Qualitative data describes users' opinions, experiences, motivations, and behaviours, whereas quantitative data consists of numerical measurements or counts. Designers combine both to understand a problem and create justified design requirements.
The Reasoning
Within B2.1 The design process, research provides evidence about users, contexts, and existing products. The data type determines how evidence can be analysed and applied.
Qualitative data answers why, how, or what does the user experience? An interview participant might say that a bottle cap feels uncomfortable to open. Designers code responses into recurring themes, needs, and problems.
Quantitative data answers how many, how much, or how often? Testing might show that 18 out of 25 users take more than 10 seconds to open the cap. Designers can calculate frequencies, averages, and percentages to compare measurable performance.
| Feature | Qualitative data | Quantitative data |
|---|---|---|
| Form | Words, observations, and descriptions | Numbers, measurements, ratings, and counts |
| Methods | Interviews, focus groups, open-ended questions, and observations | Closed questionnaires, anthropometric measurements, and timed tests |
| Value | Explains needs, motivations, and experiences | Shows scale, frequency, patterns, and performance |
| Limitation | Can be subjective and difficult to generalize | May not explain why users respond as they do |
| Application | Informs ideas and user-centred requirements | Supports measurable design specifications and testing criteria |
For example, the qualitative finding “students find the chair uncomfortable” identifies a problem. Quantitative anthropometric measurements and comfort ratings can then justify requirements for seat height, width, or adjustability.
A common misconception is that quantitative data is always better because it is numerical. Effective research uses triangulation, combining methods or data sources to produce more reliable conclusions.
Exam Technique
In an IB response, define both types, give one design-research example of each, and explain how each informs a decision. Do not merely list methods; connect evidence to user needs, specifications, concept development, or evaluation.