Usability error classification: qualitative data analysis for UX practitioners

  • Authors:
  • Lada Gorlenko;Paul Englefied

  • Affiliations:
  • IBM UK, Warwick, United Kingdom;IBM UK, Warwick, United Kingdom

  • Venue:
  • CHI '06 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2006

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Abstract

Usability evaluations generate large amounts of poorly structured qualitative data, but traditional methods of analysis are often impractical for use by industry practitioners. To address this, we developed a classification of usability issues covering cause, effect, task impact and business impact. In a design project, this has several applications, such as a) enabling practitioners to analyze qualitative data quickly and reliably; b) ensuring that findings can be systematically compared across studies; c) presenting results to clients in terms of potential business impact and its causes; and d) offering recommendations to designers in terms of design errors and their cost. We continue refining the model as we test it in our projects.