Ages 13–17 In person or online

Designing for People

UX & UI design for ages 13–17

Ten sessions that take a teenager from "apps just exist" to having designed, tested and presented a product of their own. They learn to tell how something works apart from how it looks, build real screens in Figma, interview actual users, and use AI the way professionals do — as a first draft they are responsible for judging.

Ages
13–17
Length
10 sessions · 2 hours each
Group size
Up to 16 · 12 online
Prerequisites
None — no design or coding

Why this age

Teenagers are the most fluent users of digital products alive and the least often asked what they think of them. They already know what's annoying — this course gives them the method and the vocabulary to turn that into design.

It also lands at the age where career questions turn serious. Most students have never heard that deciding how things work is a profession.

And it teaches AI judgment at exactly the moment they're starting to use these tools unsupervised.

What they leave with

A finished product

Named, with a logo, a clickable prototype and a flow that's been tested on a real person.

A case study

Problem, research, design, what changed after testing — ready for a portfolio or a university application.

Working Figma skills

Frames, auto-layout, components and prototyping — built by hand, not generated.

Research habits

How to interview someone without leading them, and how to watch a person struggle without rescuing them.

AI judgment

An annotated record of where AI helped and where it was confidently wrong.

A design journal

Twenty entries showing how their eye developed over ten weeks.

How the course runs

Three acts. Roughly 30 minutes of teaching and 80 minutes of doing per session, closing with ten minutes of sharing work. One project runs from session seven to the end.

Act one · Sessions 1–3 Learning to see
01UX or UI? Same app, two failures

The difference shown rather than defined — one product that looked right but worked wrong, one that worked but hid its buttons. Students write the definition themselves, then hunt three annoyances of their own and sort each one.

AI — ask a chatbot to explain UX, then critique the answer against what they just found.
02You already have taste — here's the vocabulary

Rapid good-versus-bad pairs: sign-up forms, checkouts, game menus. Vote, then justify in one sentence. Hierarchy, affordance, feedback and friction enter the room, and each student annotates a bad screen with the new words.

AI — give a vision tool the same screenshot; find what it missed and what it invented.
03UI principles — patterns, layout, colour

Why a bottom navigation is a bottom navigation, and how recognising a pattern means never designing from zero. Grid, alignment, hierarchy and spacing; then colour and type, with colour theory tied straight to contrast so it's a rule with a reason.

AI — generate three palettes, then run all three through a contrast checker. At least one usually fails.
Act two · Sessions 4–6 Making something small
04First hands in Figma

Frames, shapes, text, fills and auto-layout — the one feature worth learning early. Everyone builds a screen from scratch on their own keyboard, then rebuilds their paper redesign as a real one.

No AI, deliberately — they need the muscle memory before a tool offers to do it for them, and that's said out loud.
05UX basics, quickly

Four ideas in half an hour — who it's for, the path they take, what's actually wrong, and how we'd know it worked. Then they reverse-engineer the screen they just built, and mostly discover they made something attractive for nobody in particular.

AI — draft a persona from three real facts, then delete every stereotype it added.
06The teardown

The session students tell their friends about. A full critique of a real app in two columns — how it works, how it looks — problems ranked by how much they hurt, and a sketched fix for the top three, defended out loud to the group.

AI — ask it for usability problems in the same app, then mark each one agree, disagree, or invented.
Act three · Sessions 7–10 Their own product
07Find a real problem, and ask real people

Problems, not app ideas. Why "would you use this?" is a useless question and "tell me about the last time you…" is a good one. Six interview questions, torn apart by peers and rewritten, then two interviews with family or classmates.

AI — draft the questions with it, then cut every leading one. Usually about half.
08Make sense of it, then decide

Grouping notes, naming the pattern, and choosing what not to solve. Four commitments in writing — one person, one problem, one path, one measure of success — then eight sketches in eight minutes, twice, before choosing a direction.

AI — give it the anonymised notes and compare its themes with their own grouping.
09Design it, then test it

Only the screens the path needs, built in Figma with the act-one principles as a literal checklist. Prototypes are swapped and tested in both directions: hand it over, stay silent, watch where they hesitate, fix the two worst things before leaving.

AI — generate one alternative version of a screen, then write down what it got right and wrong. Nothing generated goes in unedited.
10Brand it, and show your work

Why identity comes last: a name and a logo mean something only once you know who it's for. Name, logo, final palette, then the case study — problem, what people said, what changed, what's next — presented in five minutes, alongside the optional micro-interaction gallery.

AI — draft a name and a one-line promise, then rewrite both in their own words.

Three threads run through every session

The parts that make the difference between a course they enjoyed and a practice they keep.

The design journal

One page per session plus one at home: something they used that week and the decision behind it. Twenty entries by the end — visible evidence of progress, and the beginning of a portfolio.

The AI rule

AI drafts, you decide. If you can't explain why it's right, it doesn't go in your project.

Repeated until they can recite it. Every session includes a moment where AI is wrong, so they learn to catch it rather than trust it.

Critique as a habit

Students give and receive critique from session two onward, so presenting their own work in session ten is ordinary rather than frightening — confidence that transfers well beyond design.

Tools and delivery

Paper and markers for the sketching work. Figma from session four — free education accounts, running in a browser on any machine, and what the industry actually uses. Nothing to install.

AI tools are named and vetted for age-appropriate terms, and used by the students themselves inside the session rather than demonstrated at them.

Available as ten weekly sessions, a two-week holiday intensive, or a single two-hour taster built from the teardown. In English or Arabic.

For schools and parents

Group size

Up to 16 in person, 12 online, so every student gets critique on their own work.

Safeguarding

Interviews are with family or classmates only. No external contact, and no student work published without written parental consent.

Responsible AI use

Named tools only, no personal information entered, and interview notes anonymised before any tool sees them.

What you'll see

A written progress note at the halfway point and at the end, a certificate of completion, and an optional showcase session for parents.