2026 AI Educator Summer Institute

This session equips educators to address key limitations of AI tools, including bias and hallucination, often caused by reliance on uncontrolled or unreliable sources. It provides participants with the knowledge and hands-on experience needed to guide AI toward generating insights from curated, reliable, and controlled resources.    Participants will begin by comparing open- and closed-source AI tools, developing a clear understanding of their strengths, limitations, and appropriate use cases. They will then explore two project examples created with a closed-source platform such as Google NotebookLM, examining how these models can be adapted for technology and engineering classroom contexts. Next, participants will develop their own project and resource library on a topic of personal or curricular relevance, emphasizing organization, content curation, and instructional design. By the end of the session, educators will leave with a project in progress and a practical framework for selecting and applying AI tools in teaching.

In this session we will explore the heavy topics and controversies around A.I. in society and the classroom.  In particular, we will discuss our students using A.I. and how we can talk about it with them, guide them in best practices, and provide them safe ways to use and evaluate A.I. products. We will explore the current big research stories and how to avoid the brain rot that can come with human technology use. We will define bias in machine learning and how it impacts our ability to trust and rely on A.I. Finally, we will look at resources for creating classroom and school policies, and how to make the most of this powerful technology.

Is Social Studies in danger of being left behind in an ever-expanding AI world? As institutions push for rapid adoption, both educators and students are becoming wary of "AI slop"—generic, uncritical content that threatens to water down deep learning. This "boots-on-the-ground" session for Grade 6-12 educators moves beyond the hype to ask the hard questions: Do we actually need these tools, and how do we keep them from becoming a permanent crutch?

We will explore practical, guardrailed methods that use AI to spark historical inquiry and civil discourse without replacing the vital work of reading, writing, and analysis. Participants will discover strategies to maintain student critical thinking and traditional learning techniques while navigating modern technology. Learn how to implement ethical "human-in-the-loop" workflows that treat AI as a starting point, not the final word. Join us to ensure that in an age of automation, the human heart of Social Studies remains protected, rigorous, and relevant.

Powering Intelligence: How Electric Utilities Enable the AI Revolution

After engaging in this session, participants will be able to explain why AI uses so much electricity and how utilities like Duke Energy are addressing this demand while also using AI tools to run the grid better.

In this fascinating session, educators will learn how utilities like Duke Energy are using AI today to run the grid better. They will look inside a Data Center and discuss why AI uses so much electricity. Finally, attendees will get a glimpse into how utility companies are addressing rapid load growth while protecting customers. Attendees will learn about AI in the real world and how it impacts their lives every day. Educators are encouraged to consider how take this knowledge into their classrooms. 

In this session, I will invite educators to think about AI as more than a classroom tool. Instead of focusing only on prompting or productivity, we will explore AI literacy as a way to help students ask questions about ethics, bias, decision-making, civic life, and real-world systems. Using examples from English and interdisciplinary teaching, I will share practical strategies such as case studies, discussion prompts, short inquiry tasks, and values-based reflection. The goal is to help teachers move from general concern about AI to concrete classroom practice. Participants will leave with a clearer framework for teaching about AI, not just teaching with AI, and they will be ready to extend that work in the afternoon workshop.

In this extended afternoon workshop, participants will build on the morning session through focused, hands-on work. Educators will revisit the two project examples, taking a deeper look at their structure, design, and classroom applications, with an emphasis on adapting them to their own technology and engineering contexts.

Participants will continue developing the projects they began earlier, refining their resource libraries and expanding content using a closed-source platform such as Google NotebookLM. The session emphasizes curating high-quality materials, aligning resources with instructional goals, and designing practical implementation strategies, with opportunities for guided exploration and collaboration.

By the end of the workshop, educators will share their projects, exchange insights, and leave with a more developed, classroom-ready product and greater confidence in applying AI tools to support student learning.

The afternoon workshop will function as a hands-on design lab where participants adapt the ideas from the morning session into a classroom-ready resource. We will begin with a brief recap and discussion of how students may already be using AI as a shortcut, then examine sample resources such as AI comparison activities, verification checklists, reflection prompts, and student-facing protocols. These examples will be explored collaboratively, with attention to how they can be adapted across grade levels.

Participants will then select an existing lesson, assignment, problem set, lab, or project and redesign it to include structured, responsible AI use. Most of the workshop will be devoted to creation, peer feedback, revision, and facilitator support. Participants will focus on questions such as what students should do before using AI, how they should evaluate AI output, and what evidence they should use to justify agreement or disagreement. The workshop will culminate with participants sharing an adapted resource or implementation plan they can use when they return to school.

The workshop will divide participants into three groups (instructor tools, student tools, and curriculum design) and spend 30-40 minutes creating resources and developing ideas based on the morning sessions. After each 30-minute period, the groups will present their results, including problems they may foresee. The groups will then move to a different topic, with the understanding that the new group would develop totally new ideas. At the end of three rounds of this, the entire workshop would consider the larger problems from these three areas and how we might negotiate those issues. 

