工作量
任务(项目管理)
度量(数据仓库)
计算机科学
构造(python库)
人口
索引(排版)
运筹学
数学
工程类
数据挖掘
系统工程
人口学
社会学
万维网
程序设计语言
操作系统
作者
Matthew L. Bolton,Elliot Biltekoff,Laura Humphrey
标识
DOI:10.1109/thms.2023.3263482
摘要
Human mental workload can profoundly impact human performance and is thus an important consideration in the design and operation of many systems. The standard method for assessing human mental workload is the NASA Task Load Index (NASA-TLX). This involves a human operator subjectively rating a task based on six dimensions. These dimensions are combined into a single workload score using one of two methods: scaling and summing the dimensions (where scales are derived from a paired comparisons procedure) or averaging dimensions together. Despite its widespread use, the level of measurement of NASA-TLX's dimensions and its computed workload score has not been investigated. Additionally, nobody has researched whether NASA-TLX's two approaches for computing overall workload are mathematically meaningful with respect to the constituent dimensions' levels of measurement. This is a serious deficiency. Knowing what the level of measurement is for NASA-TLX scores will determine what mathematics can be meaningfully applied to them. Furthermore, if NASA-TLX workload syntheses are mathematically meaningless, then the measure lacks construct validity. The research presented in this article used a previously developed method to evaluate the level of measurement of NASA-TLX workload and its dimensions. Results show that the dimensions can, in most situations, be treated as interval in population analyses and ordinal for individuals. Our results also suggest that the methods for combining dimensions into workload scores are meaningless. We recommend that analysts evaluate the dimensions of NASA-TLX without combining them.
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