Framework for Eye Tracking Patterns and Usability Problems: Pt 3
Ehmke and Wilson, the two researchers who published the report in association with City University in London, raise the point that there still remains a need “for studies that relate eye-tracking patterns to specific usability problems (by indicating cognitive processes).” In the past, eye tracking metrics have been compared to general interface usability, assessed by usability experts or calculated from performance completion times for certain tasks. But, as they say, expert reviews and performance measure can only go so far, lending an overview and failing to establish any direct linkage between metrics and usability problems. Expert reviews don’t have direct relations to a users’ regular eye tracking patterns, and therefore have not been used for the identification of usability problems.
It’s kind of a tough blow for companies dealing in usability studies, but to us it makes perfect sense and seems to link with a general trend in the industry that says usability studies are not, in fact, the Holy Grail. They can be successfully employed to gain insight into a variety of subjects, but if they’re done in a vacuum, with no other supplementary research or tactics, it’s sort of a lost effort, aside from putting a bunch of pretty graphics and stats on a page and handing it to a customer.
This is not to say that past researchers haven’t tried to establish eye tracking data frameworks. Eye tracking has been around for longer than most know – early studies using eye tracking for usability provided insights into problem solving, reasoning, mental imagery, and search strategies, to name a few. In 1950 researchers actually tested pilots’ gaze and proposed fixation frequency and duration as important metrics that still influence more contemporary studies.
The City University paper credits researchers Goldberg and Kotval as having created one of the most influential frameworks in eye tracking history when they set out to investigate correlations between eye tracking metrics and usability problems. The two proposed a number of spatial eye tracking metrics relevant to visual search, and they were tested in a study where a drawing tool selection program was configured with various interfaces. For example, they set up a page with randomly grouped tools, and another where the tools were grouped by functionality, and both were evaluated by interface designers and regular web users with the expectation that there would be a great difference between the two interfaces.
Identifying Web Usability Problems from Eye-Tracking Data
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