Your Personal Naismith: Measure Your Flat and Uphill Pace

Each student measures their own walking speed on flat ground and their climbing rate on the school stairs or bleachers, then builds a personal version of Naismith's rule. It shows that a route's timing depends on who's hiking it.

How to play

1. Walking warm-up for ankles and calves (4 min).
2. Flat leg: a measured 200 m at hiking pace, slow enough to talk. A partner times it and you calculate speed in km/h (6 min).
3. Climbing leg: measure one step's height and count the steps to get the vertical meters. Each student climbs several times in a row at a sustainable pace, walking down the other side, and calculates how many meters they'd climb in an hour (8 min).
4. Math: using your own numbers, estimate the time for a 10 km route with 600 m of climbing and compare it with Naismith (8 min).
5. Share-out: the class range and why a group has to move at the slowest hiker's pace. Also note that a short test overstates your real speed over a whole day (4 min).

Rules

• On stairs, walk up, never run, and come down on the opposite side.
• Test pace is conversational, not a race.
• Data is personal: nobody compares out loud without permission.
• If you feel dizzy or have pain, stop and tell the teacher.

Variations

Adaptations

• Limited mobility: measures their pace on a ramp and on flat ground in a wheelchair and builds their own rule.
• Asthma: climbing pace capped at what still allows talking; inhaler at hand.
• Students self-conscious about fitness: work with a trusted partner and keep their data private.

Learning goals

• Measure one's own walking speed and climbing rate.
• Adapt a general timing rule to oneself.
• Understand why a group adjusts to the slowest pace.

Equipment for a class of 25

• stopwatches: 15
• tape measures: 2
• cones: 8
• recording sheets: 30

Teacher tip

Measure the step height before class to save time. If there are no wide stairs, use a ramp and measure its rise with a tape and a phone level app. The usual mistake is climbing too fast to look good, which skews the data.

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