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Every few years, a new technology enters schools. beamed lessons from the best teachers into classrooms. gave students access to a wealth of information, right at their fingertips. Interactive whiteboards, tablets and Chromebooks were sold as the .

Now, it is artificial intelligence. And educators must ask: What does this innovation help students learn that they couldn’t without it?

Unlike previous classroom technologies, generative AI can perform the very thinking that many lessons are designed to develop. It can write essays, solve problems, summarize readings and produce analyses that students are meant to do themselves. 

 have now issued AI guidance for schools. Much of it centers on data privacy, human oversight and teacher training, rather than whether a given use of AI is developmentally appropriate for a child.

That leaves the question most states have been skipping: What thinking should students do themselves? To answer that, it helps to look backward. In 1958, psychologist B.F. Skinner designed a  around a simple principle: Students could not move to the next problem until they had produced the correct response themselves. The machine provided immediate feedback, but it never completed the work for the student.

Whatever one thinks of Skinner’s broader work, he understood that students learn by responding to problems, answering questions, making mistakes, receiving feedback and trying again. The student must do the thinking.

But today, generative AI can complete the assignment without the student.

This is referred to as cognitive offloading, handing one’s thinking off to an external system. A  involving about 1,000 high school math students tested this, comparing two versions of an AI chatbot. One answered questions outright. The other offered hints and guidance, but not the answer. Students with the first chatbot performed worse on later exams than those who did not use AI at all. Students who received only hints and guidance performed as well as the no-AI group. One tool did the thinking for students; the other made them think first.

The rule that should anchor any school AI framework is simple. Its role should expand only as a child’s own foundation grows.

In kindergarten through second grade, students are building the skills everything else depends on, including sounding out words, forming letters and developing number sense. How well a child masters these literacy skills  in third and fourth grade, and  is indicative of math performance years later.

Children build those skills by doing the work; such as sounding out words, making errors and trying again. If AI gives students the answer, that productive struggle never happens, and the skill never truly forms.  shows that the more students hand a task to a machine, the less able they become to do it themselves. 

So, in K-2, AI belongs only in the teacher’s hands. There, it can help educators in planning phonics instruction and generating practice at each student’s level.

Third grade marks the shift from learning to read to reading to learn. The same shift happens in math and writing, where the foundational skills become tools for building arguments, drawing inferences and working through problems. That’s what makes a different kind of AI use possible. 

In grades three through five, students should use AI only after they’ve done an assignment themselves, and only under a teacher’s direction. A teacher might take a paragraph a student has written, generate an AI version, and have the class pick out errors and find weak reasoning, wrong facts and claims that do not hold up.

Working with flawed examples is one of the oldest ways to teach analysis, and AI produces an endless supply of them. A  found that when students critique AI-generated work with a teacher’s guidance, their critical thinking improves. The same research points the other way, too; the more readily people trust AI’s output, the less they think for themselves.

By middle school, AI should become something students should study, not just something they use. This is the age when the judgment to evaluate information . Every eighth grader should be able to explain how these technologies work, where they fail and why they can produce convincing but wrong text — the beginning of true . Students’ own work should still come first, with AI used afterward and under a teacher’s direction.

By high school, students who can read critically, write clearly and work through problems independently can get real value from AI. In writing, they can first draft an essay, then use AI to help identify gaps or missing arguments. The students would then weigh the feedback to decide whether to follow the tool’s suggestions. AI could also work as a tutor, helping students, say, catch up in algebra or progress beyond grade level, giving feedback faster than a teacher with 25 students can.

High schoolers are also entering a world where AI is embedded in most professional fields, and they need to learn to use it well. That means having the capacity to think, write and reason without it, direct the tool and catch its errors. Those skills are the prerequisite to AI readiness. 

One principle should hold across all grades: Keep assessments AI-free. Tests should measure what the student can do, not what a chatbot knows.

Technology has never been the goal of education. Learning is. Schools exist to help students develop knowledge and skills they couldn’t develop on their own, and every technology should earn its place by helping accomplish that. AI may become one of the most powerful instructional tools schools have ever adopted. But its success shouldn’t be measured by what it can do. It should be measured by what students can do as a result of it.

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