Assessing Soldier Individual Differences to Enable Tailored Training

The operational tempo of the United States Army has increased dramatically, placing a premium upon quality of training. For decades researchers have explored the extent to which training quality can be improved by tailoring training, defined as assessing learning-relevant individual differences and assigning learners to optimal learning conditions based on those differences. Before informed tailored training in U.S. Army institutional settings can take place, researchers must know what individual differences (IDs) are related to course performance. Instructors from the Warrant Officer Candidate School (WOCS) at Fort Rucker, Alabama, were interviewed to determine what IDs, in their experience, predict academic success in the WOCS course. Based on those interviews, three IDs dimensions (initiative, attention to detail, and metacognition) were chosen. Other IDs were selected by the research team on the basis of hypothesized relationships between experience and course demands. A set of instruments measuring those IDs as well as demographic information was constructed and given to the instructors to review. Upon instructor approval, the packet was administered to a 5-week and a 7-week WOCS class (total n=157). The student responses were then statistically compared with end of course grades to determine the predictive validity of the instruments. For the 5-week class, only one demographic variable and none of the instructor-provided IDs correlated with academic performance. For the 7-week class, two of the demographic items and two of the instructor-provided IDs predicted academic performance. However, correlations between the predictor and criterion variables would have to be stronger to serve as a basis for tailoring training. On the other hand, the demographic items are easy to administer and the gain in prediction may be judged worth the effort. Possible reasons for the moderate predictive power of the individual differences are proposed. Prepared in collaboration with Dynamics Research Corporation, Andover, MA.