The learning efficiency of complex tasks is an area being widely investigated in the literature. Specifically, many different instructional strategies have been developed in an effort to improve efficiency, especially within automated systems. Of particular interest are application methodologies which provide individual-ized recommendations. In this paper we compared the impact of individualized feedback based on both performance and real-time workload levels to feedback based on performance alone. Our data suggest pa-per-based knowledge acquisition test scores were not impacted by the intervention timing assisted by neuro-physiological measures. However, scenario-based decision-making performance scores were signifi-cantly improved when utilizing EEG data to aid intervention timing but not with eye-tracking data.
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