Exploring the Use of Computational Cognitive Models to Personalize Training

The purpose of training and education in the United States Department of the Air Force (DAF) is to develop and sustain mission-critical knowledge, skills, and abilities (KSAs) among airmen, guardians, and civilians. The DAF must deliver effective training and education to fully use its human capital, provide warfighting assets to combatant commanders, and maintain asymmetric advantage over competitors. Yet training and education is costly. A recent budget request included more than $2 billion for training and education, and recent guidance has highlighted that the U.S. Air Force must transform all facets of training and education to field a highly capable force in an affordable manner. This report focuses on computational cognitive models, a class of training technologies with transformative potential. Computational cognitive models emulate psychological processes like knowledge acquisition and retention. These models have been used to develop empirically grounded training curricula and deliver personalized training in diverse domains. The primary benefits of using these models to deliver personalized training are enhanced learning gains and reduced training time. This report explores the feasibility of applying computational cognitive models to the acquisition and sustainment of mission-critical KSAs, with emphasis on second-language learning. The authors affirm that cognitive models can be integrated with training curricula in a variety of ways, and each of these potential courses of action (COAs) presents different levels of benefits along with different technical and logistical challenges.