The afternoon workshop will be hands-on and product-based. After a short recap and model, participants would choose an existing lesson, text, unit, or topic from their own classroom and use a simple planning template to adapt it into an AI literacy resource. I will provide a small menu of sample case studies, guiding questions, and activity structures so teachers can either build from scratch or revise something they already teach. Most of the workshop will be devoted to drafting, conferring, and peer feedback, with time at the end for revision and sharing. The goal is for every participant to leave with at least one usable product—a discussion protocol, mini-lesson, case-study activity, assessment, or short inquiry sequence. If the participants stay for the entire  three hours, participants will expand their product into a fuller mini-unit; if they stay for 90 minutes, the focus will stay on one strong classroom-ready resource.

*This is a cohort session. Following one morning session on Monday, July 13, this group will meet every afternoon to continue its exploration and learning.*

In the afternoon sessions participants will continue to examine various problems in applied mathematics and will explore how AI connects disparate mathematical concepts.  By attempting challenging problems from various resources (e.g., the Mathematical Association of America, The Art of Problem Solving, and The American Mathematical Society), teachers will again apply a blend of traditional techniques and numerical tools to solve advanced problems; however, unlike the morning session these problems will include examples that current AI models often fail to thoroughly grasp. By discovering more of AI’s limitations, they will be reminded of the value of primary source materials, such as time-tested, multi-edition textbooks.  These examples will reinforce the necessity of human oversight and boost professional confidence in identifying "hallucinations" or errors.  Additionally, teachers will also be encouraged to research and solve relevant problems of interest to them and their particular course w

*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.

In this extended afternoon workshop, participants will build on the morning session through focused, hands-on work. Educators will revisit the two project examples, taking a deeper look at their structure, design, and classroom applications, with an emphasis on adapting them to their own technology and engineering contexts.

Participants will continue developing the projects they began earlier, refining their resource libraries and expanding content using a closed-source platform such as Google NotebookLM. The session emphasizes curating high-quality materials, aligning resources with instructional goals, and designing practical implementation strategies, with opportunities for guided exploration and collaboration.

By the end of the workshop, educators will share their projects, exchange insights, and leave with a more developed, classroom-ready product and greater confidence in applying AI tools to support student learning.

The afternoon workshop will function as a hands-on design lab where participants adapt the ideas from the morning session into a classroom-ready resource. We will begin with a brief recap and discussion of how students may already be using AI as a shortcut, then examine sample resources such as AI comparison activities, verification checklists, reflection prompts, and student-facing protocols. These examples will be explored collaboratively, with attention to how they can be adapted across grade levels.

Participants will then select an existing lesson, assignment, problem set, lab, or project and redesign it to include structured, responsible AI use. Most of the workshop will be devoted to creation, peer feedback, revision, and facilitator support. Participants will focus on questions such as what students should do before using AI, how they should evaluate AI output, and what evidence they should use to justify agreement or disagreement. The workshop will culminate with participants sharing an adapted resource or implementation plan they can use when they return to school.

The workshop will divide participants into three groups (instructor tools, student tools, and curriculum design) and spend 30-40 minutes creating resources and developing ideas based on the morning sessions. After each 30-minute period, the groups will present their results, including problems they may foresee. The groups will then move to a different topic, with the understanding that the new group would develop totally new ideas. At the end of three rounds of this, the entire workshop would consider the larger problems from these three areas and how we might negotiate those issues. 

The afternoon workshop will be hands-on and product-based. After a short recap and model, participants would choose an existing lesson, text, unit, or topic from their own classroom and use a simple planning template to adapt it into an AI literacy resource. I will provide a small menu of sample case studies, guiding questions, and activity structures so teachers can either build from scratch or revise something they already teach. Most of the workshop will be devoted to drafting, conferring, and peer feedback, with time at the end for revision and sharing. The goal is for every participant to leave with at least one usable product—a discussion protocol, mini-lesson, case-study activity, assessment, or short inquiry sequence. If the participants stay for the entire  three hours, participants will expand their product into a fuller mini-unit; if they stay for 90 minutes, the focus will stay on one strong classroom-ready resource.

*This is a cohort session. Following one morning session on Monday, July 13, this group will meet every afternoon to continue its exploration and learning.*

In the afternoon sessions participants will continue to examine various problems in applied mathematics and will explore how AI connects disparate mathematical concepts.  By attempting challenging problems from various resources (e.g., the Mathematical Association of America, The Art of Problem Solving, and The American Mathematical Society), teachers will again apply a blend of traditional techniques and numerical tools to solve advanced problems; however, unlike the morning session these problems will include examples that current AI models often fail to thoroughly grasp. By discovering more of AI’s limitations, they will be reminded of the value of primary source materials, such as time-tested, multi-edition textbooks.  These examples will reinforce the necessity of human oversight and boost professional confidence in identifying "hallucinations" or errors.  Additionally, teachers will also be encouraged to research and solve relevant problems of interest to them and their particular course w

*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.