Augmented reality user experience scale (ARUXS): Development and validation

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Authors
Bui, Bill
Advisors
Ni, Rui
Issue Date
2024-12
Type
Dissertation
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Abstract

As augmented reality (AR) technology continues to evolve, there is a lack of established guidance on what constitutes an effective design for AR user interfaces. AR encompasses a spectrum of applications, from assisted reality devices featuring 3D digital overlays to more advanced spatial recognition headsets known as mixed reality (MR). This research addresses this gap by developing and validating a comprehensive user experience (UX) scale for AR environments to reliably measure UX in AR and identify its key factors. The scale also enables comparisons between old and new iterations and facilitates benchmarking against competitors. This study implemented a six-step process to develop, refine, and validate the scale. The item pool generation phase incorporated heuristic lists and questionnaires to identify relevant items. Experts in survey design and AR development reviewed and refined the set of items to ensure comprehensiveness. Following these expert reviews, cognitive interviews were conducted to assess the clarity and intuitiveness of the questions from the users’ perspectives. The subsequent phases involved exploratory and confirmatory factor analyses to identify the structure of the scale and validate its components. The final step involved evaluating the scale with an AR application and comparing its effectiveness to other validated scales. The findings revealed strong positive correlations with these scales and demonstrated that the newly developed scale was a better predictor of key outcome metrics, such as likelihood to purchase and user satisfaction. Thus, the Augmented Reality User Experience Scale (ARUXS) was developed and validated, comprising 52 items across 10 dimensions: Aesthetic, Cybersickness, Engrossment, Interaction, Physical Comfort, Presence, Privacy, Ease of Use, Usefulness, and Social Collaboration. The scale is designed for applications in both assisted reality and MR interfaces.

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Thesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Psychology
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Wichita State University
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