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The FAA is seeking concepts and approaches for the implementation of the Air Traffic Controller Academy Performance & Excellence System (APEX), which aims to provide a scalable, data-driven system for monitoring student performance in real-time across Academy training. The system must integrate various training data sources and support predictive modeling and performance standardization.
The FAA is looking for a modern, adaptive system to serve as a foundational performance intelligence backbone for Academy training operations.
This Request for Information (RFI) includes a Statement of
Objectives (SOO) which describes the Federal Aviation Administration’s (FAA) goals and expectations for the implementation and operation of the ATC Training Performance Intelligence System. The FAA seeks concepts, approaches, and general capabilities only; please do not submit proprietary, trade secret, or confidential information. All responses should be written at a level that can be released publicly without restriction. The FAA seeks a scalable, data-driven system capable of providing near–real-time visibility into student performance across all phases of Academy training. The FAA seeks a modern, adaptive solution that can serve as an enterprise training performance intelligence backbone. The FAA intends for this solution to function as an enterprise-level training performance intelligence infrastructure, forming a scalable data architecture that integrates disparate training data sources into a unified analytics environment. The system must serve as the foundational performance intelligence backbone for Academy training operations and future enterprise expansion. The FAA does not seek a standalone reporting overlay or content delivery enhancement tool; rather, the solution must establish an interoperable, extensible enterprise data framework capable of supporting predictive modeling, performance standardization, and strategic decision-making. The FAA requests that respondents provide concept papers identifying real-world solutions, along with an implementation plan that, at a minimum, addresses the following areas: Comprehensive Data Integration
Objective-Level Mastery Mapping Near–Real-Time Analytics Dashboards Error Taxonomy and Trend Analytics Predictive Analytics Instructor Performance Analysis Enterprise Leadership Reporting Technical and Security
Requirements Scalability and Future Expansion Implementation Approach Nature of this RFI:
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