science skills such as critical thinking, data analysis, and ethical reasoning. These resources are intentionally designed to be adaptable across multiple subject areas, empowering teachers to seamlessly integrate data science into their existing curricula. Whether you teach math, science, social studies, or language arts, you’ll leave the session with actionable strategies and ready-to-use materials that you can implement in your classroom the very next day.

In this session, we will engage in a learner-centered approach to developing scientific principles through data. Participants will work together to build a model of a phenomenon that they observe through videos and experimental apparatus. We will conclude by looking at student data from their engagement in a similar activity. We will discuss how “pedagogical tools” can be used to facilitate knowledge construction in the classroom using science and engineering practices.

Explore aiEDU's proven approach to building communities of practice using AI literacy-focused curriculum and aiEDU’s AI Trailblazers Fellowship as a model. Examine aiEDU's AI Readiness Framework to identify the student competencies essential for AI literacy and readiness, and use it as a lens for evaluating curricular resources. Apply these competencies to analyze instructional practice, discuss strategies for replicating AI-focused CoPs in your own setting, and develop an actionable implementation plan.

This presentation details the application of the Rapid Forest Assessment protocol for systematically collecting and analyzing ecological data in a forest landscape. Participants will learn how to implement RFA as a citizen science collaboration with local public land managers. Data collected and organized by students can provide land managers with a clear, science-based assessment to evaluate the success of fire as a management tool, track ecosystem health, and make informed decisions for future landscape resilience. Participants will also learn about other STEM resources related to citizen science and the SMART FIRES project (Sensors, Machine Learning , and Artificial Intelligence for Real-Time Fire Science). Attendees will have the chance to win one of two Rapid Forest Assessment kits to take home with them.