5-Minute Lesson: Teaching Problem Framing with AI

The fastest way to help students think more deeply about problems—starting tomorrow.

You have 47 minutes left in your planning period. You want to try something new with your students, but you don't have time to redesign your entire curriculum or learn a complicated new technology. You just need one small, manageable thing that will make tomorrow's class better.

This is that thing.

This 5-minute activity teaches students that how you frame a problem determines which solutions become visible. It works in any subject. It requires almost no preparation. And it creates a discussion so rich that you'll use it again and again.

Here's everything you need.

What This Lesson Does

Students see a list of questions generated by AI about a problem related to your current unit. They discuss which questions change their thinking. That's it.

But in those 5 minutes, students experience something most of them have never experienced: watching their understanding of a problem shift because someone asked a different question.

They're not learning about AI. They're learning that expert problem-solvers ask systematic questions before jumping to solutions. The AI just makes that invisible process visible.

Before Class: 3 Minutes of Prep

Step 1: Go to AI_App_Ideator and submit a problem observation related to your current lesson.

For example:

• English: "I noticed that this editorial about school start times makes claims about student health without citing medical research."

• Social Studies: "Our town has people experiencing homelessness even though we have a homeless shelter."

• Science: "Local stream water quality varies significantly by location."

• Math: "Students struggle to know which mathematical approach to use for real-world optimization problems."

Step 2: The AI will generate questions. Copy them. You'll see questions that follow a pattern:

• What specific frustrations or experiences...?

• What positive aspects exist that should be preserved...?

• How does [current process] work, and what makes it difficult...?

• Who else is affected by...?

• What would an ideal solution look like...?

Step 3: Paste these questions into a slide or handout. Remove any references to "app development" if that would confuse your students. Just show the questions.

Done. You're ready.

During Class: 5 Minutes

Minute 1: Display the questions

Show students the list without context. Don't explain where it came from yet. Just say: "Here are some questions about [topic we're studying]. Read them quietly."

Minutes 2-3: Partner discussion

"Talk with your partner: Which of these questions changes how you think about this problem? Why?"

Students will naturally start discussing which questions surprised them, which ones they hadn't considered, and which ones reveal complexity they'd missed.

Minutes 3-5: Whole class share-out

Ask 2-3 pairs to share which question changed their thinking and why.

Listen for students saying things like:

• "I was only thinking about [one aspect], but this question made me realize..."

• "I assumed [something], but this question challenges that..."

• "I hadn't thought about [stakeholder group] before..."

Final 30 seconds:

"Notice what just happened. Good problem-solvers ask systematic questions before jumping to solutions. These questions came from AI, but you can learn to ask questions like this yourself."

Done. Class continues with whatever you'd planned next.

What Makes This Work: Problem Framing with AI

It's Concrete, Not Abstract

Most metacognition instruction sounds like: "Think about your thinking." Students nod politely and have no idea what you mean.

This lesson gives them something concrete: a list of specific questions. They can see the questions. They can compare them to their own initial thoughts. They can discuss which questions open new pathways.

That's problem framing with AI. It's metacognition happening, not metacognition being talked about.

It Reveals Invisible Expert Thinking

When you approach a problem, you automatically ask systematic questions: What's the human experience here? What's working? What's difficult? Who's affected? What would ideal look like?

Your students don't see you doing this. It happens invisibly in your expert brain.

The AI makes that process visible. Students see the questioning pattern and can observe, discuss, and eventually internalize it.

Problem Framing with AI Works in Any Subject

The questioning pattern is universal:

• English: What frustrations do readers experience with unsourced claims? What positive aspects of open discourse should we preserve?

• Social Studies: What specific challenges do unhoused individuals face? Who else is affected by homelessness in our community?

• Science: What makes water quality monitoring difficult? What would ideal water quality look like for different uses?

• Math: What frustrations do students experience when choosing optimization approaches? What makes this decision-making process difficult?

  
  

Same pattern. Different content. Every subject benefits.

It Creates Natural Discussion

You don't need to force a discussion. The questions themselves spark curiosity:

• "Why would we ask about positive aspects when we're trying to fix a problem?"

• "I never thought about [stakeholder group]—how does this affect them?"

• "What does 'ideal' even mean in this situation?"

  
  

Students generate the discussion because the questions genuinely make them think differently.

Student Handout Template

You can project this or print it. Either works.

Problem Framing Discussion

The Problem: [One sentence describing the observation]

Questions to Explore:

1. [Question about specific frustrations/experiences]

2. [Question about positive aspects to preserve]

3. [Question about current processes and challenges]

4. [Question about other affected stakeholders]

5. [Question about ideal outcomes]

Discussion Prompt:

Which of these questions changes how you think about this problem? Why?

Reflection:

What's one question you would now ask about this problem that you wouldn't have thought to ask before?

Facilitation Tips

If Students Say "None of These Questions Change My Thinking"

Ask: "Which question would lead to the most interesting research? Why?"

Or: "If you could only investigate one of these questions, which would teach you the most?"

The goal isn't for students to admit they were wrong. It's for them to recognize that different questions open different pathways.

