Accelerating Knowledge Acquisition for Close Combat Warriors
Navy SBIR 2019.2 - Topic N192-132
ONR - Ms. Lore-Anne Ponirakis - firstname.lastname@example.org
Opens: May 31, 2019 - Closes: July 1, 2019 (8:00 PM ET)
TECHNOLOGY AREA(S): Human Systems
ACQUISITION PROGRAM: Accelerating Development of Small Unit Decision Making (ADSUDM)
OBJECTIVE: To develop an adaptive training system that leverages advances in artificial intelligence and decisions sciences, and incorporates commercially available educational technologies that align with military systems (e.g., Moodle), to accelerate the acquisition of knowledge and increase learning gains with a specific focus on close combat-related tasks.
DESCRIPTION: Rote or mass learning is critical for developing foundational knowledge to support higher order decision making. However, current military education technologies and methodologies are focused on industrial age vs. information age methods of learning. A convergence of key enablers exists to pivot away from the mass industrial age of training and education towards a tailored education and training approach by exploiting the availability of ubiquitous computing, advances in machine learning, and science of learning. Furthermore, opportunities exist that are ideal candidates for use of technologies and approaches (e.g., students awaiting the start of a training course).
Adaptive training approaches, which tailor training to the needs of the trainee, are generally effective at increasing learning outcomes above and beyond traditional approaches [Ref 1]. However, adaptive training systems are typically one-off systems and require specialized personnel to develop training content and curriculum, which is time-consuming and costly to develop and maintain. When rapid knowledge acquisition (mass learning) is required for core knowledge components (e.g., weapons systems), specialized training content and curriculum are unnecessary. Rather, technologies that support easy content creation and adaptive techniques are needed to provide greater learning gains beyond currently used techniques, such as self-study and flash cards.
The overarching goal of this effort is to develop a generalized and domain-agnostic capability for rapid knowledge acquisition. As part of the proof-of-concept, the specific focus is on developing an adaptive training system that aligns with current Marine Corps eLearning ecosystem management systems (e.g., Adobe experience, Moodle), incorporates machine learning, and is guided by learning sciences principles to accelerate the acquisition of close combat-related knowledge – weapon systems, threats, terrain reasoning, military tactics, etc. Authoring, content development and management of adaptive training system must be done by end users with limited expertise (e.g., information technology, instructional design). The key innovation sought is a persistent educational platform /
experience (connected to a Marine Corps eLearning system) that provides an always-available and on-demand capability for learning, and the adaptive algorithms and approaches to support personalized content, feedback and curriculum.
The end state is to increase learning gains and academic outcomes (e.g., passing rates, test scores) by creating opportunities with an always-available and on-demand service (ubiquitous computing) that provides tailored content through macro and micro adaptations. Human Subjects testing is likely needed in Phase II to assess these training effectiveness outcomes. The anticipated skill sets necessary to support this topic are: military close combat relevant subject matter expertise, software engineers, instructional designers, data scientists, human factors, and cognitive psychologists.
PHASE I: Develop early mockups and prototypes for software, and the associated workflow and requirements for supporting standalone or connected activities within a Marine Corps eLearning ecosystem. Initial requirements for data collection should include types of data and methods necessary for conducting a research experiment during Phase II. Phase I deliverables will include: (1) CONOPS / workflow, and requirements for the system employment;
(2) conceptual models and overview of the system and plans for Phase II; and (3) mock-ups or a prototype of the system.
If awarded, the Phase I Option should also include the processing and submission of all required human subjects use protocols as needed for Phase II training effectiveness evaluations. Due to the long review times involved, human subject research is strongly discouraged during Phase I. Phase II plans should include key component technological milestones and plans for at least one operational test and evaluation, to include user testing.
PHASE II: Develop a prototype system based on the Phase I effort, conduct a usability assessment, and perform a training effectiveness evaluation. Specifically, develop an early stage prototype focused on a single task domain to support evaluations and usability testing by military personnel regarding the ability to develop and manage the training – authoring, content inclusion, dashboards, assessments, etc. Recommend and develop / include adaptive training algorithms and approaches. Perform all appropriate engineering tests and reviews, including a critical design review to finalize the system design. Once system design has been finalized, conduct a training effectiveness evaluation with a Marine Corps population. Phase II deliverables will include: (1) a working prototype of the system that is able to interact with existing Deployable Virtual Training Environment (DVTE) system specifications and all necessary source documentation; (2) usability assessment to support workflow and initial utility of the training system; and (3) a training effectiveness evaluation of system capabilities to provide demonstrable improvement to the instructor population (Human Subjects protocol needs to be approved in Phase I Option if needed for this evaluation). A statistically significant improvement from pre- to post-test is the desired outcome of a Training Effectiveness Evaluation in Phase II.
PHASE III DUAL USE APPLICATIONS: Support the Marine Corps in transitioning the technology for Marine Corps use. Develop the software for evaluation to determine its effectiveness in a formal Marine Corps school setting. As appropriate, focus on broadening capabilities and commercialization plans.
Commercially, products such as Quizlet provide some of these learning concepts to civilian users. However, these solutions are not fit for DoD use. Development of affordable, scalable, non-proprietary technologies are needed in order to integrate these accelerated learning concepts across the DoD. Additional considerations that are not addressed by commercial products include encryption and classification. This technology will have broad application in the commercial sector. Software to develop effective instructors and educators rapidly without the need for formal schooling is crucial for businesses worldwide.
1. Durlach, P. J., and Ray, J. M. “Designing adaptive instructional environments: Insights from empirical evidence.” (Technical Report 1297). Arlington, VA: U.S. Army Research Institute for the Behavioral and Social Sciences, 2011. https://apps.dtic.mil/dtic/tr/fulltext/u2/a552677.pdf
2. Landsberg, C. R., Van Buskirk, W. L., Astwood, R. S., Mercado, A. D., and Aakre, A. J. “Adaptive training considerations for simulation-based training.” (Special Report 2010-001). Orlando, FL: Naval Air Warfare Center
Training Systems Division. https://pdfs.semanticscholar.org/de2e/5a6ba00644b665abbfba19db3a7c5c523da3.pdf KEYWORDS: Best Practices; Education; Training; Adaptive Training; Authoring Tool