For our May 2018 issue, we start with an invited essay from Jeff Kelley on the origins of the Wizard of Oz (WoZ) prototyping methodology in the lab directed by one of the fathers of modern human factors engineering—Alphonse Chapanis. Widely regarded as the originator of the WoZ method, in his essay, “Wizard of Oz (WoZ)—A Yellow Brick Journey,” Dr. Kelley describes his early work with WoZ and reminisces about his mentor, Dr. Chapanis.
In addition to the editorial, this issue includes three research papers, one on the use of self-trackers in telerehabilitation, one presenting a new way to use a combination of multidimensional scaling and k-means clustering in the development of information architecture, and a method for setting benchmarks for individual items of the System Usability Scale.
The first article is “Evaluation of Self-Trackers for Use in Telerehabilitation,” by Kim Munck, Mark Hummeluhr Christensen, Alan Tahhan, Birthe I. Dinesen, Helle Spindler, John Hansen, Olav W. Nielsen, and Søren Leth. They evaluated the usability of six self-tracking devices used in telerehabilitation of heart failure patients and found significant differences among the evaluated products using scores based on structured interviews.
The second article is “Information Architecture (IA): Using Multidimensional Scaling (MDS) and K-Means Clustering Algorithm for Analysis of Card Sorting Data,” by Sione Paea and Ross Baird. They describe a method for visualizing and analyzing card sorting data aiming to develop an in-depth and effective information architecture and navigation structure using k-means clustering and multidimensional scaling, with appropriate handling of overlaps and outliers.
In the third article, “Item Benchmarks for the System Usability Scale,” Jim Lewis and Jeff Sauro provide a method for setting benchmarks for individual System Usability Scale (SUS) items. Using a large-sample database of SUS questionnaires (11,855 individual SUS questionnaires from 166 unpublished industrial studies/surveys), they developed regression equations for computing benchmarks for SUS items based on an overall SUS score. A review of the SUS literature on published benchmarks for the means of overall SUS scores from usability studies/surveys provides guidance on selecting an appropriate value of SUS to use when setting item benchmarks.