Primary and secondary research methods, the use of anthropometric and market data, and modelling and prototyping (sketch models, CAD models, working prototypes) to develop, test and refine design ideas through the iterative cycle.

A Component 02 short-answer question. Marks for the distinction and a relevant example of each.

Award marks for: primary research is information the designer collects first-hand for the specific project, such as measuring potential users (anthropometrics), interviewing or observing people sitting, questionnaires, or testing a prototype chair with users. Secondary research is information from existing sources gathered by others, such as anthropometric data tables, market reports on the furniture sector, competitor product reviews, standards documents or manufacturers' material data. For the chair: a primary example is observing and measuring how a sample of users sit; a secondary example is consulting an anthropometric data table for seat heights.

A common dropped mark is giving an example that is the wrong type (calling a data table primary, or calling a user interview secondary).

A Component 02 levels-of-response question (AO2 plus AO3), marked by levels.

A top-level answer links model types to stages and weighs their value. Early on, quick sketch models (card, foam, blue foam) test form, scale and proportion cheaply and let many ideas be explored fast. CAD models then allow accurate 3D visualisation, simulation (stress, fit, motion) and refinement without making anything physical. Working prototypes test real function, ergonomics and manufacture, and are tested with users to gather feedback for the next cycle. The value is that modelling makes ideas tangible and testable early, so problems are found cheaply before committing to expensive tooling, which is the heart of iterative design. The evaluation should weigh the cost and time of prototyping, the fact that early models cannot test everything (a foam model shows form but not function), and that over-investing in one prototype too early can entrench a flawed idea. A justified conclusion is that matching the fidelity of the model to the question being asked at each stage gives the most value.

Markers reward linking models to stages and weighing their value, not just listing model types.