ADL in Exercises (MADLx)

Enhance military education and training by integrating distributed learning capabilities into joint and coalition training exercises.

The Challenge

Military training exercises are typically large, expensive events. They take months or years to plan and can require weeks to execute. After an exercise concludes, however, it can be difficult to quantify how much the individual participants learned, or to identify what knowledge or skill gaps they might still possess.

The Solution

Supplement military exercises (including joint and international coalition exercises) with distributed-learning opportunities before, during, and after their execution, allowing performance data to be captured and analyzed to derive learning outcomes. This capability can be matured by blending distributed learning and subsequent analytics into a wide array of exercises and training events.

About the Project

The MADLx project has focused on enhancing joint and coalition training exercises by integrating distributed learning into computer-based and live training activities. The benefits include enhanced learning outcomes, increased learning efficiency through improved convenience of instructional materials, and expanded readiness reporting through advanced learning analytics and associated dashboard visualizations. In addition to these technical outcomes, this effort seeks to strengthen international partnerships by executing case studies in collaboration with coalition military organizations.

MADLx project exercises include the following:

April 2018: VIKING 18, a 10-day multinational civil/military staff exercise, was held across multiple networked sites. This represented the first large-scale trial of advanced distributed learning (ADL) in exercise with the MADLx project, retrofitting 26 legacy courses for xAPI.
April 2019: The Combined Joint Staff Exercise 19 (CJSE), organized by the Swedish Armed Forces, replicated the VIKING 18 success while inserting ADL into the exercise management cycle as a formal component of the core exercise planning team.
December 2019: First staff exercise with the National Defense University of Ukraine (NDUU) in Kyiv, and first use of learning analytics via MADLx in a computer-aided exercise simulation environment, incorporating ADL from the US with Joint Conflict and Tactical Simulation software (JCATS).
June 2020: Demonstrated efficiency and effectiveness gains for training with a controlled experiment in another NDUU staff exercise, showing 20% performance increase on training objectives by the treatment group that used the eLearning platforms.
October 2020: Bold Quest 20.2 was the first exercise with Joint Staff J6, and the first event incorporating ADL into a live/constructive exercise, leveraging learning analytics on tactical objectives with sensor data.
December 2020: Returned MADLx to a Joint HQ exercise at NDUU where Return-on-Investment (ROI) learning analytics data were captured simultaneously from multiple learning platforms, including a PeBL eBook.
April 2021: Field tested the MADLx Exercise ROI Dashboard prototype at the Swedish/Finnish staff exercise, CJSE 21.
October 2021: In Bold Quest 21, learning analytics were demonstrated on tactical medical training objectives, comparing the performance of field medics in eLearning pre-training with LIVEX sensor data on the medics' performance against benchmarks for speed accuracy and completeness of patient care.
April 2022: Viking 22 field validated the MADLx Exercise ROI Dashboard prototype and refined the approach for pre-exercise data gathering with xAPI-instrumented e-learning courses, customized Learning Record Store (LRS) and Learning Management Systems (LMS) infrastructure, and an event-specific informational website.

Viking 22 MADLx Capstone

The Viking exercise series was first chartered in 1999 as a Swedish and US initiative at NATO’s 50th Anniversary Summit. Since then, it has become the world’s largest recurring civil-military relations exercise, with 50 countries and 60 organizations participating in 2022. The Viking 22 exercise involved approximately 2,500 people, including 1,300 trainees and additional operators, monitors, and support staff. The exercise was conducted simultaneously in six countries at nine separate locations. Translated into a real-life situation, the training audiences would have led, and commanded operations comprised of up to 80,000 personnel.

For MADLx, the Viking 22 execution was a high-profile demonstration of ADL mainstreaming in an operationally relevant exercise, featuring a complex blend of humanitarian efforts by a civilian United Nations mission in the context of a kinetic NATO operation with a hybrid-threat near-peer opponent.

The ADL Initiative was assigned a dedicated chair in Viking 22’s exercise management core planning team, and the exercise evaluation team for the Viking 22 MADLx Capstone. To set the foundation for regularly capturing the ROI of eLearning during future exercises, MADLx was able to gather Viking 22 participant performance data for comparison with their performance on MADLx-developed analytics-instrumented learning content.