SPhO Experimental Skills: What Past Rounds Show
A practical preparation guide based on verified past SPhO evidence, with no assumption that a four-hour experimental paper applies to the 2026 cycle.
Q: Does SPhO 2026 have a four-hour practical round? A: The public 2026 organiser page does not confirm that format. The latest detailed organiser-linked cycle we could verify was 2024, when the experimental event was on 20 November and the examination itself was listed as two hours. Use the current school circular for 2026 logistics.
What is confirmed and what is not
SPhO has included experimental work in past cycles, so laboratory preparation is sensible. However, an old version of this guide incorrectly described a fixed four-hour theory paper plus a fixed four-hour practical paper as the current SPhO format.
The public IPS SPhO page does not give the 2026 dates, duration, round structure, equipment, or marking weights. The organiser-linked 2024 notice listed an experimental event at NUS on 20 November 2024, with a two-hour examination inside the event schedule.
Treat that as historical evidence, not a forecast.
Experimental skills worth building
These skills remain useful for physics competitions and school practical work even if the current SPhO task changes:
- choose a useful range and spacing of measurements;
- record raw data with units and sensible precision;
- repeat readings where variation matters;
- distinguish random variation from a systematic effect;
- choose clear axes and scales for graphs;
- use a best-fit line or curve rather than joining dots blindly;
- extract a gradient or intercept from well-separated points;
- connect the observed pattern to a physical model; and
- explain one realistic improvement to the method.
Do not memorise a single uncertainty formula for every situation. Start by identifying what was measured, what resolution or spread is justified, and how the calculated result depends on those values.
A practical preparation routine
During school laboratory work
Before collecting data, predict the relationship you expect. During the experiment, label every table heading with a quantity and unit. Afterward, check whether the graph and result support the prediction and state the main limitation in plain language.