Beyond AI as a Tool: Helping Students Learn About AI, Not Just With It

AI Engagement Looks Different in Every Subject Area 

For a while now, we have framed AI literacy instruction in terms of technical knowledge about AI systems, prompting, and ethical discernment. While this framing is a necessary step towards effective implementation in our schools, it also implicitly positions AI as a general-purpose tool with one set of rules. Once you learn those rules, you are ready to use AI in any context relevant to your work. 

Over the past year, I have worked with districts to complicate and refine this approach. What if, instead of treating AI as a hammer, we treated it as a Swiss Army knife? What if we adapted AI literacy instruction to fit the learning goals of particular contexts? In other words, what if we developed a discipline-specific approach to AI literacy? 

When AI Becomes Invisible, Learning Can Too 

The advent of generative AI created a need in school districts around the country. If our students are using AI outside of school to complete assignments, then we need to provide safe and transparent access to AI inside the classroom, where we can teach students to use it appropriately. In addition, we can use these access points to drive academic instruction by creating interactive spaces where students can work on discipline-specific content. 

In practice, however, teachers are using AI primarily to provide these interactive spaces, lacking the time and curricular space to do deeper AI literacy work. The side effect of this approach is that it renders the operation of AI—both its capabilities and its limitations—relatively invisible to students. AI is implicitly positioned as an authoritative expert, providing information and feedback. 

Shifting from "Using AI" to "Studying AI" 

Another approach to AI literacy and implementation draws on the rich context of individual courses. Admittedly, this approach requires some AI experimentation by teachers within their disciplinary context, but I would argue that this need will help us create more-focused, teacher-facing AI literacy trainings and workshops. 

In the spring of 2025, I piloted this approach with a group of teachers in a discipline-specific AI literacy workshop focused on 6–12 ELA instruction. In the morning, we explored AI operations, disciplinary literacy, and the ELA context that can frame engagements with AI. In the afternoon, teachers developed activities, lessons, and units that used AI as an object of study and a tool for inquiry—work that aligned with disciplinary standards and helped students build disciplinary literacy. 

Teaching Students to Critique AI 

What does this look like in practice? Let's start with AI as an object of study. By this, I mean asking students to critique an AI output. In most existing versions of this assignment, an AI output is dropped into an activity or unit, and students engage with it by critiquing elements of style or sourcing procedures. But what if we used this experience to work towards specific academic standards and objectives? 

Critiquing an AI output in a history class hinges on preexisting knowledge about a person, events, or controversy. I call this "knowledge asymmetry." Without this background knowledge, students will more readily defer to confident AI responses. Then, students need to practice reading, analyzing, and evaluating historical texts and interpretations. While this may seem like a lot of building and instruction prior to AI use, what teachers are discovering is that AI critique can function as a feedback loop. Students bring knowledge to AI outputs and refine that knowledge through critical engagement. 

Productive Uses of AI That Support Learning 

The key aspect of this work is that AI literacy becomes a dynamic topic of conversation inside classrooms. AI engagement helps build foundational knowledge and skills—not through an invisible learning partner, but through the process of critique. The consequence of this approach is a repositioning of the learner as an active agent who constructs knowledge through reflection, metacognition, and disciplinary engagement. 

In other words, the work of AI literacy is embedded in the work of becoming an expert in a particular field. It just so happens that this approach aligns with ODE's recent publication, Integrating AI into Content-Area Instruction. To create this document, teachers from ten different content areas came together and mapped their learning standards onto specific AI engagements. The majority focus on AI as an object of study and critique, but others lean into AI as a tool for inquiry. Given the complexity of that work, we will have to save that other modality for a follow-up blog. 

Moving from Policy to Guidance 

All Ohio districts now have AI policies on the books. We spent the past year developing these documents to scaffold district-level implementation. This year's challenge is to convert those policy statements into concrete action. While districts grapple with community challenges to technology use in schools, one thing remains certain: AI will continue to impact student learning, and students need instruction about AI use that goes beyond stoplight models and interactive spaces. Students need to see in real time how and why AI misrepresents historical materials, how AI-assisted research truncates the complexity of academic conversations, and how AI writing is formulaic—stealing from students the opportunity to surface their own thinking. Content-area instructors are the only ones in the position to deliver that instruction.  

Learn More 

At the ESC, we are excited to work with you to develop AI literacy initiatives that fit your technology needs and objectives. I facilitate the Central Ohio AI Network. We meet this fall on September 8, October 15, and November 12. Email nicolas.potkalitsky@escco.org to get more information and to be added to the mailing list. We plan on offering discipline-specific AI literacy training throughout the year. Reach out if you want to bring this work to your district. 

The ESC will be hosting a Digital Wellness workshop on September 30th. Learn more and register for that event here.

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Nick Potkalitsky serves as the AI Specialist at the Educational Service Center of Central Ohio, where his extensive background in language, learning, and pedagogy informs his approach to educational technology integration. Holding a BA in Classics, M.Ed., and Ph.D. in English, Nick has taught across diverse environments—Latin in Cleveland public schools, Montessori middle school in Hudson, college composition, and ELA curriculum development at a Dayton private school. These experiences shaped his understanding of how students learn and communicate across age groups and contexts. 

As a recognized voice in AI implementation, Nick collaborates with educators nationally on thoughtful integration of artificial intelligence in schools. He advocates discipline-specific approaches to AI literacy that strengthen fundamental academic skills like critical analysis, clear communication, and thoughtful problem-solving within existing curricular contexts. 

Nick lives in Dublin with his wife and two children, ages 8 and 13. When not working with educators, he explores music through guitar and sitar.