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Total Learning Architecture (TLA)

What’s the TLA?

The TLA project is a research and development activity, sponsored by the ADL Initiative and conducted in collaboration with stakeholders from across the defense community, professional standards organizations, and commercial industry. The TLA project will result in a collection of specifications for accessing and making use of learning-related data.

Organizations that use learning technology to educate and train are facing a new set of interoperability problems. Many new products—including adaptive systems, intelligent digital tutors, real-time data analytics, and interactive e-books—offer dramatic learning benefits. However, these products primarily “stand alone” and work outside of typical browser-based delivery environments controlled by traditional learning management systems. Furthermore, the effectiveness of these “intelligent systems” often depends on their access to data generated by and stored in other systems.

The TLA is intended to provide a framework of specifications to ultimately enable “plug-and-play” interoperability among such learning technologies. That is, the TLA will allow these new products to interoperate with each other, with other existing learning systems, and even human capital management technologies.

More precisely, the TLA will define a set of technical guidelines, APIs, middleware, and data model descriptions that define how training, education, and personnel management technologies “talk” to each other—both syntactically and semantically. The TLA is intended to provide a “plug-and-play” interoperability backbone across these technologies, or, in other words, to characterize and standardize the structure, abstraction, and communication functions of an “internet for learning.”


The volatility and complexity of the evolving security environment place increasing demands on our military workforce. To thrive under these conditions, personnel require a broader set of competencies, higher levels of proficiency in them, and a greater ability to rapidly learn new material to confront novel challenges. In other words, personnel must develop an ever-expanding set of sophisticated, agile knowledge and skills—albeit without significantly increasing training and education time or costs. Each of the US Services, US Joint Staff, and many other federal programs has released publications highlighting this need and, correspondingly, calling for reforms to their learning and personnel development systems (see Raybourn, Schatz, Vogel-Walcutt, & Vierling, 2017 for a detailed summary). Remarkably, these numerous publications generally point towards a shared vision, which includes the concept of a modern “learning ecosystem” comprised of interconnected learning opportunities, supported by technology, driven by data, and integrated with other talent management capabilities.

This envisioned “continuum of learning” includes features such as the following:

  • Continuous: Career-long, continuous learning replaces the status quo’s stovepipe, episodic learning
  • Blended: Formal training and education, just-in-time support, and informal learning are integrated
  • Enterprise-focused: Training, education, and talent management are considered in concert, holistically
  • Diverse: Disparate learning technologies and methods are stitched together into a cohesive ecosystem
  • Learner-centric: Learning adapts to individual and team needs, contexts, and characteristics
  • Data-driven: Learner data from across many sources are aggregated and analyzed to drive decisions
  • Competency-based: Competency frameworks support assessment and guide developmental trajectories
  • On-Demand: Modular training and education can be delivered at the point of need
  • Cloud-Based: Software services and network-based repositories support flexibility and discoverability


The ADL Initiative first introduced the TLA concept in 2013, in a book chapter called, “Learner modeling considerations for a Personalized Assistant for Learning (PAL).” At that time, “TLA” stood for the “Training and Learning Architecture.” The name was updated to “Total Learning Architecture” in 2015, to better acknowledge the blurring boundaries between formal and informal training, education, and experience. Throughout 2015 and 2016, contributors grappled with the TLA concept, as evidenced in papers such as Folsom-Kovarik and Raybourn’s 2016 I/ITSEC article, “Total Learning Architecture (TLA) Enables Next-generation learning via meta-adaptation” and Freed and colleagues’ 2017 MODSIM World submission, “More than the sum of their parts: Case study and general approach for integrating learning applications.”

Concerted development of the TLA largely began in 2016 and culminated with empirical testing in 2017. Results from the first spiral of development are summarized in Gallagher and colleagues’ 2017 I/ITSEC article, “Total Learning Architecture development: A design-based research approach” and detailed in the Institute for Defense Analyses lengthy report, Bridging the archipelago: An assessment of the Advanced Distributed Learning Initiative’s Total Learning Architecture (Gallagher, Barr, & Turkaly, 2018).

Throughout the development process, the ADL Initiative has adopted a multiyear design-based research approach:

Spiral-1 (2015-2017) of the TLA research and development project focused on developing an initial set of 10 APIs consisting of candidate specifications as well as protocols developed specifically for the initial development cycle. During Spiral-1, community stakeholders provided feedback on the functionality of the written specifications, and end-users (active duty personnel) interacted with a prototype reference implementation created from the specifications. Findings suggested that users could learn effectively through this system and data were efficiently shared between devices and a central learning record store.

