I.T.S. News and Events

 

Picture this. I was in the middle of teaching my 8th grade science class, the last lesson before a chemistry quiz. About half the class finished early, and I started to panic. The review and activities I planned should have lasted the entire 80 minute block, and now I had 40 minutes left.

So I pulled up one of the AI tools TSD was piloting and let the students pick. They chose “Choose Your Own Adventure.”

I had no idea if it would work or even be helpful. As a class, they helped build the prompt.
“Zombie apocalypse!” one student yelled.
“Make them all friendly!” another added.

We included the standards from the review, I clicked launch, and off they went.

A few minutes in, there were laughs, but also confusion. It got too deep, and suddenly we were talking about homonuclear diatomic molecules that were not even in our unit. So we adjusted. I uploaded the chapter we were working on.

More time, more laughter, and then some honest feedback. “This is fun, but it’s not helping us study.”

So we adjusted again.

I switched tools and created a fill in the blank review and flashcards in real time, projecting everything through Vivi. Students saw every choice, every phrasing decision, every typo. We were learning together in real time.

As I continue using AI in the classroom, here are three things I’ve learned.

1. Learning Together (Embracing Imperfection)

This is not something I have to master ahead of time. It can grow with the class.

I used to think everything had to be perfect before students walked in. The lesson plan, the lab setup, the visuals. I approached AI the same way at first. I thought I needed to have everything dialed in so students would not see me struggle.

Now I see it differently.

Students already help build the classroom. They help set up labs, adjust lessons, and contribute ideas. AI is just an extension of that.

During a STEAM career essay unit, students wanted feedback all at once. I could not keep up. So I paused, pulled up MagicSchool on Vivi, and we built a writing feedback tool together. They chose the focus areas and essentially created a rubric as a class.

Suddenly, each learner could get feedback in real time that met them where they were.

Now, I still plan ahead sometimes. I have used AI to scaffold intervention lessons or generate targeted practice. But it does not always have to start that way.

Which brings me to Thing 2.

2. There’s No “Right Way” (Permission to Experiment)

Teachers will not use every tool, and that is okay.

Just like we do not give every student the same task, teachers will not use AI in the same way. That is not a failure. That is good teaching.

There are tools I will never use because they do not fit my role. And sometimes, I just use a chatbot because it is faster than searching through options. That is okay too.

What matters is how we support students.

Students need scaffolding with AI just like any other skill. It is overwhelming, and it is evolving quickly. We would never assign a full essay without supports, so we should not expect students to use AI without guidance.

Create structured spaces. Set clear expectations. Let students help build those spaces with you while you are learning alongside them.

3. Relevance Over Technology

Students have mixed reactions to AI. Some are excited. Some are hesitant. Some want nothing to do with it.

AI itself is neutral. Relevance and relationships are what drive engagement.

Technology does not create engagement on its own. If a student wants to disengage, they will find a way with or without it. If they want to learn, they will.

So the question is not, “How do I use AI to make students care?”
It is, “How does AI help me show relevance faster?”

The real time writing feedback mattered because it met students in the moment. The chemistry review worked because students helped shape it. It connected to what they cared about.

That is what made the difference.

Conclusion

You do not need to be an AI expert. Your students do not either.

Stop waiting until everything feels figured out. Start small. Start messy. Start with your students.

Because when you do, you are not just introducing a tool. You are showing that learning is something we build together. And that matters far more than any perfectly planned lesson.

 

In writing this, I used AI to help refine wording and proofread. The ideas, decisions, and perspective are entirely my own.

 

Technanigans returns for its second year, bringing educators together to strengthen their practice and learn from one another. The experience centers on refining what works, staying curious, and exploring how technology can support learning across classrooms and professional practice.

The theme Redefining Learning reflects the shifts happening in education as new tools, new possibilities, and new questions continue to emerge. It invites educators to think about how learning is changing, how classroom experiences can expand, and how technology can be used in ways that open up opportunities that were not possible before. It also draws on the SAMR model, where redefinition represents transformation through technology integration, creating something that couldn’t have been possible without technology.

"Year 1 sparked ideas—Year 2 is where we bring them to life. Technanigans provides the hands-on learning, collaboration, and innovation we need to turn emerging tools into real impact for students,” Chief Technology Officer Kelly Sain said.

This year, Technanigans connects with the Summer Symposium to create two full days of learning for TSD staff and educators from across Colorado. Together, these experiences expand opportunities for collaboration, allowing educators to learn from colleagues within the district and from across the state.

Holly Clark, keynote speaker for Technanigans, brings a nationally-recognized voice in educational innovation and AI integration to TSD. Her work focuses on helping educators use technology in thoughtful, purposeful ways that support strong instruction. Her message aligns closely with the work across TSD, where the focus remains on thoughtful use of tools to support teaching and learning while maintaining the central role of educator expertise.

Across both days, participants will experience sessions led by TSD educators, educators from across Colorado, and our keynote speakers. These sessions highlight how technology is being used in real classrooms, with a focus on instructional strategies, intentional integration, and the purpose behind when and why to use these tools.

