Understanding preference: A meta-analysis of user studies

IF 5.3 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies Pub Date : 2024-11-23 DOI:10.1016/j.ijhcs.2024.103408

Morten Hertzum

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引用次数: 0

Abstract

A user's preference for one system over another is probably the most basic user experience (UX) measure, yet user studies often focus on performance and treat preference as supplementary. This meta-analysis of 144 studies shows that while users in general prefer systems with which they achieve lower task time and error rate, they more consistently and more strongly prefer systems that impose lower workload. In only 2 % of the studies a preferred system imposes significantly higher workload than a nonpreferred system. Across the studies, a stronger preference coincides with a larger difference in workload, task time, and error rate. This correlation is strongest for workload, lower for task time, and lowest for error rate. That is, workload is a stronger predictor of preference than performance is, even for the near exclusively utilitarian tasks covered by this meta-analysis. The implications of these findings include that workload should be more fully integrated in research on usability, UX, and design and that it is risky for practitioners to infer preference from performance, or vice versa.

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理解偏好：用户研究的荟萃分析

用户对一个系统的偏好可能是最基本的用户体验（UX）衡量标准，但用户研究通常关注性能，将偏好视为补充。这项对144项研究的荟萃分析表明，虽然用户通常更喜欢任务时间和错误率较低的系统，但他们更一致、更强烈地喜欢工作量较低的系统。在只有2 %的研究中，首选系统比非首选系统施加了明显更高的工作量。在这些研究中，更强的偏好与工作量、任务时间和错误率的较大差异相吻合。这种相关性在工作量方面最强，在任务时间方面较弱，在错误率方面最低。也就是说，工作量比工作表现更能预测人们的偏好，即使是在本荟萃分析涵盖的几乎完全功利的任务中也是如此。这些发现的含义包括，工作负载应该更充分地集成到可用性、用户体验和设计的研究中，并且从业者从性能推断偏好是有风险的，反之亦然。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Human-Computer Studies 工程技术-计算机：控制论

CiteScore

11.50

自引率

5.60%

发文量

108

审稿时长

3 months

期刊介绍： The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...