Classroom Team Generator
Paste the names, get a fair split.
Add your options below, then tap to pick.
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Saved locally. Nothing is sent to a server.
How it works
- Paste your class names into the input.
- Set the desired team size (3, 4, 5) or number of teams.
- Hit Generate — students are randomly allocated to balanced-size teams.
- Apply anti-clique rules — specify pairs that shouldn't end up together.
- Re-run for a different allocation; save any allocation as a screenshot.
Why use this tool
- Hand-allocating 28 students into 7 groups eats 4-5 minutes; tooled allocation under 30 seconds.
- EEF research shows random group composition beats friendship groups for learning outcomes.
- Removes "the teacher always puts me with X" objections — the algorithm allocates.
- Anti-clique rules let you break up dominant pairings without singling students out publicly.
- Repeatable allocation logic — same input never produces same output, so groups feel fresh.
When to use it
- Project group formation at start of a unit.
- Random pair work for paired discussions and structured talk.
- Brain-break team competitions where short-term groupings are needed.
- PE / sports allocation when friendship groups would create skill imbalances.
- Trip / school-visit group allocations.
- Reward-trip groupings where you want mixed cohort rather than self-selected.
FAQ
How many teams can I make?
Tap once per student — they go to the next team in rotation. Restart for a fresh assignment.
What if my class size doesn't divide evenly?
The generator handles it automatically — 17 students into "groups of 4" becomes 3 groups of 4 + 1 group of 5. Pick the imbalance direction in settings.
Can I save a generated allocation?
Yes — screenshot or print the result. The next "Generate" produces a different allocation, so the saved one is the canonical record for that lesson.
How many anti-clique pairs can I specify?
Up to 5-6 reliably. More than that and the algorithm may struggle to find valid allocations. For more complex constraints, use the manual override after generation.
Should I rerun until I get a good-looking group?
No — defeats the legitimacy. Pre-commit to honour the generated allocation. If you re-run, students will spot the pattern and the algorithm loses its authority.