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Does Thinking Aloud Reduce the Evaluator Effect?

In Think Aloud (TA) testing, participants speak their thoughts while attempting tasks. The process is meant to help researchers identify usability problems and potential fixes. Indeed, in an earlier analysis, we found an increase in problem discovery. Our evaluation of 153 videos, split between TA and non-TA, revealed that evaluators uncovered 36–50% more problems with

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Does Thinking Aloud Uncover More Usability Issues?

One of the most popular UX research methods is Think Aloud (TA) usability testing. In TA testing, participants speak their thoughts while attempting tasks. The process helps researchers identify usability problems and potential fixes. But is the process of thinking aloud necessary to uncover problems and insights? Earlier, we investigated the effects of TA on

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A New Statistical Approach for Predicting Usability Problems

In an earlier article, we described the most common methods for modeling the total number of unique usability problems uncovered in a usability test: the average problem occurrence (p), adjusted problem occurrence (adj-p), beta-binomial, and specific problem probabilities. While these methods provide reasonably accurate predictions of the total number of unique problems, there is still

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The Anatomy of a Survey Question

We’ve written extensively about question types, the elements of good and bad writing, why people forget, and common problems with survey questions. But how do you get started writing questions? Few professionals we know have taken a formal course in survey development and instead rely on their experiences or best practices. Despite being called questions,

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A Decision Tree for Picking the Right Type of Survey Question

Crafting survey questions involves thinking first about the content and then about the format (form follows function). Earlier, we categorized survey questions into four content types (attribute, behavior, ability, or sentiment) and four format classes (open-ended, closed-ended static, closed-ended dynamic, or task-based). As with any taxonomy, there are several ways to categorize response options (e.g.,

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