Personalized AI education · Grades 6–12
AI education that starts with the student.
We're building personalized AI learning around each student's interests and current understanding. It helps them explore what AI can do, question its answers, and make their own decisions.
In development Meet the team and explore the approach we're building.
One way in
How could AI help sort photos from a stream survey, and what would you still have to check yourself?
Example starting questions. Illustrative, not the live product.
Why the starting point matters
The same starting lesson isn't the right starting point for every student.
Students arrive with different interests, different experience with AI, and different levels of confidence. Two students in the same class can need very different first lessons.
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Using AI often isn't the same as understanding it.
A student can use a chatbot every day and still not know when to doubt its answers.
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Avoiding AI isn't the same as being unable to learn it.
Some students stay away because they're cautious, or because they were told not to use it. That says nothing about what they can do.
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One example won't speak to every student.
A student who loves architecture and a student who loves music may each need a different way in.
We think the place to begin is where each student already is. That's why we're building Chameleon around personalization.
Our approach
Start with the student. Then keep adjusting.
This is the loop we're building. Each step feeds the next one.
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Understand the starting point
A short starting-point assessment looks at a student's interests, what they currently understand about AI, and what they can already do.
A starting point, not a label.
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Shape a relevant lesson
That picture guides the lesson: useful examples, a suitable level of challenge, and real chances to take part.
Format is about choice and engagement, not sorting students into learning styles.
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Check understanding and refine
Students explain, question, verify, or improve something. What we learn from that informs the next lesson.
Where this stands. We're developing and testing this approach case by case, with a person reviewing each step, before we build out the full system.
Personalization, made concrete
Two students. Two different first lessons.
Same goal for both: learn that an AI's answer can sound right and still need checking.
Has tried a chatbot a few times. Loses interest during long explanations and does best when things keep moving.
Three quick rounds. Ask an AI a basketball question, guess whether the answer is right, then check it. Keep score.
Tell a classmate one thing the AI got right, one thing it got wrong, and how they found out.
Two example students, shown to make the idea concrete. The difference is in pacing, examples, and format, not in sorting students into types. This isn't a controlled comparison, and these aren't results from students.
What students could explore
Using AI isn't the same as understanding it.
These are the subject areas we intend to cover, described by what students would practice. No prior AI knowledge or coding is assumed.
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Understand
Where AI shows up in everyday life, what data and models are, and how a generated answer differs from verified information.
For example: explain why a chatbot can sound certain and still be wrong.
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Use
Ask clear questions, add relevant context, and improve a result over several tries.
For example: turn a vague request into a clear one, then compare the two results.
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Question
Spot errors, check evidence, recognize limits, and decide when not to use AI.
For example: find the mistake in an AI answer and show the source that proves it.
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Take responsibility
Privacy, consent, fairness, permitted use, and the fact that a person stays accountable for the work.
For example: decide what's okay to share with an AI tool, and say when you used one.
These are intended subject areas, not finished courses. We're organizing the AI subject matter in a library that's kept separate from our learning-science and assessment work. More technical depth is planned as an option for students who want it. It isn't the starting point, and not every student is headed for a coding track.
Learn with AI. Keep doing the thinking.
For schools
Help shape how this fits your school.
We're looking for educators who want to think this through with us. Tell us about your students and your schedule, and we'll share the approach and the examples we have so far.
What a demo is right now: a conversation with the team, a walk through the approach, and a look at the examples we have. It isn't access to a finished platform.
Settings we'd like to talk through
- A class period
- An advisory block
- An after-school program
These are starting points for a conversation, not packaged programs. We'd like to hear what would work in your building.
People and approach
Who's building Chameleon.
Chameleon brings together work with schools and research on how students learn. When you request a demo, you talk with us directly.
Matthew Leck
Co-founderMatthew is a senior at the University of Virginia pursuing a B.S. in Finance and Entrepreneurship. He has worked in investment banking and has built startups in esports and AI.
Matthew on LinkedInMaya Rose, Ph.D.
Co-founderMaya has spent more than a decade building game-based cognitive training and measuring its effect on cognitive, behavioral, and academic outcomes. She holds a Ph.D. in Educational Psychology from the CUNY Graduate Center, specializing in learning sciences and development.
Maya on LinkedInFAQ
Questions schools ask first.
Who is Chameleon for?
We're building it for students in grades 6–12. This site is for the adults around them: school leaders, curriculum directors, teachers, and parents.
Do students need to know AI or how to code already?
No. The beginner entry point we're designing assumes no prior knowledge of AI and no coding.
Is the product available now?
Not yet. Chameleon is in development. Requesting a demo starts a conversation about the approach and the examples we have so far. It doesn't give instant access to a platform.
Is this a homework-answering chatbot?
No. The focus is learning about AI and practicing thoughtful use of it, including knowing when not to use it.
What is the starting-point assessment?
A short set of questions and tasks about a student's interests and what they currently understand and can do with AI. It's a starting point, not a label. It isn't an intelligence test or a validated psychological diagnostic, and it doesn't sort students into fixed types.
Request a demo
Tell us about your students.
Share a few details and we'll reply to set up a conversation about the approach and a possible pilot.
This form is for adults. If you're a student, please ask a teacher or parent to get in touch.
One more step: send your request.
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