qualification. It might be decided, for example, that for soldiers to receive a live-fire
qualification rating of Marksman, they must shoot an LMTS ALT-C (for rifle), or LMTS
APQC (for pistol), score associated with a predicted 80% probability of successful
qualification on the range (i.e., 30 for rifle; 86 for pistol). Analogous standards could
also be set for Sharpshooter and Expert for each weapon.

Given the apparent lack of live-fire AQPC difficulty, it should be noted that for
pistol shooters a Go/NoGo qualification prediction can be made without the use of
LMTS APQC scores and still achieve about a 94% degree of predictive accuracy, as
shown in Table 2 for our sample. Thus, an LMTS-based prediction would not be
warranted unless a commander's unit pistol marksmanship qualification goal is higher
than 94%. If this were the case, then LMTS-based predictions would be necessary to
identify the specific soldiers in need of remedial/sustainment training. Caution is
recommended in the use of pistol predictions associated with the Marksman level because
these predictions extend well beyond the lower end of the obtained pistol score
distribution. Although it is assumed that the obtained relation between LMTS-based and
live-fire scores for pistol extends to areas of the distribution in which data are lacking,
such an assumption can be risky (Hays, 1963) and, therefore, in need of further
examination.

Until then, the suggested competency-based delivery strategy for LMTS-based rifle
and pistol marksmanship training, with empirically derived live-fire performance
standards serving as its basis, should enable the USAR to take a substantial step forward
in its ongoing commitment to meeting the Total Army readiness challenge through more
productive home-station small arms marksmanship training and evaluation while saving
precious time and ammunition in the process.

12



and less than a 10% chance of qualification at the Expert level (Column 5). A soldier
with an LMTS score of 30 would be predicted to fire 31 on the range and have an 80%
chance of qualifying Marksman, a 30-40% chance of qualifying Sharpshooter, and a 10-
20% chance of qualifying Expert, and so forth.

Table 1.
LMTS-Based Predicted Chances of First-Run Qualification at Marksman (=26 hits),
Sharpshooter (>33 hits), and Expert (>38 hits) Levels on ALT-C.

Predicted Chances of a Live-Fire Score of... _

LMTS = Qualification

Score Score >26 (Marksman) >33(Sharpshooter) > 38 (Expert)
3 19 10 - -
8 21 20 - -
13 23 30 - -
16 25 40 - -
18 25 - 10 -
19 26 50 - -
23 28 60 - -
24 28 - 20 -
26 29 70 - -
28 30 - 30 -
29 30 ~- - 10
30 31 80 _ -
31 31 - 40 --
34 33 ad - 20
35 33 - 50 -
36 34 90 - -
38 35 - 60 -

39 ne

Experiment 2: Pistol
Experiment 2 examined the relation between LMTS- and live-fire-based
qualification scores fired with the M9 pistol. The investigative paradigm was similar to
that used in Experiment 1.
Method
Participants
Eighty-one soldiers from an Idaho Army National Guard armor brigade voluntarily

participated in the research as part of their yearly pistol qualification firing at Orchard
Range near Boise, Idaho. None of these soldiers had ever fired with LMTS.



FOREWORD

The United States Army Reserve (USAR) is looking for more effective and efficient
ways to train and evaluate small arms marksmanship through the use of training devices. To this
end, and at the request of the U.S. Army Reserve Command (USARC), the U.S. Army Research
Institute (ARI) has been working in partnership with the USAR's 84th Institutional Training
Division (DIVIT) and Small Arms Training Team (SATT) to develop and evaluate device-based
(ie., the BeamhitTM Laser Marksmanship Training System [LMTS)) rifle and pistol
marksmanship training programs for use at home station (i.e., reserve centers). The common
goal of this cooperative effort is to field companion programs that will produce rifle and pistol
marksmanship proficiency levels that meet, or exceed, unit readiness requirements while
minimizing the resources needed to do so.

To date, both the rifle and pistol programs have been developed and plans are underway
to answer questions about their payoff. A necessary step in the implementation of these plans is
to determine the relation between LMTS- and live-fire-based marksmanship performance and, if
found to be of sufficient magnitude, develop a tool for trainers to use in predicting the latter from
the former. This report describes the research conducted first to assess this relation and then to
develop the LMTS-based tools for predicting both rifle and pistol record fire qualification scores.

This research was conducted by the ARI-RCTRU, whose mission is to improve the
effectiveness and efficiency of Reserve Component (RC) training through use of the latest in
training technology. This research is supported under Work Package XI, "Maximizing Payoff of
Reserve Training," of ARI's Science and Technology Program for Fiscal Year 1999.

This research was sponsored by USARC under a continuing Memorandum of
Understanding initially signed 12 June 1985. Findings have been presented to Deputy Chief of
Staff for Training, Training and Doctrine Command (TRADOC); Director, USARC; and Deputy
Chief of Staff for Operations, USAR 84th DIVIT.

