Examples

One format, many challenges.

The three roles work the same way in every challenge area. This page shows six areas. Each area has an example problem statement, prototypes that teams build, and the effect of the sequence. Use these areas as starting points. A challenge from a participant works better than an example on this page.

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Student-focused

Students with learning differences

Students with dyslexia, dysgraphia, ADHD and other learning differences use AI tools to access education.

Example problem statement

High school students with dysgraphia in our district avoid essay assignments because the physical act of writing is slow and frustrating, making them feel intellectually behind their peers.

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Prototypes teams might build

Voice-to-text mind mapping that turns spoken ideas into visual concept maps
An outlining assistant that organizes messy notes into essay structure
An adaptive reading companion that adjusts complexity and adds context

Why the sequence works here As Designers, teams learn the student experience. As Builders, they make something to show to a person. As Advocates, they state the case for inclusive technology. The structure keeps the focus on student needs, not on the technology.

Student-focused

Student mental health and well-being

Anxiety, stress, social isolation and emotional regulation. These conditions decide whether a student can learn.

Example problem statement

Middle school students experiencing test anxiety struggle to demonstrate their knowledge during high-stakes assessments, despite understanding the material when stress is lower.

Prototypes teams might build

A pre-test grounding routine with personalized calming strategies
A practice environment that simulates test conditions with gradual exposure
A reflection journal that helps students spot their own anxiety patterns

Why the sequence works here Mental health work needs lived experience and careful listening in the Designer phase. In the Builder phase, teams make something that feels safe, not clinical. In the Advocate phase, teams state what the prototype can and cannot do.

Student-focused

Attendance and engagement

Chronic absence. Teams work on the causes, not the symptoms.

Example problem statement

High school students with caregiving responsibilities at home miss school frequently but feel ashamed to explain why, leading to failing grades despite understanding the course material.

Prototypes teams might build

A low-shame way to communicate an absence that routes to actual support
A flexible pathway for completing missed work asynchronously
An early signal that triggers a supportive check-in rather than a penalty

Why the sequence works here The Designer phase moves teams past the attendance number to the student's home circumstances. In the Advocate phase, teams see how a support tool can become surveillance. Teams report this in their findings.

Educator-focused

Teacher professional learning

Teachers develop practice, add tools and stay current. The format does not add work to a full week.

Example problem statement

First-year teachers feel overwhelmed by the gap between theory learned in credential programs and the practical classroom management challenges they face daily.

Prototypes teams might build

A just-in-time coach for classroom management decisions
A scenario simulator for difficult parent conversations
Peer matching that connects new teachers facing the same problems

Why the sequence works here The participants are also the users. This makes the Designer phase fast and the Builder phase honest. Participants know their own schedule, so they reject a tool that does not fit it. In the Advocate phase, teams practice how to ask leadership for time.

Systems & infrastructure

Personalized learning

Students move at their own pace. They keep the rigour and the contact with a teacher.

Example problem statement

Students who master concepts quickly spend weeks bored waiting for peers to catch up, while struggling students fall further behind. Both groups disengage from learning.

Prototypes teams might build

A pacing dashboard that gives students real choice about progression
A peer teaching exchange where advanced students tutor for credit
Formative assessment that adjusts difficulty as it goes

Why the sequence works here Systems problems make teams start with architecture. The Designer phase keeps them on one student first. In the Advocate phase, teams find the institutional limits that decide whether the tool ships.

Systems & infrastructure

College and career readiness

Support for students whose family members have not been to college.

Example problem statement

First-generation college students at our school navigate financial aid, applications and course selection alone, because they can't ask family members who haven't attended college for guidance.

Prototypes teams might build

A patient explainer for financial aid, deadlines and application strategy
Near-peer mentor matching with recent first-gen alumni
A comparison tool weighted by the student's own priorities, not rankings

Why the sequence works here The hidden barriers appear only if a participant has lived them. That is the purpose of the Designer phase. The findings usually cover trust and accuracy. A wrong answer about FAFSA is worse than no answer.

Adapting it

What to keep, what to change.

You can adapt most of the format. This list shows which parts to keep and which parts to change.

Keep

The sequence. Designer, then Builder, then Advocate. Teams that jump right into building can miss the real problem behind the problem.
Human first, AI second. In every phase, participants state their own view before they open a tool.
Writing the problem statement twice. Teams learn from the difference between the two versions.
Showing it to someone. A prototype is not tested until a person reacts to it.
Reporting what didn't work. Findings, not verdicts.
Weighing AI against people at the close. Teams say which boosts earned their place and which did not.

Change freely

The challenge area. Use any topic that your participants care about, inside or outside a classroom.
Length. Two to three hours. Protect the build time and the close, and compress the findings round instead.
Whether the challenge is pre-set. A pre-set challenge saves twenty minutes. A self-chosen challenge gives participants more ownership.
Who leads the feedback. Look for people already in the room who work closest to the problem, and ask them to respond to what teams report.
Examples and language. Use the vocabulary of your own context.

Bring your own challenge.

The examples above are illustrations. The best sessions are built around the challenges the participants bring with them into the AI Flash Lab.

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