How do you measure tech savviness? UX researchers are, of course, not in the business of assessing individual performance. But differences in individual technical abilities certainly have an impact on performance. A good measure of tech savviness can help researchers target levels of tech savviness in recruiting (e.g., low, high, or a mix) and classify
All of us at MeasuringU® wish you a Happy New Year! In 2023, we posted 49 articles and continued to add features to our MUiQ® UX testing platform to make it even easier to develop studies and analyze results. We hosted our eleventh UX Measurement Bootcamp, again as a blended virtual event with a combination
All of us at MeasuringU® wish you a Happy New Year! In 2022, we posted 48 articles and welcomed several new clients to our MUIQ® UX testing platform, where we continue to add new features and reduce the friction in developing studies and analyzing results. We hosted our ninth UX Measurement Bootcamp—this time a blended
When Kraig Finstad (2010) developed the Usability Metric for User Experience (UMUX), his goal was to replace the ten-item System Usability Scale (SUS, a popular measure of perceived usability) with a shorter questionnaire that would (1) correlate highly with the SUS and (2) have item content related to the ISO 9241 Part 11 international standard,
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,
The UMUX-Lite is a two-item standardized questionnaire that, since its publication in 2013, has been adopted more and more by researchers who need a concise UX metric. Figure 1 shows the standard version with its Perceived Ease-of-Use (“{Product} is easy to use”) and Perceived Usefulness (“{Product}’s capabilities meet my requirements”) items. Figure 1: Standard
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.,
Making decisions with data inevitably means working with statistics and one of its most common frameworks: Null Hypothesis Significance Testing (NHST). Hypothesis testing can be confusing (and controversial), so in an earlier article we introduced the core framework of statistical hypothesis testing in four steps: Define the null hypothesis (H0). This is the hypothesis that
In architecture, form follows function. In survey design, question format follows content. Earlier we described four classes of survey questions. These four classes are about the form, or format, of the question (e.g., open- vs. closed-ended). But before you can decide effectively on the format, you need to choose the content of the question and
Advice on rating scale construction is ubiquitous on the internet and in the halls of organizations worldwide. The problem is that much of the advice is based not on solid data but rather on conventional wisdom and what’s merely thought to work. Even published papers and books on survey design can present a perspective that