WW. dernecctiad

Z| M. SIMUTIS
Technical Director



References

BeamHitTM (1999). Marksmanship training that works (Brochure). Columbia, MD:
Author.

Commander, Small Arms Training Team (1999a). M16 rifle LMTS (Laser Marksmanship
Training System) course of instruction ( COI). Forest Park (Fort Gillem), GA:
Author.

Commander, Small Arms Training Team (1999b). M9/M11 pistol LMTS (Laser
Marksmanship Training System) course of instruction (COI). Forest Park (Fort
Gillem), GA: Author.

Dulin, E. G. (1999, January-February). BEAMHIT: This marksmanship training system
uses lasers and can go anywhere. Armor, 44-46.

Evans, K. L. (1988). Development and evaluation of the multipurpose arcade combat
simulator (MACS): A research summary (Res. Rep. 1292). Alexandria, VA: U.S.
Army Research Institute for the Behavioral and Social Sciences. (ADA 130099)

Evans, K. L., Dyer, J. L., & Hagman, J. D. (in publication). Shooting straight: 20 years of
rifle marksmanship research (Special Rep. 44). Alexandria, VA: U.S. Army
Research Institute for the Behavioral and Social Sciences.

Government Accounting Office Report to Congressional Committees. (1995). Army
National Guard combat brigades’ ability to be ready for war in 90 days is uncertain.
(GAO/NSIAD-95-91 Army National Guard). Washington, DC: Government
Accounting Office.

Hagman, J. D. (1998, Sep-Oct). You asked, we listened: A software tool for predicting
live-fire scores from device-based scores. Armor, CVII, 28-29.

Hagman, J. D. (2000). Basic rifle marksmanship training with the Laser Marksmanship
Training System (Res. Rep. 1761). Alexandria, VA: U.S. Army Research Institute
for the Behavioral and Social Sciences.

Hagman, J. D. (in publication). Using devices to predict live-fire: A tool for the
marksmanship trainer. Infantry.

Hagman, J. D. & Phelps, R. H. (1999). Research pays off for the reserve component: U.S.
Army Research Institute products from 1985-1998 (Special Report 32). Alexandria,
VA: U.S. Army Research Institute for the Behavioral and Social Sciences.
(ADA361095)

Hays, W. L. (1963). Statistics. New York: Holt, Rinehart & Winston.

13



Table 3.
LMTS-Based Predicted Chances of First-Run Qualification at Marksman (> 80 score),
Sharpshooter (> 120 score), and Expert (> 160 score) Levels on APQC.

Predicted ____Chances of a Live-Fire Score of ...
LMTS = Qualification : : :
Score Score >80 (Marksman) >120(Sharpshooter) 2 160 (Expert)
6 57 20 - -
21 66 30 - -
34 73 40 _ --
46 80 50 - ~
55 85 - 10 -
58 87 60 - ~
71 94 70 - -
75 97 _ 20 -
86 103 80 _ -
90 106 - 30 -
103 113 - 40 -
107 115 90 - -
115 120 ~ 50 --
123 125 - - 10
127 127 - 60 -
139 134 - 70 -
144 137 _ - 20
155 143 _ 80 --
159 146 - - 30
172 153 “ - 40
175 155 - 90 -
184 160 - -- 50
ee
Discussion

These findings indicate that (a) a positive linear relation exists between simulated
rifle, as well as pistol, marksmanship performance on LMTS and live-fire marksmanship
performance on the range, and (b) this relation is both consistent and of sufficient
magnitude to support development of an easy-to-use LMTS-based tool for predicting the
probability of first-run, live-fire qualification at the Marksman, Sharpshooter, and Expert
levels for both rifle and pistol.

Application.
The rifle and pistol LMTS-based prediction tools can serve as diagnostic instruments

for meeting the current research objectives of (a) identifying soldiers most in need of
remediation/sustainment training, (b) signaling when enough such training has been

10



and trigger squeeze) and pistol (grip, aiming, breath control, trigger squeeze, target
engagement, and firing position), as well as support the training of shot grouping and
weapon battlesight zeroing procedures associated with the former, (b) ensure training
produces proficiency levels that are equal to, or greater than, those produced by
traditional training methods, and (c) develop an LMTS-based rifle marksmanship
Alternate Qualification Course (ALT-C; Headquarters, Department of the Army,1989)
and an LMTS-based Alternate Pistol Qualification Course (APQC; Headquarters,
Department of the Army, 1988) that will identify soldiers most in need of sustainment
training, signal when enough such training has been provided, and permit LMTS-based
qualification firing in place of live-fire qualification firing when outdoor range facilities
are not readily available.

Figure 1. LMTS computer/monitor, sample electronic target,
and laser transmitter with attached mandrel.

Some of the above objectives have already been met while others are either under
development or being planned. Both rifle (Commander, SATT,1999a) and pistol
(Commander, SATT, 1999b) programs of instruction (POIs), for instance, have been
completed. The rifle POI has undergone field testing and, according to preliminary
results (Smith, in publication), is capable of supporting both efficient and effective
training. In contrast, the pistol POI, has yet to be formally evaluated. It does, however,
closely parallel the POI developed for rifle in both procedure and content and is,
therefore, expected to deliver comparable results.

