Dynamic problem selection in air traffic control training: A comparison between performance, mental effort and mental efficiency

Abstract

The differential effects on training and training outcome of four methods of problem selection were investigated in a computer-based training for air traffic control. In one method, training problems were given to the participants in a fixed predetermined sequence, from simple to complex. In the other methods, problems were selected dynamically, based on three different learner variables. These were mental effort, performance and mental efficiency, which is a variable that combines mental effort and performance measures to determine problem efficiency. After the training, transfer was measured. The hypothesis that dynamic problem selection would lead to more efficient training than non-dynamic problem selection was confirmed. The second hypothesis, that dynamic problem selection based on mental efficiency would lead to more efficient training and better transfer than dynamic problem selection based on performance or mental effort alone was not supported. However, the efficiency measures of the three variables were distorted by the differential effects of these variables on the acquisition phase. A possible explanation for the results is that selection based on performance stimulates rule automation, whereas selection based on mental effort or mental efficiency leads to schema acquisition.