High School Inquiry-Based Learning × Generative AI: Practical Steps to Empower Students [The N-E.X.T. High School Era]

This is Hamamoto from TIMEWELL.

High school inquiry-based learning and generative AI. On the policy side of this combination, I have written in my explainer on the N-E.X.T. High School vision and its AI-education companion piece. This article is the practical installment. It answers the question of what you actually do in Monday's class.

Let me be clear about where I stand up front: I am in the camp that says generative AI should be part of inquiry-based learning. But there is a condition. Bring AI in as a time-saver for look-it-up learning and inquiry will reliably degrade. Only when you bring AI in as "a tool for students to create something" does inquiry accelerate. From my experience watching several hundred adults through supporting companies with AI adoption, this dividing line has nothing to do with age.

The real reason offloading happens is in the design of the question

I often hear the worry that "students hand in reports they had ChatGPT write." It tends to get blamed on students' ethics, but my read is different. The root cause is setting tasks that AI can answer in a single shot.

"Research the causes of global warming and its countermeasures" is something AI answers in 30 seconds. But questions like these cannot be completed by AI alone:

• Investigate the vacancy rate of shops on the shopping street along your route to school, and draw up a plan to revive one of them (requires primary information)
• Verify the flow of visitors at the school festival with data, and compare improvement proposals against actual measurements (requires data you gather yourself)
• Interview three local companies, and argue which jobs AI will change and which it will not, tied to your own career path (requires a stance of your own)

What they share is that primary information and a stance of one's own are indispensable. With this design, generative AI's role shifts naturally from "handing out the answer" to "preparation for research, sounding out hypotheses, and helping produce outputs." The "ability to pose one's own questions" that the N-E.X.T. High School vision talks about actually begins with the question design on the teacher's side, the side setting the task.

A quick reference: where generative AI fits in the inquiry process

Following the standard process of the period for integrated inquiry, here is where AI fits and what "students should be responsible for."

Stage	Fine to leave to AI	What the student should own
Theme setting	Sounding out how to put interests into words, breaking down the question, researching prior examples	Choosing the final question and articulating "why I am doing this"
Information gathering	Preliminary research for searches, summarizing materials, generating interview question drafts	Obtaining primary information (interviews, experiments, surveys), checking whether information is true
Organizing and analyzing	Aggregating and visualizing data, presenting counterarguments and alternative interpretations	Judging which interpretation to adopt, revising the hypothesis
Wrapping up and presenting	Slide structure drafts, polishing prose, prototyping apps via code generation	Deciding the argument, presenting, handling Q&A

Of these, the one we find the most value in is the last, "prototyping apps via code generation." Today's generative AI can build websites and simple apps from natural-language instructions. Even a high school student with no programming experience can turn a solution born from their own question into "something that works." Inquiry that used to end at a poster presentation can now end in a product, and I think that is a quiet revolution for education.

Practical steps: start small, and have them see it through

Here is how to actually run this at a school, in five steps drawn from our hands-on experience.

1. Put your approach on a single page. Share a guideline with students that is as simple as, "You may use AI for research, sounding out ideas, and production, but primary information and the final judgment are yours." Showing examples of recommended uses works better than listing prohibitions.
2. Have a core team of teachers experience it first. Before any all-staff training, have two or three people from the inquiry team and the information-studies department use AI to the hilt in preparing their own classes. The internal credibility this builds is on another level.
3. Refine questions into "a form AI cannot complete on its own." Revisit theme setting using the primary-information and stance-taking conditions described above. It is worth spending 30% of your time here.
4. At the interim presentation, look at the "dialogue log with AI," too. Make the process an object of evaluation, not just the deliverable: what questions students posed to AI and how they revised the output. This curbs offloading and makes thinking visible at the same time.
5. In the end, have them build it through to something that works. Rather than stopping at a report, bring it down to a form a third party can touch, such as a web page, a prototype app, or a data visualization. The experience of "my own question took shape" is the core of empowering students.

Reaching this fifth step with only in-house resources is, frankly, a high bar. For how to use code-generation AI, debugging when things get stuck, and quality control of the deliverable, having someone who does AI development in practice alongside you is reliably faster. The N-E.X.T. High School vision itself lists the use of specialized inquiry-support teams and external talent among the activities eligible for grants[^1].

Empowering students is the real objective

Finally, let me write about why we work in this area.

TIMEWELL's WARP was originally a hands-on AI support program for companies. Having taught several hundred adults to use AI, what I keenly feel is that changing one's view of learning after becoming an adult is genuinely hard. Prompting someone who has spent 20 years trained to "produce the right answer quickly" to shift to a way of working that is "pose a question, try, and fix" takes time and energy.

High school students are different. A student who passes even once through posing a question and the experience of giving it shape with AI, while still in high school, can stand on the side of "creating something with AI" whether they go on to further study or into work. The "student-centered" education MEXT drew in the grand design[^1] is, in our words, empowering students. The skill of AI-driven development is a means to that end; the goal is for students to become able to expand their own possibilities themselves.

It is with this thinking that we offer our WARP program for schools and educational institutions. From design support for inquiry-based learning to walking alongside students until they have built a product through to the end, we design it around each school's situation. If your school is considering applying to become a reform pilot site, or if you are a teacher wrestling with how to connect inquiry and AI, please reach out, even if it is just to compare notes.

Summary

• The root cause of offloading is not the students but the design of the question. Change it to a question where primary information and taking a stance are indispensable
• AI can be used at every stage of inquiry, but decide in advance where the line falls between "what to leave to AI" and "what the student is responsible for"
• Thanks to code-generation AI, we have entered an era where inquiry can end in "a product that works"
• Start the practice small. Five steps: a one-page approach, a core team, refining the question, evaluating the dialogue log, and the experience of seeing it through
• The goal is not AI skills but empowering students. The experience of posing a question and giving it shape expands students' possibilities

---

References

[^1]: MEXT, "Basic Policy on High School Education Reform (Grand Design): The 'N-E.X.T. High School Vision' Toward 2040" (February 13, 2026)

Related Articles

• What Is the N-E.X.T. High School Vision? A Clear Guide to MEXT's Grand Design for High School Reform
• What Are the "Abilities AI Cannot Replace"? How AI Education in High Schools Is Changing
• What Are Reform Pilot Schools? The Three Types and Trends Among the 75 Selected Schools
• What Is an Advanced Essential Worker? Strengthening Specialized High Schools