S. Perrig, L. Aeschbach, Nicolas Scharowski, Nick von Felten, Klaus Opwis, Florian Brühlmann
{"title":"Measurement practices in user experience (UX) research: a systematic quantitative literature review","authors":"S. Perrig, L. Aeschbach, Nicolas Scharowski, Nick von Felten, Klaus Opwis, Florian Brühlmann","doi":"10.3389/fcomp.2024.1368860","DOIUrl":null,"url":null,"abstract":"User experience (UX) research relies heavily on survey scales to measure users' subjective experiences with technology. However, repeatedly raised concerns regarding the improper use of survey scales in UX research and adjacent fields call for a systematic review of current measurement practices. Therefore, we conducted a systematic literature review, screening 153 papers from four years of the ACM Conference on Human Factors in Computing Systems proceedings (ACM CHI 2019 to 2022), of which 60 were eligible empirical studies using survey scales to study users' experiences. We identified 85 different scales and 172 distinct constructs measured. Most scales were used once (70.59%), and most constructs were measured only once (66.28%). The System Usability Scale was the most popular scale, followed by the User Experience Questionnaire, and the NASA Task Load Index. Regarding constructs, usability was the most frequently measured, followed by attractiveness, effort, and presence. Furthermore, results show that papers rarely contained complete rationales for scale selection (20.00%) and seldom provided all scale items used (30.00%). More than a third of all scales were adapted (34.19%), while only one-third of papers reported any scale quality investigation (36.67%). On the basis of our results, we highlight questionable measurement practices in UX research and suggest opportunities to improve scale use for UX-related constructs. Additionally, we provide six recommended steps to promote enhanced rigor in following best practices for scale-based UX research.","PeriodicalId":52823,"journal":{"name":"Frontiers in Computer Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fcomp.2024.1368860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
User experience (UX) research relies heavily on survey scales to measure users' subjective experiences with technology. However, repeatedly raised concerns regarding the improper use of survey scales in UX research and adjacent fields call for a systematic review of current measurement practices. Therefore, we conducted a systematic literature review, screening 153 papers from four years of the ACM Conference on Human Factors in Computing Systems proceedings (ACM CHI 2019 to 2022), of which 60 were eligible empirical studies using survey scales to study users' experiences. We identified 85 different scales and 172 distinct constructs measured. Most scales were used once (70.59%), and most constructs were measured only once (66.28%). The System Usability Scale was the most popular scale, followed by the User Experience Questionnaire, and the NASA Task Load Index. Regarding constructs, usability was the most frequently measured, followed by attractiveness, effort, and presence. Furthermore, results show that papers rarely contained complete rationales for scale selection (20.00%) and seldom provided all scale items used (30.00%). More than a third of all scales were adapted (34.19%), while only one-third of papers reported any scale quality investigation (36.67%). On the basis of our results, we highlight questionable measurement practices in UX research and suggest opportunities to improve scale use for UX-related constructs. Additionally, we provide six recommended steps to promote enhanced rigor in following best practices for scale-based UX research.