ADL R&D Foundational Projects

For over a decade, ADL has been at the forefront of exploring how to optimize learning through R&D efforts grounded in developing technologies to empower the warfighter. The following projects reflect key areas of research that ADL has undertaken which have culminated into the groundbreaking work of the future learning environment and DoD Learning Enclave.

Legacy Efforts

The Sharable Content Object Reference Model (SCORM®) was created in 2000 by ADL to address e-learning interoperability, reusability, and durability challenges. ADL designed SCORM to leverage standard web technologies as well as emerging learning technology specifications. SCORM is now considered a legacy collection of specifications and standards that enables self-paced, asynchronous distributed learning that is delivered through a web browser. While outdated, many standards within SCORM were recently renewed by the IEEE in order to maintain SCORM as a standard.
Learn more at: Sharable Content Object Reference Model (SCORM®)

Learning Data Measurement, Handling, Analysis, and Visualization

Improved measurement, storage, analysis, and remediation of learner performance is the lynchpin to ADL’s future learning vision. The following ADL projects have laid the groundwork to provide for safe management, testing, and reporting of data to facilitate interoperability ad analytics to enable customized and responsive education and training opportunities. Data-driven learning enables real-time adaptations and will enable organizational adaptability at higher levels.

• Identity, Credentials, Access (FICAM)

• Hyper-Personalized Intelligent Tutor (HPIT)

• Integrating Human and Automated Tutoring (IHATS)

• Privacy Support for the TLA (PS4TLA)

• Range Experience Acquisition Portal for Evaluation & Reporting (REAPER)

• xAPI Data Visualizations (DAVE)

• Fast Learning from Unlabeled Episodes for Next-Generation Tailoring (FLUENT)

Learning Technology Applications and Platforms

ADL’s R&D projects have explored ways to improve learning through a student-driven approach. This entails leveraging data and technology to provide personalized learning experiences based on learner needs, skills, and performance.

• PERLS 3.0

• PeBL

• Learning Technology Warehouse

• Mars Game

• MathCraft

• Navigator for Integrated Learning Experience (NILE)

• Open Social Learner Model (OSLM)

• Perceptual and Adaptive Learning Modules (PALMs)

• Sen$e Mobile App

• Sero!

• Virtual World Framework

Learning Science

Effective application of learning science can enhance all aspects of the previously outlined vision, and to be clear, the use of iterative, evidence-based learning science methodologies is a critical enabler of those elements.

• DL Capability Maturity Model (DL-CMM)

• Mobile Training Implementation Framework (MoTIF)

• Modernizing Learning

• Science of Learning (SOLAR)

Policy

ADL provides policy support surrounding the DoD Instruction 1322.26, identifies unifying needs and strategies across the distributed learning community, and creates best practices for other agencies to follow.

• DoD DL Gaps

• Flash End-of-Life Response