Following the 9/11 attacks, the U.S. Air Force faced an urgent need to improve the efficiency of its training processes in an effort to reduce costs and increase the capabilities of hundreds of newly-hired, entry-level analysts. The Intelligence Community surged to deal with the increased volume and complexity of intelligence processing due to continuously-evolving threats posed by a variety of state and non-state actors. All new hires require specialized training to enable them to apply their expertise, acquired in higher education (e.g. science, technology, engineering, and mathematics degrees), to the unique needs in their specific area. Concurrently, existing training had to be revitalized to address the shifting mission and influx of new hires, but mission requirements didn't provide sufficient time for senior analysts to dedicate to training new personnel. A structured approach had to be used to bring the entry-level analysts up to speed quickly and evolve the curriculum to match the current threat environment.

We will describe the competency-based approach (Mission Essential Competencies, or MECs) used to define expertise by eliciting knowledge from experienced analysts identifying the groundwork essential for new analysts to be able to complete the job 95 percent of the time without the support of others. Over 110 knowledge and skills, 25 common supporting competencies, and over 100 experiences with eight learning environments across three groups of all-source analysts were identified within National Air and Space Intelligence Center (NASIC). Surveys (N=141) revealed 55 training gaps. NASIC completed a curriculum overhaul resulting in a newly designed and streamlined curriculum for 30 student analysts taught in a cohort over six weeks. NASIC's Training and Development Committee and senior analysts across the organization applied the lessons learned from the MECs to ensure on-thejob training is interactive, relevant and taught at the appropriate level for junior analysts. Lastly, we defined the training requirements and how they are applied to develop a web-based training technology. Using a Guided Problem-Based Learning approach, we are developing a virtual framework that allows analysts to proceed through multiple levels applying scientific steps to cultivate a conclusion on information gathered throughout the process. Specifications for the new technology were based upon 92 common knowledge and skills, and 55 common experiences to create learning objectives which outlined course content addressing 26 of the training gaps uncovered during the survey process. The framework developed for the flexible intelligence trainer will be generalizable enough to apply to other domains for further use outside the Intelligence Community.