Welcome to the first issue of volume
4 of JUS!
This issue is partly devoted to the technique of card sorting. In their invited editorial, Jed Wood and Larry Wood, reflect on the origins of card sorting and how it has evolved to being a popular technique in usability work. They then go on to outline and discuss various current practices with card sorting and provide very useful recommendations of how to approach each practice and avoid pitfalls and fallacies. They also go beyond the current practices to discuss their view on the open issues that require further research and accumulated experience.
In the first peer-reviewed article, “A modified Delphi approach to a new card sorting methodology”, Celeste Paul introduces a combination of card sorting and the Delphi forecasting method to produce more useful outcomes for the design of information architecture. Relative to other collaborative techniques, the proposed method utilizes the use of card sorting to elicit knowledge of a group of users or experts and the sequential aspects of the Delphi method resulting in a step-wise consensus building. Empirical experience and findings on the use of the method are presented to substantiate the proposed method.
The card sorting technique is further addressed in the second peer-reviewed article. In their “The usability of computerized card sorting: A comparison of three applications by researchers and end-users”, Barbara Chaparro, Veronica Hinkle, and Shannon Riley tackle the problem of finding the right computer-based card sorting program that can fit the needs of both end-users and the researchers. While not surprising they find the different applications are preferred for the different groups, they provide some practical advice on what aspects to look for in such programs to fit the needs.
The third peer-reviewed article addresses yet again the tough challenges that heuristic evaluation introduces. Shazeeye Kirmani continues her work on the “Heuristic Evaluation Quality Score (HEQS) – Defining heuristic expertise”. What is required of someone who performs a heuristic evaluation? The article discusses factors such age, experience, gender, etc. and how these relate to the quality of problems found. Her findings suggest that experience can be a critical factor in increasing the proportion of “real” problems found.