CATS

CATS

Research:

Thanks – That was just what I needed

Ever found yourself sitting through training that keeps touching on information that you already know or quite frankly, don’t need for your job? This Competency-based Adaptive Training System (CATS) saves learners from wasted time and costs associated with unnecessary training. How? By customizing role-based training content to match each employee’s needed skills and current competencies. Only the training you need, when you need it.

Performance data to proficiency mapping

Project Details

Proposal Title:
CATS: Competency-based Adaptive Training System
Agency:
United States Air Force
Contract Numbers:
FA8650-16-C-6696, FA8650-13-C-6402, FA8650-12-M-6290
Start Dates:
2011, 2012, 2016

To address the inherent limitations of a “one size fits all” training approach, CATS was designed to personalize training for warfighters in the Air Force. It provides a platform for pulling together an individual’s experience, proficiency, and skill development needs to create a training experience that is based specifically on that individual’s proficiency gaps.

How we did it

At its core, CATS brings together the capabilities of a learning management system (LMS), learning content management system (LCMS), and a competency management system (CMS). This enables a data-driven learning lifecycle that delivers personalized content and learning events, as needed. This is a significant advancement in technology-driven competency-based training approaches.

Not only does the integration of the three systems create a much more user-friendly management experience (everything is tracked in one system), it allows individuals to use a personalized development plan based on a certain career path or to meet requirements for particular roles.

In the final solution, we brought together many disparate processes and tracking systems to provide an underlying competency framework which mapped searchable learning content to the development or remediation needs of specific roles. In addition, we created dynamic learning paths that adapt based on all the available performance and proficiency inputs. Lastly, we built a standardized approach that allowed various models of competencies and learning objectives to be integrated within the larger training ecosystem. This created a complete, commercializable solution for managing performance and talent development across large, complex organizations.