The control–result relationship determines learning cost

What it is

Mapping is the understandable correspondence among a control action, an interface object, and a system result. Turning a knob right to increase its adjacent value, or using an arrow key to move focus in that direction, are mappings. When mapping is clear, people can infer action from the relationship; when it is arbitrary, ambiguous, or inconsistent, they must memorize each control's special rule, increasing learning cost.

Why it happens

People use spatial relation, causality, temporal order, and familiar convention to predict a control's effect. A control near its affected object, with compatible direction and stable behavior, supports transfer from what is known to what is new. When similar gestures yield different outcomes in similar places, prediction fails and memory must take over. Clear mapping also makes errors easier to diagnose by locating which action caused which result.

Studying it

Ask first-time users to complete a set of tasks requiring selection of the correct control. Measure prediction accuracy, attempts to reach stable performance, error type, and quality of explanation. Holding other factors steady, alter control–result proximity, directional compatibility, or labels and compare effects. Interviews should ask which rule a person used, not only whether the task ended successfully.

Where it stops holding

No single mapping fits every task: physical intuition may be insufficient for multidimensional control, abstract data, or limited screen space. Consistency with an external tool can sometimes matter more than a locally “natural” appearance. Good mapping also does not replace feedback, constraints, or clear naming; it reduces inference burden rather than removing every need for understanding.

Applying it

• Place controls near their results, and make direction, order, range, and state change align with relations people can see.
• Reuse one control logic across similar objects; do not change gesture meaning or result location without an evident reason.
• Add labels, previews, and immediate feedback for correspondences that cannot be inferred naturally, then test whether people can predict results in a first task.

Related

• Same group: B2.04.2 Spatial layout correspondence is the strongest natural mapping · B2.04.3 Cultural-convention mappings cannot be assumed across cultures · B2.04.4 Arbitrary mappings need labels or memory support
• Nearby: B2.03 Signifiers · B2.05 Feedback
• Search terms: mapping · control-result relationship · learnability