ADL conducts research, development, test, and evaluation to provide learning science, specifications, guidance and best practices, and technology applications to the DoD, Federal agencies, and coalition military partners.
ADL uses a multilayered approach to identify research thrusts. First, we use bottom-up methods to collect requirements from our stakeholders. This includes collating existing requirements publications, crosswalking Defense and Government agency needs, and soliciting new requirements, e.g., by interviewing stakeholders. Second, ADL integrates top-level strategic guidance from sources such as White House, Congress, Defense, and Department of Education reports. Finally, we actively monitor emerging science and technology trends from industry and academia, scouting for new techniques or tools that could enhance distributed learning.
ADL’s R&D team is separated into two overlapping subteams: Internal R&D and External R&D. Comprised of ADL staff, the Internal R&D team directly creates science and technology deliverables, which are government-owned and vendor neutral. Alternatively, ADL researchers and engineers supporting the External R&D team manage R&D projects that are executed by external vendors via our Broad Agency Announcement. Internal and External projects often inform one another, and, over time, several successful smaller-scale projects may grow into a broader, more comprehensive solution.
ADL research focuses on the following six general areas:
e-Learning (web-based learning) – Research technical components and techniques to develop and support electronic-based education and training. This includes R&D on the creation, delivery, and tracking of web-based learning content in a consistent and interoperable way; best practices for e-learning policy and processes; and various components for supporting web-based learning, such as content and learning management systems, content registries, and Massive Open Online Courses.
Mobile learning and mobile performance support – Research focused on the use of commercially-available handheld computing devices to provide access to learning content and information resources by leveraging ubiquitous mobile technology for the adoption or augmentation of knowledge, behaviors, or skills through education, training, or performance support.
Learning analytics and performance modeling – Research in the collection, measurement, analysis, and reporting of data, which may include “big data,” about learners and their contexts, for purposes of understanding, optimizing, and predicting learning success. Other topics under this category may include competencies, credentialing, learner profiles, data visualization, open/social learner models, and associated privacy and information security concerns.
Learning theory – Research focused on the application, evaluation, and embedding of efficient and effective, current, new, and emerging theories of learning, learning science, instructional technology, and tutoring to the design, prototyping, and evaluation of primarily digital learning technologies. This research is pervasive, touching all aspects of research and development performed by ADL.
Total Learning Architecture infrastructure (TLA) – Research focused on modernizing the platforms used for education and training, to interoperability of disparate systems so they can be used together as a Service Oriented Architecture (SOA) to securely share relevant learning data including, but not limited to, granular learning experience information, competency frameworks, learner profiles and metadata about learning and training content.
Web-based Virtual Worlds and simulation (VWs) – Research into the emerging fields of serious games, simulations, and virtual reality (within a distributed learning context) for the purpose of providing rich interactive content, delivered to remote learners, allowing these learners to exercise skills that are either too costly, complex, or dangerous to practice in real life.