This year also introduces a new type of session: the Model Classroom. Educators often leave conferences with exciting ideas, but without a clear path for applying them in their classrooms. These sessions are designed to bridge that gap. During each 50-minute session, participants step into the role of students as the facilitator leads either an elementary or secondary model lesson that integrates technology in intentional ways. Each session then transitions into a debrief, where participants reflect on what they experienced and consider how the instructional moves and use of technology could transfer to their own classrooms.

Technanigans continues to be a space for connection, reflection, and growth. It is an opportunity to learn with colleagues, explore new ideas, and continue refining practice together.

Registration is now open for both Technanigans and the Summer Symposium. We invite you to join us for two days of learning and collaboration!

Any time we step into new ideas, new tools, or new possibilities, it can be energizing. There’s a kind of momentum that comes from imagining what could be different, what could be strengthened, or what could be possible.

The real work though, is not about chasing inspiration somewhere else. It’s about bringing focus to the work we are already doing. How do we thoughtfully integrate powerful tools into classrooms, systems, and daily practice in ways that align with what we value most about learning?

This moment feels like a transition: the practice of teaching and learning is being asked to evolve not only because new tools exist, but because we have an opportunity to examine our priorities and ensure they reflect our deepest educational values.

For a long time, there has been a desire to move toward student-owned learning that is deeply personal, driven by passion, and shaped by student voice. At the same time, it has often felt like an almost insurmountable challenge to make that vision real within the confines of traditional school structures.

AI is not creating new questions so much as amplifying the ones we’ve had for a long time. It is surfacing long-standing tensions in teaching and learning, while also opening new possibilities for more responsive, student-centered classrooms. At the same time, this moment raises urgent questions about trust, equity, and what we want learning to become. In many ways, the work underneath it is not actually about AI at all. It is about learning, values, and decision-making, and powerful tools simply make those questions harder to ignore.

If you’re feeling the pressure to move fast with AI, you’re not alone. When decisions impact students directly, it’s worth slowing down enough to stay thoughtful.

It doesn’t have to be about rushing toward the next tool or trying to have all the answers. It’s about staying close to what we know matters most in teaching and learning, and taking the next step with care.

Here are three things worth holding in the back of our minds as we decide what AI should, and shouldn’t, do in learning spaces.

1. Human First, Human Last

The most important part of any AI experience is the human.

AI can support our work in powerful ways, but it should serve human aspirations, values, and decisions, not take the place of them.

One of the biggest risks is letting AI quietly take away agency, for teachers or for students. When a tool starts shaping the work before we’ve had a chance to think, question, or create, something important is lost.

Agency is at the heart of student-owned learning. It relies on learners actively shaping their thinking, their questions, and their voice. If AI begins to do that work for us, we risk moving farther away from the responsive, human-centered classrooms we hope to create.

It can be helpful to think about the difference between outsourcing the doing and outsourcing the thinking. AI may support the doing, but the thinking, the struggle, and the meaning-making must remain human.

Humans bring the goals, the questions, and the context. AI can help refine ideas, but the work is strongest when it begins with human intention and ends with human decision-making.

AI is a tool that should serve human intentions, not replace human judgment.

When conversations drift toward tools and features, it helps to return to a simple frame: Human first, human last.

2. What’s the Learning?

With the human at the center, the next question becomes even clearer: what is the learning?

When conversations about AI get stuck, it’s often because we skip this question.

Before deciding whether a tool belongs in a lesson, it helps to pause and ask: What is the thinking we want students to engage in?

AI can be helpful in reducing friction, generating ideas, or supporting the work around learning, but it can also blur the line between supporting a process and replacing it. If a tool begins doing the thinking that students need to do for themselves, then the learning shifts in ways that may be unintended.

The learning often lives in the process, not just the product. In math, for example, the goal is rarely just the final answer. It’s the reasoning, the problem-solving, and the persistence it takes to get there. A tool that shortcuts that process can also shortcut the learning.

AI has a way of surfacing these kinds of misalignments. It asks us to be more intentional about what we truly want students to engage in.

When we name the learning first, whether the goal is communication, reasoning, revision, or problem-solving, we create space for students to stay at the center of the experience.

Tools should follow the learning, not lead it.

3. What’s the Right Tool for the Job?

Choosing the right tool starts one step earlier than the tool itself. The first question is: what is the best method to achieve the learning outcome?

Some outcomes require practice and feedback. Others require discussion, reflection, or productive struggle. Sometimes the best method is modeling and guided instruction. Sometimes it is inquiry, revision, or collaborative sense-making.

Once the method is clear, the tool choice becomes much easier. AI can be useful when it supports the method, reducing barriers, offering examples, or helping students rehearse skills. But if it shortcuts the thinking we want students to engage in, it may work against the outcome.

Sometimes the right tool is AI. Sometimes it is paper, a whiteboard, a peer conversation, or time. The goal is not a specific tool. The goal is learning.

A Closing Thought

Many of the hardest conversations about AI are not really about technology. They are about learning and values, about what we are trying to preserve and what we are willing to change.

Learning clarity may be some of the most important work we do right now, staying grounded in what matters most and moving forward thoughtfully alongside our students.

How AI Was Used in This Document

In writing this, I used AI to help brainstorm and expand on the ideas I wanted to highlight, along with some final proofreading and word choice. The thinking, values, and final decisions remained my own throughout the process.