By the end of this topic, you should be able to...
select and use appropriate drawings, physical prototypes and CAD models to gather relevant data and feedback, which can be used to analyse and develop the design iteratively.
Guiding Question
Why is it necessary for designers to prototype ideas as part of a design process?
💡 Did You Know? Google Glass failed spectacularly in 2014—not because the technology didn't work, but because engineers tested functionality when they should have been gathering feedback on social acceptability.
Why Seek Feedback?
Prototypes are questions disguised as objects—but only if you ask them the right way. A rough sketch on paper invites brutal honesty about concept direction ("hate it, love it, what if...?"), while a polished CAD rendering triggers nitpicking about button placement—different prototype fidelities generate different quality feedback.
Strategic designers deliberately match prototype type to the question they need answered:
drawings test initial reactions and aesthetic preferences quickly and cheaply
physical prototypes reveal ergonomic failures, emotional responses, and usability problems that screens can't capture
CAD models enable quantitative analysis—measuring grip force, testing interference fits, simulating thermal performance.
But gathering data isn't enough—you must analyze it critically: Is that user complaint a fundamental flaw or personal preference? Does this test reveal a pattern or an outlier? Which feedback contradicts your assumptions and therefore matters most?
The iterative design cycle—prototype, test, analyze, refine, repeat—only works when you select appropriate tools, ask focused questions, and translate messy human feedback into actionable design decisions that move you closer to an evidence-based solution.
Case in Point
When Fitbit developed their first heart-rate-tracking wristband, early CAD simulations predicted sensor accuracy within 2%, but physical prototype testing with 200 users revealed a critical oversight: the device failed on darker skin tones due to light absorption differences. Only real-world prototype feedback—not simulation data—exposed this bias, forcing a complete optical redesign that simulations alone would never have caught.
Learning Goals
In this topic, you'll learn to select prototype formats strategically for specific feedback goals, design effective testing protocols, analyze qualitative and quantitative data critically, and document iterative refinements—skills essential for demonstrating evidence-based design evolution in your IA project.
Linking Questions
When creating physical prototypes, which ergonomic considerations should be taken into account? (A1.1)
To what extent are user-centred research strategies useful to gather feedback on models and prototypes of proposed design solutions? (A2.1)
How do designers use their knowledge of prototyping techniques to ensure effective modelling and prototyping? (A2.2)
Which aspects of material properties can be explored through modelling? (A3.1)
How can information about a proposed structural system, such as a product housing, be gathered using CAD modelling and contribute to the development of a design solution? (A3.2, B3.2)
How effectively can mechanical systems be mocked up and tested using modelling and prototyping? (A3.3, B3.3)
How can effective electronic systems be modelled virtually? (A3.4, B3.4)
How does the development of prototypes inform the choice of manufacturing techniques and production systems for a product? (A4.1, B4.1)
How can modelling and prototyping be used to inform the development of a product following a user-centred design (UCD) strategy? (B1.1)
To what extent is modelling and prototyping essential for inclusive design? (B2.2)
To what extent can the same materials used for modelling and prototyping be used in the material selection of a commercial product? (B3.1)