Total Learning Architecture:
           1. Introduction
           2. Characteristics that intertwine
           3. Structuring a Total Learning Architecture
           4. TLA, in short

1. Introduction

You probably already know about xAPI from our article on the Learning Record Store (LRS).

It is the new reporting standard issued by the ADL agency and developed to evaluate training and learning activities within the US Department of Defense.

This standard, which exists since 2016, is gradually making its way to corporate learning ecosystems.

Military spending has often paved the way for innovations. We owe them tehcnologies such mobile phones, GPS, virtual reality, mass production of automobiles…which at first were developed for military use before being extended to the general public.

E-learning is no exception. The U.S. Department of Defense is constantly seeking innovation in this area.  It has already brought forth many specifications on current e-learning standards (xAPI, Scorm…).

Today, we want to discuss another concept on which ADL is working. They call it the Total Learning Architecture (TLA).

It is a functional, technical architecture that focuses on the learning continuum.  Much research and publications are still being done on TLA.

This architecture has as main goal to move organizations from a content-centric to a user-centric model.  It also makes it possible to interrupt learning as well as supporting decision and finally, to take into account the all learning experiences (multi-modality).

2. Characteristics that intertwine

To this end, ADL emphasizes the following characteristics for the Total Learning Architecture:

  • Continuous: Career-long, continuous learning replaces the status quo’s stovepipe, episodic learning
  • Blended: Formal education and training, just-in-time support, and informal learning are integrated
  • Enterprise Focused: Education, training, and talent management are considered in concert, holistically
  • Diverse: Disparate learning technologies and methods are interoperable within 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 education and training can be delivered at the point of need
  • Cloud Based: Software services and network-based repositories support flexibility and discoverability

Of course, these characteristics cannot be considered all at once. Which ones you focus on will depend on how mature your company is in their learning strategy.

The key lies in the interoperability and interconnection of the systems making up this ecosystem.

This is why we speak of an architecture and why we have to build the puzzle from different pieces, bearing in mind the objective and the global vision of achieving the above-mentioned characteristics.

At a time when end-users move from one app to another, it would be naive to think that all learning experiences (even at a distance) should take place on a single platform.

3. Structuring a Total Learning Architecture

When starting to implement a Total Learning Architecture strategy, you will face two main challenges.

First, there are many solution providers and you often inherit a pre-built architecture in your company. You don’t always choose the tools that your organization uses.

Secondly, there currently are no solutions on the market that addresses all of these points. For now, to get a Total Learning Architecture, you will need to piece it together by yourself.

This being said, the following diagram may help you start structuring your TLA strategy.

Total learning architecture

The idea is to build your learning environment step by step from Layer 1 to Layer 4.

Aside from the obvious LMS, step 1 here would be to implement a Learning Record Store (LRS) to orderly save all the data of the learning environments.

Next, get the different data sources in xAPI format to communicate with this LRS (step 2).  All this is done while allowing a smooth transition from one app to another via single-sign-on (SSO).

At the very least a good search engine is required before investigating in the implementation of a recommendation engine (AI).

Ideally, one would also need access to a large data warehouse (which is what LRS is) by cross-referencing different types of data.

You certainly know this already, but the more solutions are relevant, the more complex they are.

4. TLA, in short

Nowadays, L&D departments’ pedagogical skills alone are no longer sufficient to come up with a scalable architecture that will last for years regardless of your suppliers.

More and more content sources will come up. You will have more and more different profiles to manage. More and more skills to track and develop. Much of which we don’t know.

It’s however likely that we will discover them in our learning environments through the consistent use of Learning Analytics.

Here lies the main challenge. Having a dynamic system that is the opposite of the static data models of all the LMSs on the market.

The pyramid clearly illustrates that good foundations are necessary to build a sustainable architecture.  An architecture in which future innovations will be easily added.  In the same way, the modularity of this architecture will allow you to save money and limit your risk. Limit your costly dependence to software providers.

To learn more about Total Learning Architectures (TLA), you can refer to the ADL publications about it: