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Updated: Aug 29, 2025

Precise, High-throughput Analysis of Bacterial Growth
Published on: September 19, 2017
Workload transition rate matters: Evidence from growth curve modeling
Shannon P Devlin1, Noelle L Brown2, Sabrina Drollinger3
1U.S. Naval Research Laboratory, Washington, D.C., USA; University of Virginia, Charlottesville, VA, USA.
Abstract:
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.
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