Publications & Resources
Assessment of Rifle Marksmanship Skill Using Sensor-Based Measures
Sam O. Nagashima, Gregory K. W. K. Chung, Paul D. Espinosa, Chris Berka, and Eva L. Baker
The goal of this report was to test the use of sensor-based skill measures in evaluating performance differences in rifle marksmanship. Ten shots were collected from 30 novices and 9 experts. Three measures for breath control and one for trigger control were used to predict skill classification. The data were fitted with a logistic regression model using holdout validation to assess the quality of model classifications. Individually, all four measures were significant; when considered together, only three measures were significant predictors for level of expertise (p < .05). Overall percent correct in shot classification for the testing data was 90.0%, with a sensitivity of 67.5%, and 96.0% specificity.
Nagashima, S. O., Chung, G. K. W. K., Espinosa, P.D., Berka, C., & Baker, E. L. (2009). Assessment of rifle marksmanship skill using sensorbased measures (CRESST Report 755). Los Angeles: University of California, Los Angeles, National Center for Research on Evaluation, Standards, and Student Testing (CRESST).