This content originally appeared on NN/g latest articles and announcements and was authored by Maria Rosala, Feifei Liu
Summary: Analyze usability findings for authenticity, consistency, repetition, spontaneity, appropriateness, and confounding factors to separate surface impressions from real insights.
Qualitative usability tests yield two types of data: behavioral data (or performance data) and attitudinal data (or subjective data). During analysis, we must consolidate both types of data while considering additional factors, such as information about the study design or recruitment.
Why You Can’t Take a Data Point at Face Value
Consider the following example.
You’re moderating a usability test of a prototype, aiming to evaluate the usefulness of a comparison feature. After completing a task on the prototype, 4 out of 5 users said that they liked the feature and would use it in the future.
Read Full Article
This content originally appeared on NN/g latest articles and announcements and was authored by Maria Rosala, Feifei Liu
Maria Rosala, Feifei Liu | Sciencx (2025-04-11T17:00:00+00:00) 6 Dimensions for Assessing Usability Data in Analysis. Retrieved from https://www.scien.cx/2025/04/11/6-dimensions-for-assessing-usability-data-in-analysis/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.