How do you measure tech savviness? For several years (since 2015), we’ve been on a mission to develop a valid and practical measure. In our earlier articles, we have Reviewed the literature. We reviewed the literature on tech-savvy measures and found three key approaches to measuring tech-savviness by assessing (1) what a person knows, (2)
While the term Lean UX has faded in popularity, many of the lean concepts remain, and they are even incorporated into other frameworks such as Agile. One of the core tenets of Lean UX is to focus on decisions and not deliverables. In project-based UX research, decisions often take a back seat to deliverables. Research
In an earlier article, we described a pilot study from 2015 in which we investigated how to measure tech savviness. Building on the published literature, we generated candidate items that measured three aspects of tech savviness: what people know, what people do, and what people feel. In that pilot study, we assessed knowledge using a
How do you measure tech savviness? Abstract constructs such as usability, trustworthiness, intelligence, and desirability can be difficult to measure. The same applies to tech savviness. But to paraphrase Potter Stewart, we know a tech-savvy person when we see one. Tech savviness should matter to UX researchers. When we measure an experience, we don’t want
The Single Ease Question (SEQ®) is a single seven-point item that measures the perceived ease of task completion. It is commonly used in usability testing. Since its introduction in 2009 [PDF], some researchers have made variations in its design. Figure 1 shows the version that we currently use. In 2022, we decided to test some
Changing the number of response options in the survey might confuse participants. Over the years, we’ve heard variations on this concern articulated a number of different ways by clients and fellow researchers. Surveys and unmoderated UX studies commonly contain a mix of five-, seven-, and eleven-point scales. That leads some to express concern. Why are
Near the top of the list of concerns people have when using statistics with UX data is what to do with non-normal data. If you remember only a few things from statistics class, you might recall something about data needing to look like the infamous bell curve; more specifically, it needs to be normally distributed.
The seven-point Single Ease Question (SEQ®) has become a standard in assessing post-task perceptions of ease. We developed the SEQ over a decade ago after our research showed it performed comparably to or better than other single-item measures. It is an extension of an earlier five-point version that Tedesco and Tullis (2006 [PDF]) found performed best
When learning statistics, you’ll encounter many formulas based on principles of probability and mathematics. But statistics isn’t just a formulaic process where you enter data and are told what to do. Statistics should guide, not dictate, decisions. In making decisions, though, there are different styles of interpreting data. Although a lot of people think statistics
Can an experience be useful without meeting your needs? The UX-Lite™ is a new questionnaire that evolved from the SUS and the UMUX-Lite. It has only two items, one measuring perceived Ease and one measuring perceived Usefulness, as shown in Figure 1. Because the verbal complexity of the original Usefulness item stands in stark contrast
