This content originally appeared on NN/g latest articles and announcements and was authored by Raluca Budiu
Summary: Qualitative usability studies have few users and variable protocol; numbers obtained from such studies are likely to poorly reflect the true behavior of your population due to large measurement errors.
Perhaps one of the most common methods of collecting user data is qualitative usability testing . This method usually involves observing a few users and noticing those elements of the design that are easy or hard to use.
Some researchers also like to collect numerical data in qualitative studies — measures like success (whether the participant was able to complete the task or not), task time, or self-reported metrics such as satisfaction, task difficulty, NPS , and SUS . As a result, in reports or presentations, we often see formulations such as:
These statements are misleading. To understand why, let’s take a detour into the true-score theory , which is central to any measurement.
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This content originally appeared on NN/g latest articles and announcements and was authored by Raluca Budiu
Raluca Budiu | Sciencx (2021-05-23T16:00:00+00:00) Why You Cannot Trust Numbers from Qualitative Usability Studies. Retrieved from https://www.scien.cx/2021/05/23/why-you-cannot-trust-numbers-from-qualitative-usability-studies/
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