Spiral-2 (2017-2018) of the TLA project focused on the identification, incorporation, and evaluation of additional candidate standards and specifications. As in 2017, the Special Warfare Education Group (Airborne) hosted the ADL Initiative’s 2018 Total Learning Architecture Test and Demonstration event at their facility in Fort Bragg, NC. This event marked the second empirical trial of a TLA prototype, and it provided researchers with the opportunity to observe its operation under semi-realistic, ecological conditions.

Spiral-3 (2019+) of the TLA will focus on development and refinement of the formal requirements, specifications, and architectural design. The design will shift to a streaming data architecture, and specific emphasis will be placed on the articulation of content metadata, persistent learner profiles, and competency data definitions. Related efforts regarding learning analytics and visualizations, adaptive privacy support, and xAPI profiles will also continue throughout this development cycle.

The Future Learning Ecosystem

“Out-Learn, Out-Think, Win: Future Learning and Development” tells a story about how Defense personnel may learn in the future, using complex interconnected network-based technologies. The video is a fictional depiction of how a future learning ecosystem, or the Total Learning Architecture (TLA) could work. Viewers travel with Staff Sergeant (SSG) Reynolds along her learning pathway from training prerequisites to a culminating exercise, both of which take advantage of distributed learning. SSG Reynolds works through the individualized learning experience at a flexible pace and proceeds on to the collective learning event, which is facilitated by an instructor and connects live and virtual team members to accomplish the mission. The instructor takes advantage of personnel’s competencies and skills, which have been shared and made interoperable across systems. This demonstrates potential efficiencies in cultivating teams for mission success.

This video shows the possibilities in future learning ecosystems, such as the TLA, as well as potential for efficiencies in training and mission successes when the management of our talent and learning are data-driven.


DATASIM Conceptual UX/UI Design Report

2019; Yet Analytics; Black-Plock, Shelly
DATASIM is an open source application that will provide a valid means of producing the datasets necessary to benchmark and stress test the Total Learning Architecture (TLA) and distributed learning acquisitions. Additionally, DATASIM can help learning scientists, ISDs, IT and...

2018 Total Learning Architecture Final Report

2019; Smith, Brent; Gordon, Jerry
The Total Learning Architecture (TLA) program sponsored by the ADL Initiative seeks to develop a set of policy and standards defining the process for developing a learning ecology, where multiple services and learning opportunities (of various modalities and points of...

Total Learning Architecture: Moving Into the Future

2018; IITSEC; Smith; Gallagher; Schatz; Vogel-Walcutt
Increasingly, the defense community requires a continuous, adaptive learning enterprise that delivers the right training, education, and just-in-time support, in the right ways and at the right time. The Total Learning Architecture (TLA), now in its second iteration of development,...

Recommendation across Many Learning Systems to Optimize Teaching and Training

2018; AHFE, Applied Human Factors and Ergonomics; Neville, K.J.; Folsom-Kovarik, J.T.
To help learners navigate the multitude of learning resources soon to become available in the Total Learning Architecture (TLA) ecosystem, a Recommender algorithm will give learners learning resource recommendations. Recommendations will support immediate training needs and provide guidance throughout one's...

Total Learning Architecture Development: A Design-Based Research Approach

2017; IITSEC; Gallagher, P.S.; Folsom-Kovarik, J.T.; Schatz, S.; Barr, A.; Turkaly, S.
Organizations that use learning technology to educate and train are facing a new set of interoperability problems. Many new products - including adaptive systems, intelligent digital tutors, real-time data analytics, and interactive e-books - offer dramatic learning benefits. However, these...

Exploring Assessment Mechanisms in the Total Learning Architecture (TLA)

2017; Chapter in Book - GIFT; Goodwin, G; Folsom-Kovarik, J.T.; Johsnon, A.; Schatz, S.; Sottilare, R.
The focus of this chapter is on the challenges and potential solutions to conducting realtime and long-term assessments of performance, learning, and domain competency in the Total Learning Architecture (TLA). TLA, a distributed learning ecosystem, is being developed by the...

Humans as the Strong Link in Securing the Total Learning Architecture

2017; Applied Human Factors and Ergonomics, AHFE; Maymí, F.; Woods, A.; Folsom-Kovarik, J.
This paper describes a proposed approach, centered on human factors, for securing the Total Learning Architecture (TLA). The TLA, which is being developed for the United States Department of Defense, will rely on large stores of personal data that could...

Total Learning Architecture (TLA) Enables Next-generation Learning via Meta-adaptation

2016; IITSEC; Folsom-Kovarik, J.T.; Raybourn, E.M.
Technology is becoming ever more central to teaching and training. In classrooms, students use intelligent tutors and adaptive tests instead of textbooks and worksheets. In daily life, mobile devices enable blended, on-demand and ubiquitous life-long learning applications. Connected, pervasive media...