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Meaning-Aligned Record Synthesis for Training Emerging Capabilities (MARSTEC)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-18-C-0338
Agency Tracking Number: N18A-003-0041
Amount: $124,927.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N18A-T003
Solicitation Number: 2018.0
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-04-26
Award End Date (Contract End Date): 2018-10-26
Small Business Information
3600 Green Court
Ann Arbor, MI 48105
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jeremiah Folsom-Kovarik
 (407) 249-0454
 jeremiah@soartech.com
Business Contact
 Laura Schweensen
Phone: (734) 887-7683
Email: proposals@soartech.com
Research Institution
 Georgia Tech Research Institute
 Elizabeth Whitaker
 
250 14th Street, NW
Atlanta, GA 30332
United States

 (404) 407-6656
 Nonprofit College or University
Abstract

Operational experts collect recorded data about emerging tactics, techniques, and procedures (TTPs) from sources such as live and virtual training exercises, and numerous test and evaluation simulations. However, instructional designers cannot easily reuse the recorded data to create new training. Without sufficient access to operational experts, expert knowledge is inaccessible and fragmented, often locked within documents like after-action reports, interviews, test summaries, and accident reports. So, instructional designers need a way to unlock the expert knowledge in written reports and recorded data. SoarTech and GTRI propose a data analytics approach that draws knowledge from written reports to transform recorded data into training content. Meaning-Aligned Record Synthesis for Training Emerging Capabilities (MARSTEC) leverages GTRIs academic leadership in textual analysis and semantic reasoning, combined with SoarTechs Training Analytics research team experienced in data analytics and research application specific to Naval training needs. MARSTEC will deliver the following key capabilities: First, narrative meaning capture unlocks the expert knowledge in text documents such as AARs. Second, aligned recording analysis replaces blind big-data approaches with informed analytics. Third, multimodal training integration supports instructional designers, unit commanders, and individual learners. As a result of our research, MARSTEC will enable fast and effective instruction for new TTPs.

* Information listed above is at the time of submission. *

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