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Fast Learning from Unlabeled Episodes for Next-Generation Tailoring (FLUENT) Total Learning Architecture Infrastructure (TLA)

Identify specifications and software services for the TLA for tailored learning trajectories improving the sequence of learning content over time.


FLUENT provides an innovative research and development platform to build on, and mature, the Total Learning Architecture (TLA). FLUENT implements an adaptive recommendation system that evaluates xAPI statements within a Learning Record Store (LRS) to collect details about learning interactions across different sequences of learning events. These “Learning Episodes” include specific information about learning events, their effectiveness for different types of users, and the context of each learning event (e.g., the string of learning events that preceded it). This information allows FLUENT to tailor the delivery of content to enable students to learn more efficiently with less time wasted on poorly chosen material. As part of this year's work, FLUENT will be identifying, implementing, and evaluating candidate standards and specifications that it requires to interoperate with other components of the TLA.

Major Deliverables

  • Developer guide with meta-data
  • Candidate standards and specifications
  • Mature algorithms and candidate specifications for interoperability with other recommender systems

Project Details

Period of Performance: FY16-FY19

External Performers: Soar Technology, Inc.

Contract: W911QY-16-C-0019


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