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Subtle patterns in users' think-aloud (TA) verbalizations (i.e., utterances)are shown to be telltale signs of user experience (UX) problems and used tobuild artificial intelligence (AI) models or AI-assisted tools to help UXevaluators identify UX problems automatically or semi-automatically. Despitethe potential of such verbalization patterns, they were uncovered with nativeEnglish speakers. As most people who speak English are non-native speakers, itis important to investigate whether similar patterns exist in non-nativeEnglish speakers' TA verbalizations. As a first step to answer this question,we conducted think-aloud usability testing with Chinese non-native Englishspeakers and native English speakers using three common TA protocols. Wecompared their verbalizations and UX problems that they encountered tounderstand the effects of language and TA protocols. Our findings show thatboth language groups had similar amounts and proportions of verbalizationcategories, encountered similar problems, and had similar verbalizationpatterns that indicate UX problems. Furthermore, TA protocols did notsignificantly affect the correlations between verbalizations and problems.Based on the findings, we present three design implications for UXpractitioners and the design of AI-assisted analysis tools.

Think-Aloud Verbalizations for Identifying User Experience Problems: Effects of Language Proficiency with Chinese Non-Native English Speakers