The U.S. military has been implementing simulation-based training systems in an effort to provide more effective training programs with reduced time to train. Integrating emerging technologies such as virtual, augmented, and mixed reality into their training curriculums has become the expectation. Over the past couple of years, the military has focused its attention on future threat training by developing multi-domain environments for more experienced warfighters. This includes Live, Virtual, and Constructive (LVC) assets for operations in complex, dynamic, and uncertain battlespaces.

The Department of Defense (DoD) is investing in a Joint All-Domain Command and Control (JADC2) concept that strives to connect multiple domains (air, land, sea, space, and cyber) into a single interoperable network (Congressional Research Services, 2020). Developing an interoperable Synthetic Training Environment is
challenging and once successful, the amount of data collected in a JADC2 type of environment can be overwhelming. The DoD is working across services to determine how best to manage the data. This presentation describes and illustrates an architecture for analyzing measurable data for assessing warfighter performance that can be collected during training in a natural environment. This data architecture is open, free, portable, containerized, and scalable for real-time monitoring and feedback.

The success of JADC2 training is dependent on relevant and actionable data (Rosenberg, 2020). This presentation identifies relevant data for measuring training effectiveness that provides actionable data for use in training automation, personalization, and adaptation. Research conducted by Hoke et al. (2017) and Dideriksen et al. (2018) validates the methodology of assessing training effectiveness through the combination of task performance measures and physiological signals of cognitive workload. It concludes with a discussion of how this methodology and architecture can be applied to improve training outcomes for individuals and teams for modern warfare in a multi-domain battlespace.

Automated Human-Machine Performance Assessment for the Multi-Domain Battle Space

This is the first of four poster sessions.

**Date & Time:**  Wednesday March 24th,  8-9:30am PDT

**Location:** Poster Session Room 1A

The live poster sessions will happen in our Gather.Town lounge at the designated time. Each session has their own room. Once you click the gathertown button below, you will need to navigate to the Poster Session Room for each session located on the right side of the lounge. Each speaker will be by their poster where you can communicate with them and view their poster by clicking X on your keyboard.

[![](https://assets.underline.io/uploads/markdown_image/1/image/737a34c989ecf3ae95182670d99c072c.png)](https://gather.town/app/5IAViMZXC9ZF4E4l/NAML)

Poster Session 1A

poster

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

Joe Williams

1

SHORT BIO

Presentations

Automated Human-Machine Performance Assessment for the Multi-Domain Battle Space

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