Amy E. Bolton
Research Psychologist
NAVAIR Orlando Training Systems Division
AIR-4961
12350 Research Parkway
Orlando, FL 32826-3275
V (407) 380-4555
F (407) 380-4063
amy.bolton@navy.mil
Short Statement of Interest
For the past five years we have been conducting a program of research investigating alternative techniques for identifying and interpreting patterns in human performance data collected during sessions in training simulators. To date, we have investigated the application of multiple linear regression, nonlinear regression, fuzzy logic, and classification and regression trees (CART). We are currently investigating discrete choice analysis and several “fast and frugal” algorithms (ala Gigerenzer).
Our three primary research questions have been:
(1) How closely can each technique fit human performance data?
(2) How well does each technique identify patterns that are consistent with the subjective reports of the human participants?
(3) How effective is training feedback that is based on a critique of the performance patterns derived with each technique?
We are interested in learning about new techniques and gaining insight into the representational power of different techniques. In addition, within a training simulator, events unfold over time, and thus we need to find effective ways to incorporate background knowledge (or history information) when modeling performance data. Finally, our work has a strong focus on the application of models to support training goals. It is our hope that identifying performance patterns in data collected from a training simulator should help the trainer determine a student’s strengths and weaknesses, and thus support the development of adaptive and tailored feedback, instruction and scenario exercises. We would welcome the opportunity to talk to other researchers who are interested in similar applications.
References for our Research
Campbell, G. E., Buff, W. L., & Bolton, A. E. (in preparation). Viewing training through a fuzzy lens. To appear in A. Kirlik (Ed.), Working with Technology in Mind: Brunswikian Resources for Cognitive Science & Engineering. Oxford University Press.
Campbell G. E. & Bolton, A. E. (2003) Mathematical Models of Human Decision Making: Rational, Fuzzy, or Fast and Frugal? To be presented at the 47th Annual Conference of the Human Factors and Ergonomics Society.
Bolton, A. E., Buff, W. L., & Campbell, G. E. (2003). Faster, cheaper, and “just as good”? A comparison of the instructional effectiveness of three HBRs that vary in development requirements. Proceedings of the 12th Conference on Behavior Representation in Modeling and Simulation, Scottsdale, AZ, May 12-15, 2003.
Campbell, G. E., Buff, W. L. & Bolton, A. E. (2002) Traditional mathematical modeling applied to human prioritization judgments: Quicksand for the unwary modeler. Presented at the Eleventh Conference on Computer Generated Forces. May 7th-9th, 2002, Orlando, Florida.
Campbell, G. E., Buff, W. L., Bolton, A. E. & Holness, D. O. (2001). The application of mathematical techniques for modeling decision-making: Lessons learned from a preliminary study. In E. M. Altman, A. Cleermans, C. D. Schunn & W. D. Gray (Eds.), Proceedings of the Fourth International Conference on Cognitive Modeling (pp. 49-54). Mahwah, NJ: Lawrence Erlbaum Associates.
Bolton, A. E., Holness, D. O., Buff W. L., & Campbell, G. E. (2001). The application of mathematical models in training systems: A viable approach to cognitive modeling? Proceedings of the Tenth Conference on Computer Generated Forces, 497-505.
Holness, D. O., Buff, W. L., Bolton, A. E. & Campbell, G. E. (2001). Delivering feedback in a training system using mathematical modeling techniques. Poster presented at the 16th annual meeting of the Society of Industrial and Organizational Psychology, San Diego, CA.
Campbell, G. E., Buff, W. L. & Bolton, A. E. (2000). The diagnostic utility of fuzzy system modeling for application in training systems. Proceedings of the XIVth Triennial Congress of the International Ergonomics Association and the 44th Annual Meeting of the Human Factors and Ergonomics