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How to encourage smarter AI use in the classroom

How to encourage smarter AI use in the classroom

Techonolgy Reviewby Techonolgy Review
2 September 2026
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This article is from Making AI Work, MIT Technology Review’s limited-run newsletter examining how to apply LLMs across industries. To receive it in your inbox, sign up here.

Chatbots took many schools by surprise upon their release a few years ago. Suddenly, students carried an app in their phones that could magically answer almost any homework question or spin up an essay in seconds. Of course, teachers can often tell when a student is using AI—models make mistakes that most humans don’t, and some teachers say that AI-generated text has simple giveaways like too many em dashes. 

Nevertheless, the generative AI boom increased the burden on teachers, who were already working long hours to plan lessons, make homework assignments, and grade exams, and now needed to adapt to a new technology. For many, it still feels like there’s no clear path forward. Organizations ranging from OpenAI to UNESCO encourage AI use in the classroom, but many teachers feel confused about how exactly to handle it. 

Case study

Cheshire Academy is a private boarding and day school in Connecticut with about 400 students in grades 9 through 12. Administrators there don’t force instructors to use AI at all, though the school’s librarian and technology coordinator George Aiello claims the “vast majority” of instructors use it in some way. The educators there are trying a patchwork of programs, including general-purpose chatbots like ChatGPT and Perplexity as well as more specialized tools like MagicSchool, an AI-powered platform meant specifically for educators.

That patchwork approach is partly because the school, on the advice of consultants, opted to train its staff on general techniques for how to use AI instead of prescribing certain tech. The staff training covered topics like how to craft useful prompts but also stressed the technology’s limits, highlighting its potential for generating incorrect and biased responses. 

Now, teachers there often use generative AI to prepare class materials. This means asking the AI of their choice for help with planning lessons or creating grading rubrics. Some even want to use it to help them give feedback to students, though concerns over quality, personalization, and privacy have prevented any of them from doing that just yet.

Others, like Miriam Przybyla-Baum, who teaches French, don’t use AI themselves but do address it with their teaching. Przybyla-Baum says she doesn’t really need AI’s help since she’s built up plenty of classroom materials across nearly 30 years of teaching. But she started seeing students try to use AI-powered tools like Google Translate to take shortcuts on their assignments years before ChatGPT’s launch. 

She’s developed a system to make students reflect on how AI can and can’t teach language skills. In one assignment, students let a large language model (LLM) edit their homework. Then, they go through the edits and decide which ones were correct and which ones removed their voice. In another, she has students anonymously grade each other’s AI-assisted assignments, making annotations as to which parts they think are AI-assisted.

Cheshire Academy is continuing to experiment with how AI can be harnessed productively in the classroom. The school is piloting a program in which students create media and lead discussions regarding healthy AI use. This program, which they call a “Student AI Council,” aims to push students to reflect on how AI should and shouldn’t be used to benefit the community around them.

The academy as a whole has since adopted similar techniques to those Przybyla-Baum introduced to make students reflect on their own use of AI. Assignments are now labelled like traffic lights, with green meaning AI is fully allowed and red banning any AI use. Yellow, then, lets the teacher permit some tools while banning the rest, like allowing students to use spell-check but not message a chatbot.

The tool

As generative AI was becoming mainstream, Cheshire Academy previewed MagicSchool to its staff. 

For many, MagicSchool’s main strength seems to lie in the sheer amount of offerings it provides in one package. It can generate questions and assignments of all kinds, from quizzes to worksheets, across many subjects and grade levels. It has a specialized grading rubric generator, which outputs a ready-to-go table that teachers can use to score assignments. It can make presentations and lesson plans and administrative reports, too. 

All of this is done through a single platform where educators enter specific prompts tailored for each task. For example, to make an assignment, a teacher can specify the students’ grade level, number of questions, the types of questions (such as multiple choice or short answer), and more, and include documents to align the questions with. 

Not every teacher feels comfortable using LLMs to generate student-facing text, whether because they don’t think an AI can produce effective teaching materials or helpful feedback, or because they’re concerned about accuracy. MagicSchool, which has free and paid versions, does offer tools on its platform for other tasks like lesson planning. If teachers want unlimited access and complete records in the system, though, they need to pay just under $100 per year for an individual plan. Alternatively, many of the general-purpose generative AI tools (think the chatbots on offer from Anthropic, Google, OpenAI, and more) seem suited to administrative tasks, as well, attested by the fact that many of the teachers at Cheshire Academy use those instead. Some of these companies are even rolling out features tailored for schools, to mixed results.

How to apply this

  • Meet students where they’re at. Students will be tempted to try AI, and there’s no way to entirely police this for take-home assignments. The internet and social media can spread a lot of misinformation as to what AI can and can’t do, and it’s critical to counter these narratives and teach healthy strategies and relationships.
  • Model best practices. AI is very good at automating tasks, but it struggles with precision and voice. Keep this in mind, especially when generating any text that anyone else may see. Impressionable students who see those in authority using AI in a lazy way could internalize this as an excuse to cut corners in their own work.
  • Refine and replace. AI is great for brainstorming lesson plans and extra problem sets, especially for teachers early in their careers who don’t have a big problem bank already built up. However, because it can make mistakes (called hallucinations), using it for final drafts can result in assignments that confuse students and impair learning. Be sure to check every citation, equation, and statement an LLM makes.

Sign up for Making AI Work, MIT Technology Review’s limited-run newsletter examining how to apply LLMs across healthcare, climate tech, education, and more.

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