Sometimes it seems that there isn't enough collaboration between the academic side of User Experience and the applied side of it. UX practitioners need supporting evidence to back up their decisions when designing interfaces. Those who run studies about UX need to know that the questions they're researching are relevant in actual practice.
Often I discuss problems to which I don't have a direct solution, but this time I feel there is something I can do about it. So from now on I'll occasionally post entries that highlight UX research/studies of particular relevance to web design. Hopefully this will become a helpful source of evidence to support decisions that UX practitioners often deal with.
Let's start things off with a series of studies by Formulate Information Design, which were summarized in two articles by Jessica Enders on A List Apart. Zebra Striping is when a table of data has slight shading on alternating rows, with the intent of making it easier to read. The first study attempts to determine whether shading of single, alternating rows makes a difference in the speed at which users are able to accomplish tasks involving finding specific data. No clear answer resulted from this study, so further studies were conducted, yielding the following recommendations:
The results of the three studies conducted to date suggest that the safest option is to shade the alternating, individual rows of your table with a single color. Taking this approach is likely to ensure that:
- task performance is better, or at least no worse, than with other table styles, and
- the aesthetic sensibilities and subjective preferences of the majority of your users are catered for.
If zebra striping of this type cannot be done easily, then ruling a line between each row may be the next best option.
The research summary article concludes with a bit of wise advice:
Secondly, if you are designing an application or website that contains data tables, don’t let personal preference, habit, or the (untested) status quo drive your design decisions—go out there and get some user data. Run some tests using your preferred approach and one or more of the alternatives described here. And if you can, share your results with us, so our knowledge of the efficacy or otherwise, of different styles of tabular data, can grow.
This can, and should, be applied to all areas of UX design, not just data tables. We need to test our assumptions and conventional methods more thoroughly before making design decisions. With the vast array of information-sharing tools available today, we shouldn't have any problem getting the word out when our research reveals something useful to UX practice as a whole. Consider this post the start of my contribution to this vision.
Have you conducted or discovered any research you'd like to see featured here, or that you think is relevant to the field of User Experience?