U.S. Naval Research Laboratory, Washington, D.C., USA; University of Virginia, Charlottesville, VA, USA.
University of Virginia, Charlottesville, VA, USA.
Appl Ergon. 2023 Jan;106:103885. doi: 10.1016/j.apergo.2022.103885. Epub 2022 Sep 6.
This research examined three specific gaps in the workload transition literature: (1) the impact of workload transition rate, (2) the applicability of current theoretical explanations, and (3) the variability of performance overall and over time. Sixty Naval flight students multitasked in an unmanned aerial vehicle control testbed and workload transitioned at three rates: slow, medium, or fast. Response time and accuracy were analyzed via growth curve modeling. Slow transitions had the largest decline in performance over time. Medium transitions had some of the slowest, but most accurate and consistent performance. Fast transitions had some of the fastest, but least accurate performance. However, all performance trends significantly varied, suggesting multiple theoretical explanations may apply and performance may also depend on the individual. Design guidance on how to maximize performance goals with transition rate is provided, but future research needs to study the theoretical explanations and impact of individual differences further.
（1）工作量转换率的影响，（2）当前理论解释的适用性，以及（3）整体和随时间变化的绩效变化。60 名海军飞行学员在无人机控制试验台进行了多项任务，并以三种速度进行了工作量转换：慢、中或快。通过增长曲线建模分析了响应时间和准确性。随着时间的推移，缓慢的转换导致性能下降最大。中等转换的性能虽然有些缓慢，但准确性和一致性最高。快速转换的性能虽然有些较快，但准确性最低。然而，所有的绩效趋势都有很大的差异，这表明可能有多种理论解释适用，并且绩效也可能取决于个体。提供了关于如何根据转换率最大化性能目标的设计指导，但未来的研究需要进一步研究理论解释和个体差异的影响。
