Training providers continue to be challenged in accurately measuring the effectiveness of performance-based training solutions. Studies have shown interest in measuring cognitive state to improve human performance (Schmorrow & Kruse, 2002), yet the training industry still lacks a non-invasive, near real-time deployable method to objectively measure the trainee's cognitive state. Our collaborative research team has developed and documented a valid methodology for quantitatively assessing training effectiveness, using physiological measures of cognitive state coupled with task-specific performance metrics. To successfully employ this method and design personalized training, we must develop standard definitions of proficiency levels in terms of the physiological signature of cognitive workload. During an initial study performed in 2017, we measured the total cognitive load, spare cognitive capacity and taskspecific performance metrics (i.e., flight technical performance) of novice pilots performing standardized hand-flown tasks in a simulator and in live flight. We extended this evaluation in 2018 to include competent and expert pilots. The purpose of this follow-on study was two-fold: to further validate the approach for measuring training effectiveness, and to characterize the effect of pilot education and experience on cognitive workload, spare cognitive capacity, and task-specific performance. Through this research, we have defined an initial set of standards for the interplay between cognitive workload and performance associated with various learner proficiency levels. This paper summarizes the key results of the follow-on study and describes the standards of cognitive workload developed as a result of the two-year research effort. It also illustrates how cognitive workload trends can assist in developing personalized, performance-based learning for trainees with varying degrees of proficiency. It concludes with a discussion of how this methodology can be applied to improve training outcomes and future studies that would further extend its value in the simulation and training industry.