Throughout their careers, DoD personnel are educated or trained by numerous organizations, each using their own IT systems and business processes. Typically, these systems are developed and implemented independently, without coordination, causing duplication in function and stovepiping of the data maintained. Many of these systems also use proprietary data repositories. As a result, data transport, control, management, governance, and ownership are not easily compatible or interoperable across network boundaries. Therefore, there is now large-scale duplication of data and a lack of interoperability, transparency, and effective management to ensure DoD-wide data quality, availability, integrity, security and usability.

The Total Learning Architecture (TLA) is a set of policies, standards, and specifications, developed by the Advanced Distributed Learning (ADL) Initiative, that is driving the DoD’s Enterprise Digital Learning Modernization initiative. The TLA vision features a robust data strategy that collects and maintains fine grained data across the learner’s entire career arc. These data can leverage machine learning capabilities for personalization, adaptation, and recommendation across modalities, accommodating changes to the credential, the course content, and the trained systems, to support continuous improvement and validation of learning outcomes.

The standards included within the TLA allow for fielding and sustainment of education and training solutions that dynamically change and grow in response to new technology, or new approaches to learning, while normalizing data these systems generate about human capability. The normalized data facilitates a truly global learning analytics capability and enables the enterprise-wide planning of individual lifelong learning journeys in support of an organization’s human capital supply chain.

This tutorial provides an in-depth understanding of the TLA data strategy and the future learning ecosystem it enables. It introduces learners to the core concepts of data interoperability and decomposes existing systems into the basic building blocks required to support lifelong learning. The TLA relies on four general data types including metadata about registered activities, the common definition of competencies required to perform different jobs, streaming data on learner performance, and enterprise learner records that manage data about experiences, credentials, and career trajectories.

Attendees will gain a good understanding of the core TLA services that publish or subscribe to these data and transform them into meaningful information. General guidelines will be provided for implementing these standards, building an integrated data strategy, and managing the lifecycle of learner data across the DoD enterprise.