Planning¶

Syllabus mapping

Working Scientifically outcome — Planning. Covers identifying and managing variables, designing a fair and valid method, assessing risk, and selecting appropriate equipment. Like every Working Scientifically outcome, it's assessed through application inside a focus area's practicals and depth study, not as standalone content.

Exact NESA outcome code TODO — confirm against the official syllabus PDF (Resources) before treating any wording on this page as verbatim NESA text.

You need to know: how to name your three types of variables correctly, how to design a method that actually isolates the relationship you're testing, and how to fill out a risk assessment properly — not just as a formality.

Core¶

The three types of variable¶

Every fair investigation in this course has (at minimum) these three:

Independent variable (IV) — the one thing you deliberately change between trials.
Dependent variable (DV) — the thing you measure, which you expect to respond to the IV.
Controlled variables — everything else that could affect the DV, which you deliberately hold constant so the only thing changing is the IV.

Worked example

Investigation: how the angle of an inclined plane affects a trolley's acceleration (see Questioning and Predicting).

Variable	Role	This investigation
Angle of incline	Independent	Deliberately set to 10°, 20°, 30°, 40°, 50°
Acceleration	Dependent	Measured via light gates or a motion sensor at each angle
Trolley mass	Controlled	Same trolley used for every trial
Surface of the ramp	Controlled	Same ramp material throughout (affects friction)
Release method	Controlled	Trolley released from rest, not pushed, every time

A method that changes the angle and swaps trolleys partway through hasn't isolated anything — if the acceleration changes, you can't tell whether it was the angle or the trolley. This is the whole point of "fair testing": change one thing, measure one thing, hold everything else still.

Fair testing vs a control¶

Two related but different ideas get called "control" in science:

Controlled variables (above) — the things you deliberately keep the same across every trial of a single experiment.
A control experiment (or control group) — a separate, baseline trial run with no treatment applied, used as a comparison point. This shows up constantly in biology and medicine (a placebo group, an untreated sample) but is less common in a typical Year 11 physics prac, where you're usually comparing a range of IV values against each other rather than against a no-treatment baseline. It's still worth knowing the distinction, since "control" gets used loosely and command-verb questions sometimes expect you to be precise about which one you mean.

Designing the method itself¶

A few things worth deciding before you're standing at the bench, not while you're there:

Range of the independent variable — spread values across a sensible range (not clustered at one end), so a resulting graph actually shows a trend rather than a cluster of nearby points.
Number of data points — enough IV values to draw a convincing line or curve; five or six is a reasonable minimum for a Year 11 prac unless told otherwise.
Repeats — plan to repeat each trial (typically 3+) so you can calculate a mean and get a sense of how consistent your results are. This matters for Conducting and becomes essential once you get to processing uncertainty.
Equipment precision — pick equipment whose precision actually matches what you're trying to detect. A ruler with mm markings can't meaningfully distinguish a 0.3 mm difference; a stopwatch operated by hand has a reaction-time uncertainty of roughly 0.2–0.3 s regardless of how many decimal places it displays.

Risk assessment¶

A risk assessment isn't a box-ticking formality — it's how you show you thought about what could go wrong before it does. NESA (and every school's WHS policy) expects one to accompany any practical involving equipment, chemicals, electricity, heat, or moving parts.

The standard structure:

Hazard	Risk	Likelihood	Consequence	Control
What could cause harm	What could actually happen	How likely, given your setup	How bad if it happens	What you'll do to reduce it

Worked example — electromagnet prac

From Magnetism's suggested prac (factors affecting electromagnet strength):

Hazard	Risk	Likelihood	Consequence	Control
Current-carrying wire/coil	Wire overheating with sustained high current	Medium (depends on current used and duration)	Minor burn	Use current within the power supply's rated limit; switch off between trials rather than leaving it energised continuously
Iron/steel core and nail	Sharp point on the nail	Low	Minor puncture/scratch	Handle by the shaft, not the point; store point-down when not in use
Power supply	Electric shock from exposed terminals	Low (low-voltage DC supply)	Minor shock	Check cable insulation before use; switch off before adjusting connections

Note the pattern: every hazard gets a specific, actionable control — not "be careful," which controls nothing.

Advanced

Pilot studies. Before committing to a full run of trials, a short pilot (one or two quick trials across the planned IV range) can reveal problems a plan alone won't — an IV range that's too narrow to show a trend, a DV that's too small to measure reliably with the chosen equipment, or a control that turns out to be harder to hold constant than expected. Adjusting the method after a pilot, and explicitly saying so in a report, is good practice, not a sign the original plan was bad — it's evidence of exactly the kind of iterative refinement Working Scientifically as a whole is trying to develop.

Extension

Beyond the Physics 11–12 syllabus — won't appear in the HSC, included for interest / depth study inspiration.

📎 Depth study idea

Clinical and pharmaceutical trials take the "control" idea much further than a typical physics prac does, using a control group that receives no treatment (or a placebo) and comparing it against a treatment group — often blinded (the participant doesn't know which group they're in) or double-blinded (neither the participant nor the person administering the treatment knows, to eliminate bias from expectation). There's a genuine, if less obvious, physics-adjacent parallel: any investigation involving human measurement — reaction-time-based timing, judging a "just noticeable" light or sound intensity — inherits the same expectation bias problem trials are designed to control for. Worth a depth study if you're investigating anything where a human is part of the measurement chain, not just the equipment.

Video/visual resources¶

🎥 Khan Academy — TODO: source a variables / experimental design explainer. Must define IV/DV/controlled clearly with a worked example, and ideally cover why equipment precision matters (matching the stopwatch-vs-light-gate point above). Essential.
🎥 Physics High — TODO: unlikely to have a generic risk-assessment/variables video — more realistic to skip this line, or link a specific NSW school WHS risk assessment template/guide instead of a video.

Check yourself¶

For an investigation into how the number of turns in a coil affects the strength of an electromagnet (see Magnetism), identify the independent variable, the dependent variable, and two controlled variables.

Answer

Independent: number of turns in the coil. Dependent: electromagnet strength (e.g. number of paperclips lifted, or a field sensor reading). Controlled (any two): current supplied, core material, wire gauge/thickness, distance between the electromagnet and whatever it's picking up.
Explain why a hand-held stopwatch is a poor choice of equipment for measuring the very short time it takes a trolley to cross a 20 cm light-gate interval, even though the stopwatch displays results to 0.01 s.

Answer

The stopwatch's displayed precision (0.01 s) is misleading — the actual limiting factor is human reaction time when starting/stopping it, which is roughly 0.2–0.3 s. For a very short interval, that reaction-time uncertainty could be a large fraction of (or even larger than) the time being measured, making the result unreliable regardless of how many decimal places are shown. A light gate, which starts/stops electronically without human reaction time in the loop, is far more appropriate.

Write a two-row risk assessment (Hazard, Risk, Likelihood, Consequence, Control) for an investigation into refractive index using a glass block and a ray-box light source (see Wave Behaviours).

Answer

Example (answers will reasonably vary):

Hazard	Risk	Likelihood	Consequence	Control
Bright ray-box light source	Eye discomfort from staring directly into the beam	Low	Temporary glare, minor discomfort	Avoid looking directly into the beam; view the ray's path on the paper, not the source
Glass block	Cuts from a chipped/broken edge	Low	Minor cut	Inspect the block before use; handle by the flat faces, not the edges