5 Strategies to Combat AI in the Secondary Classroom

In my last blog post, I shared a few key insights from the past school year, including how I’m addressing AI and student work in my classroom.  I ended that reflection acknowledging that I’m still in the process of figuring it out.  I’m not ready to implement a FINAL system (in our ever-evolving technological world, is that even possible?!), but I’m continuing to refine what meaningful learning looks like in a classroom where students have access to powerful tools that can "think" for them.

Strategy 1: Designing tasks where thinking is visible

The biggest shift last year wasn’t a single strategy. It was a design principle: I needed learning experiences where student thinking was visible throughout the process, not just in a final submission.

That meant reworking assignments so that I could actually see how students were developing ideas before they submitted the final polished version. Instead of treating thinking as something that happens privately and is then submitted, I started building structures that made the thinking part of the work.  

For example, I began incorporating more handwritten brainstorming, annotation, and quick writes before students ever opened a Chromebook. Students completed graphic organizers, responded to higher-level discussion questions, and used exit tickets to justify a claim or explain their reasoning. During literature units, they had to annotate passages, defend an interpretation with textual evidence, or explain their thinking during small-group or whole-class discussions before moving on to a larger assignment. These smaller moments of visible thinking gave me a much clearer picture of student understanding rather than just relying on a final product alone. 

With every assignment, I started asking this question: "Where will I see students thinking?" All of the strategies in this post grew out of that one guiding question.

Strategy 2: Bringing more writing into the room

One of the most effective changes I made in response to the rise of AI was moving more writing and literary analysis in terms of essay-writing into in-class time. This didn't eliminate independent work or at-home writing, nor was it intended to prevent students from ever using AI. Instead, it ensured that I could see the early stages of their thinking right in front of me before outside tools entered the picture. I could break the writing into chunks where I could use checkpoints and observe how students developed ideas and where they needed support.

It also changed the way students approached writing. When they know part of the process is happening in front of you/ the teacher, there's a different level of engagement with drafting, revising, and decision-making. Rather than relying on a polished final product that may or may not reflect a student's own thinking, I was able to assess the thinking that led to the writing. It became less about producing a perfect essay and more about developing ideas over time.

Strategy 3: Making close reading more grounded and less “searchable”

I also intentionally shifted away from over-reliance on digital tools during certain reading tasks. With AI making it easier than ever for students to generate summaries, explanations, and even literary analysis, I wanted to create more opportunities for them to interact with the text themselves before turning to outside resources. To do this, I made sure to use printed texts and handouts to create a slower, more focused reading environment. We use the My Perspectives textbooks, so reading texts like Romeo & Juliet and The Odyssey were easy to accomplish this way.  Students also have their own copies of the novels we read, so they annotated directly on the page, marked up passages, and physically interacted with each text in a way that reduced distraction and made their thinking easier to track.  I also gave students physical handouts that they completed IN class so that they couldn’t just ask an AI tool to spit out an answer.  

This wasn't about avoiding technology or suggesting AI has no place in the classroom (more on this to come in a future blog post). It was about choosing the right tool for the type of thinking I wanted to see. When the goal was close reading, interpretation, and analysis, I found that putting a printed text in students' hands often led to deeper engagement and more authentic evidence of their understanding.

Strategy 4: Building discussion as a core form of assessment

I’ve always been a proponent of structured discussion in class, but it’s becoming even more valuable in a world where AI can generate thoughtful-sounding responses in seconds.  It’s important that students have opportunities to articulate their own thinking in real time. So more and more I’ve used discussion activities that ask students to explain their thinking, respond to peers, and build on others’ ideas. This can sometimes lead to students revising their own thinking as the conversation unfolds.  THAT is very powerful!

These discussions can be incredibly revealing. You can learn a lot from a student's writing, but you learn something different when they have to explain an idea spontaneously, defend it with evidence, or respond to a classmate's perspective. It also creates a layer of accountability because students know they need to truly understand the content and be able to explain their ideas in real time instead of just submitting a polished piece of writing.  In an age of AI, real-time conversations have become some of the most authentic evidence of student learning in my classroom.

Strategy 5: Conferencing with Students Throughout the Process 

Another valuable shift I made was building more opportunities to conference with students throughout longer assignments. In the past, I often assigned a project and had students complete much of the work outside of class. While I had already built checkpoints into major essays, last year I started using that same approach with more assignments. Instead of waiting for a final submission, students worked through stages of projects while I checked in with them along the way.

Those informal conferences became some of the best windows into student thinking. I could ask students to explain why they chose a piece of evidence, defend an interpretation, or talk me through their reasoning for an image they chose or drew to represent a significant aspect of a literary work.  

This approach also made the learning process more transparent. I could see students' ideas developing over time instead of trying to infer their thinking from a polished final product. As an added benefit, breaking larger assignments into smaller checkpoints reduced the "all or nothing" pressure that often comes with major projects. 

Final Thoughts

So, it boils down to this for me: If I can't see my students' thinking, what exactly am I assessing? That's the real lesson AI has reinforced. It's not about eliminating technology or trying to outsmart it. It's about designing learning experiences where students have to actually do their own thinking (at least at first).  

I don’t think AI is going anywhere, and I DO think it has its place in education. Our students live in the real world, and AI, like it or not, is part of that world. They need to learn how to use it ethically and responsibly.  BUT, before students ask AI to help them think better, they first need to learn how to think for themselves. They need opportunities to think deeply about complex texts, to develop original ideas, to defend their reasoning, and to communicate their thinking without relying on a tool to do the cognitive work for them. Once that foundation is in place, AI can become a tool that enhances learning rather than replaces it.

That's the balance I'm striving for, and I'll continue refining it as both my teaching and the technology evolve.

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