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.

In this hands-on session, educators will explore IBM SkillsBuild through Discovery Education and learn how to navigate courses that build foundational AI and digital skills with confidence. Participants will gain a clearer understanding of AI concepts, digital literacy, responsible use, and workforce-aligned skills that can support both teacher learning and student readiness.

This session will also lay the foundation for the afternoon Expansion Pack Workshop, where educators will apply what they learned to classroom instruction. Educators will use their new AI knowledge to determine when AI is the right tool, how AI can increase rigor, and how AI can provide additional supports or accommodations for students as they design lessons for their own subject areas and grade levels.

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.

In this interactive afternoon workshop, educators will move from awareness to application by exploring research-based Discovery Education SOS Instructional Strategies that can be used across grade levels and content areas. Participants will work collaboratively to develop, curate, adapt, and practice strategies they can immediately implement in their classrooms.

Educators will first explore high-impact instructional strategies that work with or without AI, then examine how AI can be used intentionally to increase rigor, support accommodations, extend student thinking, and create more responsive learning experiences. Using knowledge from the morning session, participants will design or adapt classroom-ready lessons for their own subject areas while determining when AI adds value and when strong instructional strategy alone is enough.

Educators will leave with:

5–7 practical instructional strategies they can use for engagement, discussion, collaboration, and formative assessmentA stronger understanding of when AI can meaningfully support instructionA classroom-ready plan for using AI to increase rigor, support student needs, and strengthen learning

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. 

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.

In this interactive afternoon workshop, educators will move from awareness to application by exploring research-based Discovery Education SOS Instructional Strategies that can be used across grade levels and content areas. Participants will work collaboratively to develop, curate, adapt, and practice strategies they can immediately implement in their classrooms.

Educators will first explore high-impact instructional strategies that work with or without AI, then examine how AI can be used intentionally to increase rigor, support accommodations, extend student thinking, and create more responsive learning experiences. Using knowledge from the morning session, participants will design or adapt classroom-ready lessons for their own subject areas while determining when AI adds value and when strong instructional strategy alone is enough.

Educators will leave with:

5–7 practical instructional strategies they can use for engagement, discussion, collaboration, and formative assessmentA stronger understanding of when AI can meaningfully support instructionA classroom-ready plan for using AI to increase rigor, support student needs, and strengthen learning

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. 

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.