2026 AI Educator Summer Institute

This session will engage participants in the development of a cross-disciplinary data science course aimed at students and teachers with no prior coding background. It introduces the fundamentals of Data Science across subject areas with an introduction of Python and  with Jupyter notebooks. This session will challenge participants to imagine an introductory CS course that cuts across all subjects and can be taught by someone from any department with a little motivation. All backgrounds, subject areas, and skill-levels welcome.

This session will engage participants in the development of a cross-disciplinary data science course aimed at students and teachers with no prior coding background. It introduces the fundamentals of Data Science across subject areas with an introduction of Python and  with Jupyter notebooks. This session will challenge participants to imagine an introductory CS course that cuts across all subjects and can be taught by someone from any department with a little motivation. All backgrounds, subject areas, and skill-levels welcome.

*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.

Now that participants understand the goal and exciting potential of this course, we will start exploring the design and content of the course. In the first part of the workshop we will do a group data science activity to get used to Jupyter Notebooks and Python. In the second part of the workshop attendees will be given time to explore resources and build their own lesson in a chosen disciplinary area with the aim of building a library of activities across disciplines that could be used by this introductory course for teachers across the state. 

*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.

Now that participants understand the goal and exciting potential of this course, we will start exploring the design and content of the course. In the first part of the workshop we will do a group data science activity to get used to Jupyter Notebooks and Python. In the second part of the workshop attendees will be given time to explore resources and build their own lesson in a chosen disciplinary area with the aim of building a library of activities across disciplines that could be used by this introductory course for teachers across the state.