Adaptive training (AT) is training that is tailored to an individual trainee’s strengths and weaknesses, such that each trainee receives a unique training experience. Previous research has demonstrated that AT can lead to higher learning gains and decreased training time when compared to traditional training approaches in certain domains [1]. However, more systematic research is needed to define which AT techniques to employ and for what content in order to determine when to invest in these technologies. The goal of this research is to examine the benefits of two particular AT techniques (i.e., adapting feedback and scenario difficulty) based on trainee performance in a complex military decision-making task. In this paper, we discuss the development of a research testbed, the Adaptive Trainer for Joint Terminal Attack Controllers (ATTAC), from a science of learning perspective. In particular, we review how the Cognitive Theory of Multimedia Learning and the Expertise Reversal Effect drove design decisions and present preliminary results on participants’ impressions of ATTAC from a pilot study.
CITATION STYLE
Johnson, C. I., Marraffino, M. D., Whitmer, D. E., & Bailey, S. K. T. (2019). Developing an Adaptive Trainer for Joint Terminal Attack Controllers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11597 LNCS, pp. 314–326). Springer Verlag. https://doi.org/10.1007/978-3-030-22341-0_25
Mendeley helps you to discover research relevant for your work.