2026 AI Educator Summer Institute

This session will highlight practical AI implementation strategies for the science classroom. AI tools do not need to replace student thinking, but can be used to enhance student understanding and reasoning. In this session, we will discuss how AI can be used to support inquiry-based learning, data analysis, and scientific thinking. We will also discuss what responsible AI use in the classroom can look like, with students using AI tools to verify information, cite sources, and critically evaluate AI-generated claims, while also balancing over-reliance. We will use real classroom examples to utilize AI tools in modeling, creating simulations, and data interpretation.

As teachers, we get why our lessons about data are important, but do our students? Let's explore ideas that help students become more engaged in lessons about data and help them find relevance in what they are studying.

Workshop time will be structured by providing teachers with options for how to use the workshop time productively. The three main options teachers will be directed towards will be reworking existing problems in their own materials, creating their own progression of lessons following the same sequence from their curriculum, or developing a student driven/student centered data unit. Teachers will be able to determine their own starting ppoint and move flexibly among these outcomes. Collaboration with grade level peers and school based teams will be encouraged, but not required.

Among the additional resources teachers will be encouraged to use are CODAP, PHet, Pudding.cool, and https://www.datascience4everyone.org/datasets

*This is a cohort session. All participants who attend the morning session are invited to attend an accompanying afternoon expansion pack session each afternoon this week to apply your morning learning to the Special Education classroom.*

The 3-hour afternoon workshop gives participants dedicated creation time to apply the morning's framework to real materials from their own classrooms. It is structured as a creation studio rather than a continuation of the lecture.

Hour 1 (1:00–2:00) — Identify and Design: Participants select one real instructional challenge. A lesson that needs differentiation, a text that needs to be adapted for a lower reading level, an assessment that needs scaffolding, or a documentation task they want to streamline. Small groups form around shared challenges. Special educators learn as much from each other as from any presenter. Introduction to the creation workflow: original material → AI prompt → draft → critical review → revision.

Break (2:00–2:15)

Hour 2 (2:15–3:15) — Create: Hands-on creation using Gemini and NotebookLM. Facilitator circulates with targeted coaching. Structured peer feedback in pairs: Does this serve the student? What did the AI miss that a human expert would catch? What needs to be fixed before this goes near a classroom?

Hour 3 (3:15–4:00) — Share, Critique, and Plan: Small group shares. Not just "look what I made" but "here's what the AI got wrong and how I fixed it." Whole-group reflection on AI as a tool for inclusive practice versus a shortcut that bypasses expertise. Individual action planning to identify one specific thing I will try with students in fall 2026.

Participants leave with a real, usable adapted resource and a realistic, critical framework for continuing independently.

The afternoon workshop will allow teachers to investigate some of these tools and develop their own models, simulations, or data interpretation ideas. I’d like to introduce my collaboration with Taylor to create a simulation for my passion project, as well as some other data analysis tools (CODAP, Data Story Bytes, and websites to collect large data sets from including Kaggle).

The workshop would be divided into two mini sessions. The first will focus on simulation creation. The teachers will be able to work on creating their own simulations in pairs, then share with the group. The second session will focus on data analysis tools and will be conducted in a similar manner.

Workshop time will be structured by providing teachers with options for how to use the workshop time productively. The three main options teachers will be directed towards will be reworking existing problems in their own materials, creating their own progression of lessons following the same sequence from their curriculum, or developing a student driven/student centered data unit. Teachers will be able to determine their own starting ppoint and move flexibly among these outcomes. Collaboration with grade level peers and school based teams will be encouraged, but not required.

Among the additional resources teachers will be encouraged to use are CODAP, PHet, Pudding.cool, and https://www.datascience4everyone.org/datasets

*This is a cohort session. All participants who attend the morning session are invited to attend an accompanying afternoon expansion pack session each afternoon this week to apply your morning learning to the Special Education classroom.*

The 3-hour afternoon workshop gives participants dedicated creation time to apply the morning's framework to real materials from their own classrooms. It is structured as a creation studio rather than a continuation of the lecture.

Hour 1 (1:00–2:00) — Identify and Design: Participants select one real instructional challenge. A lesson that needs differentiation, a text that needs to be adapted for a lower reading level, an assessment that needs scaffolding, or a documentation task they want to streamline. Small groups form around shared challenges. Special educators learn as much from each other as from any presenter. Introduction to the creation workflow: original material → AI prompt → draft → critical review → revision.

Break (2:00–2:15)

Hour 2 (2:15–3:15) — Create: Hands-on creation using Gemini and NotebookLM. Facilitator circulates with targeted coaching. Structured peer feedback in pairs: Does this serve the student? What did the AI miss that a human expert would catch? What needs to be fixed before this goes near a classroom?

Hour 3 (3:15–4:00) — Share, Critique, and Plan: Small group shares. Not just "look what I made" but "here's what the AI got wrong and how I fixed it." Whole-group reflection on AI as a tool for inclusive practice versus a shortcut that bypasses expertise. Individual action planning to identify one specific thing I will try with students in fall 2026.

Participants leave with a real, usable adapted resource and a realistic, critical framework for continuing independently.

The afternoon workshop will allow teachers to investigate some of these tools and develop their own models, simulations, or data interpretation ideas. I’d like to introduce my collaboration with Taylor to create a simulation for my passion project, as well as some other data analysis tools (CODAP, Data Story Bytes, and websites to collect large data sets from including Kaggle).

The workshop would be divided into two mini sessions. The first will focus on simulation creation. The teachers will be able to work on creating their own simulations in pairs, then share with the group. The second session will focus on data analysis tools and will be conducted in a similar manner.