If Discussion Stalls

Try: "What pattern do you notice in these questions? Why might they be ordered this way?"

Students will notice the movement from specific frustrations to ideal outcomes, from current state to desired state, from individual to stakeholder perspectives.

If Students Ask Where the Questions Came From

Perfect opportunity: "These came from an AI tool that models how experts approach complex problems. Notice how it doesn't jump straight to solutions—it asks systematic questions first. That's what good problem-solvers do."

If You Have More Than 5 Minutes

Extend with: "Now generate your own question about this problem using the same pattern. What would you ask?"

Students practice creating questions that explore frustrations, strengths, processes, stakeholders, or ideals.

Assessment: Exit Ticket

Option 1 (Simplest):

"Write down one question you would now ask about [topic] that you wouldn't have thought to ask before this lesson."

Look for: Questions that show students are thinking about stakeholder perspectives, underlying assumptions, or systemic complexity.

Option 2 (More Rigorous):

"Pick one question from today's list. Explain why it changes how you think about this problem."

Look for: Evidence that students recognize how questions reveal assumptions, introduce perspectives, or shift understanding.

Option 3 (Metacognitive):

"What pattern did you notice in today's questions? How could you use that pattern when you face your own problems?"

Look for: Students identifying the systematic questioning approach and considering how to apply it independently.

Real Example: English Class

The Setup

Teacher is working on argument analysis. Students are reading editorials about standardized testing.

The Observation Submitted to AI

"This author claims standardized tests harm students but offers no alternative assessment method."

Questions AI Generated

1. What specific frustrations do you experience when you encounter arguments that critique something without proposing solutions?

2. What positive aspects exist in how educational debates are currently conducted that we should preserve while addressing gaps in argumentation?

3. How do you currently evaluate arguments that only present one side, and what makes this evaluation process difficult?

4. Who else might struggle with similar challenges when trying to assess the completeness of persuasive writing?

5. What would an ideal persuasive argument look like that addresses both problems and solutions?

What Happened in Class

Teacher displayed questions. Students discussed in pairs.

One student said: "I was just thinking 'this argument is bad because it doesn't give solutions,' but question 2 made me realize—maybe focusing on the problem first IS valuable. Like, sometimes we need to agree there's a problem before we debate solutions."

Another student: "Question 4 made me think about who reads these editorials. Teachers? Parents? Policymakers? They'd all evaluate this argument differently."

The 5-minute activity led to a much richer discussion about rhetorical choices, audience awareness, and the purpose of critique versus proposal arguments.

The teacher didn't change her lesson plan. She just added 5 minutes that made the rest of the lesson more effective because students were thinking more deeply.

Common Questions

Q: Do students need to know this came from AI?

Not necessarily. You can say "Here are some expert-level questions about our topic" and proceed. The AI is just the tool that made expert questioning visible. Whether you attribute it to AI depends on your teaching goals.

Q: What if the AI's questions don't perfectly fit my lesson?

Edit them. Remove questions that don't work. Reword questions to better match your students' vocabulary. Add a question the AI missed. The AI provides a starting point, not a script.

Q: Can I use this multiple times with the same class?

Absolutely. Once students understand the questioning pattern, you can use it throughout the year. Eventually students will anticipate the pattern: "You're going to ask about stakeholders, right?" That's when you know they've internalized expert questioning.

Q: Is 5 minutes really enough?

For the first time, yes. You want students to experience the shift in thinking without overwhelming them. Once they've done this a few times, you can extend: have them generate their own questions, compare AI questions to their initial questions, or use the questions to guide research.

Q: What if my students need more scaffolding?

Start with just 2-3 questions instead of all five. Or guide the discussion more: "Look at question 3. What assumption does this question challenge?"

Next Steps

If This Worked Well

Try the 30-minute version where students submit their own problem observations and compare AI questions to their initial thinking. (See: "Metacognitive Comparison Mini-Lesson" in the Teacher's Guide)

Or use this format weekly as a discussion starter for any complex topic in your curriculum.

If You Want to Go Deeper

Explore how entrepreneur vs. consultant perspectives generate different questions about the same problem. (See: "Entrepreneur vs. Consultant Mindsets Lesson Plan")

Or build a unit where students learn to generate systematic questions independently using the AI's pattern as a model.

If You Want Support

Visit Romney for a coffeeshop coaching session. Bring your curriculum and specific challenges. We'll generate custom questions for your units while you drink coffee and enjoy our small-town Appalachian hospitality. We're serious about the face-to-face support—this isn't a corporate webinar. It's neighbors helping neighbors teach better.

The Real Point

This 5-minute lesson isn't really about AI. It's about making invisible thinking visible.

Your students watch you solve problems all the time. They see you reframe challenging situations, ask clarifying questions, and consider multiple perspectives. But they don't see HOW you do it because expert thinking happens invisibly.

This lesson makes one aspect of expert thinking concrete: systematic questioning reveals complexity that isn't immediately visible.

Students experience that shift. They feel their understanding deepen when someone asks a question they hadn't considered. They see that problem-framing matters as much as problem-solving.

That's a lesson worth 5 minutes. And once you've done it once, you'll find reasons to use it again and again.