ITEC Fall Conference 2026

This session will dive in Woodward-Granger’s approach to moving beyond living in a productivity only usage of AI. We will discuss our work around implementation of AI in our system as well as concrete examples of teacher and student use that enhances instructional practice.

I teach Digital Media and Production through our student-led Tiger Vision program at Carroll High School. My goal is to create authentic learning experiences where students use technology, creativity, and collaboration to produce work that has a real purpose and audience. Whether they're designing graphics, creating social media content, managing the Tiger Shop, or producing livestreams, students are telling the story of our school while building skills they'll use beyond high school.


In this session, I'll share how we've built a student-driven program that gives students ownership of their learning while helping them develop the communication, collaboration, creativity, and problem-solving skills that employers value. My hope is that educators leave with practical ideas and the confidence to create authentic opportunities where students use technology to make meaningful contributions to their schools and communities.

In 1997 a computer beat the world chess champion, and within a week people were explaining that chess had never really been about intelligence anyway. We've done that every time since. Face recognition isn't understanding. Composing isn't knowing what you made. Researchers call it the AI effect: the moment a machine can do something, we stop counting it as intelligence.
So where do you put the line?
Working in small groups with a physical card deck, you'll sort ten human capacities from least to most uniquely human and discover your table can't agree, and that the argument was never about AI at all. Then you'll rank them again on your own and take your ranking to an AI that ranked the same ten, and argue with it about the biggest gap.
You'll leave with one capacity you'd fight to protect, one change you'll make to protect it, and a card deck you can print and run with your own students.

Artificial Intelligence is changing how students learn, create, and solve problems, but many educators still view AI as a mysterious "black box." Understanding how AI processes questions can help both teachers and students become more thoughtful, effective, and ethical users of these powerful tools.


In this highly interactive session, participants will experience hands-on activities that model how modern AI systems organize information using embeddings, retrieve relevant knowledge through concepts like Retrieval-Augmented Generation (RAG), and generate responses through next-token prediction. Rather than focusing on prompt "tricks," we'll explore why strong inquiry skills naturally lead to stronger AI interactions.


Through games, discussion, and inquiry-based learning, participants will build an intuitive understanding of how AI interprets context, why additional information improves responses, and how better questions help both humans and AI learn more effectively.


Participants will leave with classroom-ready activities, a practical mental model of how generative AI works, and new strategies for helping students develop one of the most important skills of the AI era: asking better questions.


Participants will:

• Explain, at a conceptual level, how modern generative AI processes prompts. 
• Experience how embeddings organize information through hands-on activities. 
• Understand how context influences AI responses and why richer prompts produce better results. 
• Connect inquiry-based teaching practices to effective AI use. 
• Leave with classroom-ready activities for developing AI literacy.