PROJECT SUMMARY. The UW School of Social Work, in partnership with Heritage University’s School of Social Work in Yakima Valley recently partnered to develop a training program for BA level Social Workers to address limited clinician capacity in rural primary care settings. Currently the curriculum is a combination of didactic training in telephone based CBT (20 hours), role play training (25 hours), and guided supervision. This model of training is like the methods used by EBPI training programs for care managers in the AIMS Center and the VA. The scalability of these programs is limited, however, by expert time to conduct training activities, clinician time away from work to engage in training activities, and the fact that even when clinicians participate in training, there is no guarantee they will certify. Adaptive learning, an educational method that uses adaptive algorithms to may be a potential solution to these problems in capacity building. These programs can tailor the educational experience to the needs of the trainee, reduce time in training, improve competence in complex decision-making and standardize training. This study builds on the existing research base on EBPI training, and adds to it by designing and testing an intelligent tutoring system (ITS) based on adaptive learning algorithms. Both EBPI experts (Aisenberg) and past EBPI trainees (Heritage University School of Social Work) will partner with experts in educational software development (Popovic) to create the ITS, which will be compared to training as usual on time to training, competence and skill drift. We hypothesize that capacity building through improved EBPI learnability (target mechanism) will result in enhanced clinical ability to deliver EBPI elements competently, and in a shorter time-period, and that greater competence will result in better quality of care.