The Relevance of Attention Control, Not Working Memory, in Human Factors

Abstract

Objective Discuss the human factors relevance of attention control (AC), a domain-general ability to regulate information processing functions in the service of goal-directed behavior. Background Working memory (WM) measures appear as predictors in various applied psychology studies. However, measures of WM reflect a mixture of memory storage and controlled attention making it difficult to interpret the meaning of significant WM-task relations for human factors. In light of new research, complex task performance may be better predicted or explained with new measures of attention control rather than WM. Method We briefly review the topic of individual differences in abilities in Human Factors. Next, we focus on WM, how it is measured, and what can be inferred from significant WM-task relations. Results The theoretical underpinnings of attention control as a high-level factor that affects complex thought and behavior make it useful in human factors, which often study performance in complex and dynamic task environments. To facilitate research on attention control in applied settings, we discuss a validated measure of attention control that predicts more variance in complex task performance than WM. In contrast to existing measures of WM or AC, our measures of attention control only require 3 minutes each (10 minutes total) and may be less culture-bound making them suitable for use in applied settings. Conclusion Explaining or predicting task performance relations with attention control rather than WM may have dramatically different implications for designing more specific, equitable task interfaces, or training. Application A highly efficient ability predictor can help researchers and practitioners better understand task requirements for human factors interventions or performance prediction.

The Impact of Interpreting Training Experience on the Attentional Networks and Their Dynamics

“…Variables that situate individuals along that continuum can be modeled to better understand how the dynamic nature of in-class and after-class interpreting training experience affects the attentional networks differently. Thirdly, most tasks used to measure individual differences in attention need better reliability [ 87 , 88 , 89 ]. Further study could utilize the three squared tasks developed by Burgoyne and his team members [ 90 ] to resolve critical theoretical and methodological flaws in tasks measuring attention, and these tasks can be administered in less than 3 min (compared to over 15 min for ANT).…”