Improving our understanding of user trial samples using survey data
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Abstract
User research such as user trials provides valuable information on users and how they respond to interfaces in practice. However, it can be hard to ensure a repre-sentative sample. We propose a methodology to improve the understanding of a sample’s skew and to identify the characteristics of those who are missing by com-paring the sample with survey data. This can improve the interpretation of results and inform further recruitment to improve the sample. We provide a case study of this methodology in practice. 30 participants were recruited using quota sampling with significant effort to obtain people with low technology experience. Neverthe-less, comparison with UK survey data on technology experience, competence and attitudes identified four key groups of people not included in the sample, covering 29% of the population. We discuss how these missing people would likely respond on the tasks, based on the characteristics of similar people in the survey