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17 July, 2003

ONR Advanced Distributed Learning. The USMC Marksmanship Application. 17 July, 2003. Bill Bewley Allen Munro Greg Chung Josh Walker Girlie Delacruz USC/BTL UCLA/CRESST. 2003 Regents of the University of California. The KMT Project. The Problem

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17 July, 2003

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  1. ONR Advanced Distributed Learning The USMC Marksmanship Application 17 July, 2003 Bill Bewley Allen Munro Greg Chung Josh Walker Girlie Delacruz USC/BTL UCLA/CRESST 2003 Regents of the University of California

  2. The KMT Project • The Problem • Assessment models and tools are needed to help Navy, Marine, and contractor personnel evaluate, design and use Distributed Learning • Project Goals • Develop and test models and tools on real applications • Content knowledge: USMC marksmanship (02-03) • Problem solving: USN EDO (Engineering Duty Officer) training and one other domain (03)

  3. Unqualified Marksman Sharpshooter Expert The First Application: HUEY • HUEY: “UNQ to Expert” • In 2002, about 45% of Marines are shooting lower than Expert • About 2% of Marines are unqualified • About half need two tries to qualify • The goal: Move all Marines to Expert classification

  4. The KMT Plan • Assess and remediate potential unqualified Marines before they reach the firing line—on-line—using USMC and ONR training approaches • Research Questions • What are the critical types of knowledge that affect shooting performance? • To what extent can cognitively-based measures predict USMC rifle shooting performance?

  5. The Payoff • Save time • Save money • Increase shooting scores

  6. What’s Wrong With This Picture?

  7. And What Would Cause This Shot Pattern?

  8. Who Cares? • The answers are important if you want to be a good marksman

  9. Who Cares? • And marksmanship is not easy • A shooter must routinely hit a 19-inch circular area at 500 yards in the prone position

  10. 500 yards: • 1.5 times the distance between the top row of opposite end zones of the LA Coliseum Who Cares? • A 1/16 inch muzzle deflection will cause a miss of over 2 feet at 500 yards

  11. What We Did • Field research • Knowledge acquisition + staff expertise • Develop and pilot test draft assessments • Delivery infrastructure • BTL’s iRides authoring system • BTL’s Battlesight Zero and Databook simulations integrated with the CRESST Knowledge Mapper

  12. Steadiness Prior shooting experience* Device-fire performance Perceptual-Motor Environ-ment Equip-ment Cognitive Affective Variables: The Big Picture Rifle Marksmanship Performance • Training effects* • Aptitude* • Knowledge of shooting* • Confidence • Anxiety* • Attitudes* • Ballistics • Rifle character-istics • Weather • Distance * = attempted to measure in current studies

  13. Marksmanship Inventory Knowledge Assessment • Evaluates prior knowledge, knowledge transfer of fundamentals instruction • Paper or online

  14. Marksmanship Knowledge Mapper • Trainees diagram key marksmanship concepts and relationships • Fundamentals • Shot-to-shot explanation • Data book procedure • Score against a “doctrine” map produced by Quantico WTB staff

  15. Mapper: Fundamentals

  16. Mapper: Shot-to-Shot

  17. Mapper: Data Book Procedure

  18. Shot Group Depiction

  19. Evaluation of Shooting Positions • Assess and correct fundamental problems with shooter’s body position and the resulting impact on performance

  20. Evaluation of Shooting Positions

  21. Affective Measures • Trait worry about qualification trial • Trait anxiety about qualification trial • State worry (pre- and post-qualification) about qualification trial • State anxiety (pre- and post-qualification) about qualification trial

  22. Sample Description SLR = Sustainment-Level Rifle Marksmanship ELR = Entry-Level Rifle Marksmanship

  23. Sample Description

  24. Prediction of Qualification Score(Regression Model)

  25. Prediction of Qualification Score(Perceptual-Motor vs. Cognitive/Affective)

  26. Prediction of Qualification Score(Knowledge)

  27. Working Hypotheses

  28. Working Hypotheses • Three stages of skill acquisition: • Learning, practice, automatic • Cognitive measures should be most sensitive to Marines in the beginning to middle of the learning phase, and less sensitive to those past the mid-learning phase • Psychomotor variables should be the most sensitive to Marines past the initial learning stage

  29. Working Hypotheses

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