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Training Management and STE: Mapping Squad Level Competencies in

Simulation Data Through a GIFT/TLA Integration

Benjamin Goldberg, Ph.D. U.S. Army Combat Capabilities Development Command-

Soldier Center STTC

Additional Authors: Gregory Goodwin, Ph.D. & Joan Johnston, Ph.D.

Concurrent Presentation SessionBRIDGING ADL AND SIMULATION

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U.S. ARMY COMBAT CAPABILITIES DEVELOPMENT COMMAND –SOLDIER CENTER

Benjamin Goldberg, Ph.D.

Senior ScientistCCDC-SC, Simulation and Training Technology Center

Training Management and STE (Synthetic Training Environment):Mapping Squad Level Competencies in Simulation Data through a

GIFT/TLA Integration

DISTRIBUTION A: This is approved for public release distribution is unlimited.Collaborators: Dr. Greg Goodwin (CCDC-SC), Dr. Joan Johnston (CCDC-SC), Dr. Keith Brawner (CCDC-SC)

Kevin Owens (ARL, UT-Austin) and Kevin Gupton (ARL, UT-Austin)

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ADAPTIVE PEDAGOGY AT THE TEAM LEVELLeveraging Sports and Military Psychology to Accelerate Team Development

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WHAT IS THE GOAL OF A TEAM-AIS?To Take a Team of Experts and to Build an Expert Team!...

…by leveraging sports and military psychology to accelerate team development

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OVERARCHING TECHNOLOGY OBJECTIVE

• Leverage and integrate existing opensource technology to support an experiential training ecosystem based on X-Learning model

– Implement persistent performance tracking across competency model based on SQUAD LETHALITY and TEAM DEVELOPMENT (xAPI)

– Use ecosystem to store STE exercise data for AI and adaptive training optimization and scenario generation (Big Data)

– Maximize AAR and post-STE training efficiencies through directive Training Support Packages based on Unit Deficiencies (Recommender Engines)

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• STE produces Raw Data [TSS] (simulation events [S/SVT, SAMT, IVAS, RVCT, etc.], movement, performance, bio/physio, etc.)

• Raw [TSS] consumed by STE TMT [e.g., GIFT] and produces Metrics (ACTIVE performance states [SPM/IVAS], PASSIVE performance states [MASTR-E], Go/No-Go, TEAM states [STTC research])

• STE TMT generates xAPI (experiential statements on all data context)• xAPI routed to LRS/DataLakes for storage• LRS/DataLakes accessed by Competency and Skills System (CaSS)• CaSS updates Squad Lethality Competencies based on data assertions from

STE TMT• TMT Squad Lethality linked to ATIS/TMT/TLA• Recommender engines target Solider development opportunities and guide

and/or automate plan/prepare scenario generation activities

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STE Exercise A

STE Exercise B

Competency and Skill System - Individual

Warfighter Function (Role)

• K• S• A• s

Leadership

• K• S• A• s

Teamwork

• Adaptability• Resiliency• Communicate

Experience Capture Experience Capture

xAPI

(Mea

sure

s of P

erfo

rman

ce/E

ffect

iven

ess)

TSP Generator/Library

STE TMT Data Lake

xAPI(Measures of Perform

ance/Effectiveness)

Training Strategy Recommender Engine (Solider Development)

Role Functions(each KSA)

• Technique• Mechanics• Consistency

Role in Team Context

• Declarative• Procedural• Interdepend

Team Execute Skills

• Opp Unders• Counter Tac• SA

Competency and Skill System – Team/Unit

Performance

• TTPs• Go/No-Go• Communicate

Teamwork

• Adaptability• Cohesion• Communicate

Mission

• Type• Environment• Enemy Level• Leadership

Present

STE Exercise Generator/Recommender(Objective - T)

Team Compet(each KSA)

• Technique• Mechanics• Consistency

PerformanceGo/No-Go

• Declarative• Procedural• Interdepend

OBJ T Readiness

• Mission Obj• OWT • PMESII

Plan Prepare

Intervention 1 Intervention 2 Intervention 3 Intervention 4

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STE EXPERIENTIAL LEARNING (STEEL) PROJECT (OWENS, GUPTON & GOLDBERG)

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SQUAD ADVANCED MARKSMANSHIP TRAINER (SAM-T):BATTLE-DRILL TRAINING

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EXPERIENCE CAPTURE/INTELLIGENT TUTORING

Weapon:Aim (x,y)Trigger Squeeze

BioHarness:BreathingECGPosture

Performance :Hit/MissCasualtiesRate of Fire

Feedback/Remediation

STE TMT

Expert Marksmen

Models

SAM T

BioHarnessSensor

Weapon

Performance

Eye-Tracking(Nov. 19?)

Raw DataTeam

CoordinationModel

TeamPerformance

Model

Back-Up BehaviorModels

Team/Trainee Model

Coaching Model

Assessment

Total LearningArchitecture

LMS

Learner Record StorexAPI

Competency Framework:SQD Performance Model

Recommender Engine

Universal Trainee Record

Eye Tracking:Gaze/FixationCommunication:NLPOC Input

Scenario Library

DKF Metadata Matching Metadata File

Scenario Request

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SAM TWeapon

Performance

Eye Track

BioHarness

GatewayRaw

AMQDomainModule

TraineeModule

PedModule

LMS

LRS

LOG Offline

Perfo

rman

ceSt

rate

gyStrategy

Ped Request

Trai

nee

Stat

e

PedRequest

xAPI

Strategy

Raw

GENERALIZED INTELLIGENT FRAMEWORK FOR TUTORING (GIFT)

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Presence Patrol

ROE Weapon Control Reporting

xAPI Data Lake

xAPIxAPI

xAPI

Soldier1 Movement

Competency

Soldier1 Shooting

Competency

Competency and Skills System (CaSS) Mapping

Soldier2 Movement

Competency

Soldier2 Shooting

Competency

SquadModel

CaSS Mapping (Unit Level)

CaSS Mapping (BTL Level)

Scenarios create these via GIFTxAPI specifications

(authored by domain experts…Represented in GIFT task model)

Training Managers create these

Training Managers create these

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STE EXPERIENTIAL LEARNING (STEEL) PROJECT (OWENS, GUPTON & GOLDBERG)

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ARCHITECTURE STRATEGY

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Moving Forward…

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• Receive proponent approval to proceed (COMPLETE)• Build Testbed Environment for Data Logging

• Modify API/GIFTadapter for SAM T data formats (COMPLETE)• Incorporate eye-tracking and video/motion capture data sources into modeling efforts

(IN PROGRESS)• Coordinate with operational training test sites identified for pilot data collection

• Fort Benning (Initial Entry Training)• Fort Bragg (Special Operational Forces)• Fort Campbell (Home Station Training)

MOVING FORWARD…

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• Define and Implement a Data Strategy (WE need your help!)• Proper Front-End Analysis with Community of Interest

• Establish analysis Wish List (What questions do you want the data to answer?)

• Establish simulation translation layer via GIFT with specified measures mapped to analysis requirements

• Build xAPI statement structures around GIFT logging schemas• Build Reference Implementation of Squad Performance Model (SPM) in CaSS

• Research individual competency model to support Solider development

• Research team competency model predictive of readiness (Objective – T)• Implement Data-Driven recommender engines

• Training Strategy grounded in sports and military psychology

• Targets accelerated team-development centered on lethality and SPM attributes

MOVING FORWARD…

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THANK YOU FOR YOUR ATTENTION!!!