The Advanced Distributed Learning (ADL) Initiative started the Total Learning Architecture (TLA) project in 2016 with the goal of establishing a common data strategy across the education and training industry that enables lifelong learning. The TLA data strategy is built around commercial standards that organize the learning-related data required to support lifelong learning and enable defense-wide interoperability across DoD organizations, products, and data.
As a policy driven architecture, the TLA does not require any mandatory components. There are only required functions, organized into microservices and data. Each functional area must be exposed through common interfaces, asynchronous services, and standard data formats for communicating and storing data. Learner performance data is generated using the IEEE Experience API (xAPI) and compared against IEEE Reusable Competency Definitions. The activities generating this learner data are described using IEEE P2881 Learning Activity Metadata. Together, this data enables a ledger of learner performance that is housed in the IEEE Enterprise Learner Record. These standards are coupled with an active governance strategy to help the community adapt to an unexpected future.
In recent years, progress has been made towards providing adaptivity and personalization in technology-enhanced learning environments. However, the breadth of data made available through the TLA standards also supports systems that adapt to the needs of the organization across functional areas. This paper summarizes the approach taken to mature and enhance the IEEE data models with DoD stakeholders. It presents the TLA logical model that describes the interdependent relationships between the four major types of data required by the TLA and demonstrates how they improve DoD’s ability to analyze, visualize, and tailor learning experiences through different views of the same data. The resulting dashboards present a granular view of lifelong learning and establishes a foundation for adaptation across all echelons of the human capital supply chain.
Keywords
ADVANCED DISTRIBUTED LEARNING,ANALYTICS,ARCHITECTURE,DATA
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