Last week, I attended this great webinar hosted by AI for Education. When we hear AI, we usually think of ChatGPT or high-tech tools that aren't exactly age-appropriate for a 6-year-old. But the session made a compelling case: AI is already part of our students' lives, from the videos recommended to them on YouTube to the voice assistants they talk to at home.

The big takeaway? We aren't recommending direct student use of AI before third grade. However, we have a responsibility to build AI Literacy early on, and we might be surprised how much will click with our students.

How do we teach AI to young learners?

The goal isn’t to get kids "on" the tech, but to help them understand the world around the tech. Here’s what was covered:

• Spotting AI in the Wild: Using real-world examples to show kids that AI is a tool humans built. It’s in our Netflix recommendations…

(Simple shifts to build career readiness - without adding more to your plate.)

Career readiness doesn’t have to be one more thing - it can be how your classroom already operates!

A recent webinar EdWeb “Design for Career Readiness: Using the National Career Clusters Framework to Build Classrooms That Function Like Industry” - highlights a simple but powerful idea: any classroom (CTE, STEM, or core content) can function more like industry with a few intentional moves!

📊 A Quick Foundation: What’s the Career Clusters Framework? 

The Advance CTE National Career Clusters® Framework organizes careers into broad pathways and emphasizes:

• Real-world application of academic skills

A recent edWebinar - Boost Math Relevance with Career-Connected Learning edWebinar- highlighted a simple shift with big impact: when students see how math is used in real careers, engagement and understanding increase.

This isn’t about new curriculum - it’s about connecting what you already teach to real-world application.

What This Looks Like in Practice

Construction & Skilled Trades

• Math: Measurement, geometry, ratios

Thanks to one of the latest ChatEDU episodes, I recently came across a post by Carla Engelbrecht Fisher that felt really relevant as we look at infusing AI into existing engineering lessons for this year's for Oregon STEM Week:

14 Ways to Remind Yourself (and Your Kids) AI is a Machine, Not Your Friend

This article is full of simple, relatable ways to help students (and us!) understand what AI is (and isn’t).

At its core, the post reinforces a few key ideas that are essential for students: AI doesn’t think - it predicts. AI doesn’t understand - it patterns. And sometimes, it gets things wrong in ways that feel surprisingly human.

What I appreciate most is how actionable her approach is. Here are five of the 14 ways she suggests we can start talking about AI with kids:

1. AI is an it.

If you’re looking for a clear, current snapshot of where Career & Technical Education is headed - and what to do about it - the Disruption: CTE report offers a valuable, all-in-one reference.

The full report is linked above and attached as a PDF, making it a practical, go-to guide for understanding how CTE is evolving, and how schools can respond in real time.

What’s Changing (and Why It Matters)

• CTE is now foundational. It’s no longer an “alternative” - it’s central to preparing all students for what’s next.

• The readiness gap is real. Most employers and students agree: current systems aren’t fully preparing learners for the workforce.

As conversations around AI in education continue to grow, it’s easy to get swept up in tools, efficiency, and what’s possible. But there’s a quieter - and arguably more important - question sitting underneath it all:

What happens to human connection as chatbot use continues to grow amongst students and models become more "lifelike"?

Recently, I came across the Rithm Project's Sparks Toolkit, and it felt like a really timely resource for educators navigating this exact question.

At its core, the Sparks Toolkit isn’t about technology at all. It’s about relationships, empathy, and helping students better understand themselves and each other. It offers simple, classroom-ready activities designed to build connection between students, and between students and educators.

And connection feels like exactly what we need right now.

It's a modern teaching paradox that we all grapple with: How do we equip our students with foundational Computational Thinking skills while honoring the research that tells us young children learn best by doing, not by staring at a screen?

The answer might be just outside your classroom door!

Earth: The Ultimate Open Source Code

In many ways, Earth is the world’s oldest and most sophisticated engineer. From the structural efficiency of a honeycomb to the network architecture of a forest’s root system, nature has been debugging its designs for billions of years. When we shift our STEM focus from screens to systems, we realize that nature is actually a massive, unplugged lab for exploring design and logic.

Coding as the New Literacy

The research of experts like Marina Bers helps us understand that coding isn't just a technical skill; it’s a fundamental literacy.

A new national report, Applied Co-Intelligence: Preparing Career and Technical Education Learners for an AI-Driven Workforce, offers a timely roadmap for CTE educators navigating rapid advances in artificial intelligence. The report argues that while AI may not eliminate entire occupations, it will significantly change the composition of jobs across industries - and CTE is uniquely positioned to respond.

At the center of the report is the Applied Co-Intelligence (ACI) model, which calls for the integration of three interconnected skill areas:

• Technical skills

• Transferable skills (critical thinking, communication, ethics)

• AI mastery (from basic literacy to evaluation and adaptation)