可用性测试中的认知负荷测量方法:界面评估的关键分析与框架

Cognitive Load Measurement Methods for Usability Testing: A Critical Analysis and Framework for Interface Evaluation

Human Factors The Journal of the Human Factors and Ergonomics Society · 2026
被引 0
ABS 3

中文导读

系统综述了2001至2025年间87项实验研究,将认知负荷测量方法分为主观和客观两类,并提出了一个根据界面类型和评估目标选择合适方法的框架,帮助研究人员和实践者提升可用性测试的准确性。

Abstract

ObjectiveThis systematic review evaluates the use of cognitive load measurement methods in usability testing across diverse software interfaces. It provides guidance for researchers and practitioners by proposing a framework for selecting appropriate cognitive load measurement techniques.BackgroundCognitive Load Theory offers insights into software usability by addressing users' mental effort during task performance. Although cognitive load measurement methods are increasingly used in usability testing, no comprehensive analysis has focused specifically on various software interfaces.MethodWe systematically analysed 87 experimental studies published between 2001 and 2025. Databases searched included IEEE, ACM, ScienceDirect, SpringerLink, and Scopus. Inclusion criteria focused on studies applying cognitive load measurement to usability testing for different types of software interfaces.ResultsCognitive load measurement methods were categorised as subjective (e.g., NASA-TLX and self-reports) or objective (e.g., EEG, eye-tracking, dual-task paradigms, and physiological sensors). The most frequently used methods were performance measures (19%), NASA-TLX (12%), and eye fixations (11%). Commonly evaluated platforms included websites, virtual reality systems, and productivity tools. Each method's applicability, strengths, and limitations were identified.ConclusionThe review synthesises the relative merits of cognitive load measurement methods in usability evaluations and introduces a framework to guide the selection of techniques based on interface type and evaluation goals.ApplicationThe proposed framework operationalises CLT to support targeted, user-centred usability testing. It facilitates the selection of effective cognitive load measurement strategies, enhancing evaluation accuracy and informing better software design.

可用性测试认知负荷人机交互软件工程用户体验