LMTS-based training has received other quantitative support as well. A recent
investigation conducted at Fort Benning, GA (Hagman, 2000), has shown that LMTS is
superior to traditional devices (i.¢., the dime [washer], target [shadow] box, Multi
Purpose Arcade Combat Simulator [MACS] [e.g., Evans, 1988; Purvis & Wiley, 1990;
Schroeder, 1986], and the Weaponeer [Schendel, 1985; Schendel, Heller, Finley, &
Hawley, 1985]) in training certain aspects of basic rifle marksmanship (BRM). Hagman
reported that LMTS-based instruction during the early stages of BRM training
significantly reduced the number of rounds expended during subsequent live-fire shot
grouping and weapon zeroing exercises, and increased the number of hits on known-
distance targets.

While other research is examining the long-term retention benefits of LMTS-based
training and the relative effectiveness of this training compared to that of traditional



PREDICTING RIFLE AND PISTOL MARKSMANSHIP PERFORMANCE WITH THE
LASER MARKSMANSHIP TRAINING SYSTEM

CONTENTS.

INTRODUCTION

EXPERIMENT 1: RIFLE o...escssecssssssssssssesssssescsnesessesacenenecscneensanesssnssssatissssncsssscscseraeneneneneasesees 3

Participants
Procedure ..........
Analytic Approach

RESULTS ....csessssesstcsecsessescvesscsssssccsecsssssccssesncasccuecuscnuecusenucaussnsanssnssnssncencaecsneseanenncnucanenagensanesseans 4

Group 1 Data (N = 48) ..
Group 2 Data (N = 47) .
Pooled Data

EXPERIMENT 2: PISTOL .......sscsssssssssssssessesssssesseceseesccaeeneeseeaeececaesessessesnseesensnseassseanennsanennenee 6
METHOD ...eeeeseecesessesesesescscecsecscscccecesescssscsessseeesscsesesesessaeseeensescecesesseessesesssnsnssnasaenenencaneagenseneeees 6
Participants

Procedure ....
Analytic Approach

RESULTS

Group 1 Data (N= 40) .
Group 2 Data (N= 41) .

Pooled Data
DISCUSSION .ccssssssesssscssessesssscsseccnsccsnecsscsssscsscssscssssessecasecsnssaccusecnccnsessscancaucencesnssseesessaseavenneges 10
REFERENCES o...scsccscsssssssscssesssenscesccsscuessscsucsscsucsnecsscaceaeesecsequssncnseanauesucenssesessuseesacensenennennenngs 13

ix



PREDICTING RIFLE AND PISTOL MARKSMANSHIP PERFORMANCE WITH
THE LASER MARKSMANSHIP TRAINING SYSTEM

EXECUTIVE SUMMARY

Research Requirement:

To develop a Laser Marksmanship Training System (LMTS)-based tool for
predicting live-fire marksmanship qualification performance for both rifle and pistol.

Procedure:

Idaho Reserve Component (RC) soldiers fired for record on LMTS and on the live-
fire range with either the M16A2 rifle (N = 95) or M9 pistol (N = 81). Live-fire
qualification was fired on the Alternative Qualification Course for rifle (ALT-C) and for
pistol (APQC), whereas LMTS-based qualification was fired on simulated versions of the
same courses of fire. Separate regression analyses were performed to identify the relation
between the LMTS- and live-fire-based qualification scores found for each weapon. The
identified relations were then used to develop weapon-specific, LMTS-based tools for
predicting the probability of soldier live-fire qualification.

Findings:

A statistically significant relation between LMTS and live-fire qualification scores
was found and validated for both rifle (r = .55) and pistol (r = .47). Based on these
obtained relations, weapon-specific tools were developed to enable RC marksmanship
trainers to predict the probability of individual soldier, first-run, live-fire qualification
based on scores fired on LMTS.

Use of Findings:

Use of the developed rifle and pistol prediction tools will enable RC marksmanship
trainers to schedule LMTS-based training more efficiently by targeting only those
soldiers in need of remediation (i.e., those predicted to be unlikely first-run, live-fire
qualifiers), as well as to identify when enough training has been provided (i.e., when the
predicted likelihood of live-fire qualification is good). These tools also provide the RC
unit commander with a set of LMTS-based, empirically derived live-fire performance
standards to support (a) implementation of a competency-based rifle, as well as pistol,
sustainment training program of instruction using LMTS, and (b) use of LMTS-based
qualification firing in place of live-fire qualification firing when outdoor range facilities
are not readily available.

vii



provided, and (c) providing device-based, live-fire performance standards for enabling
the substitution of LMTS-based qualification firing for live-fire qualification firing when
outdoor range facilities are not readily available. In doing so, these tools can form the
basis for competency-based delivery of the USAR's newly developed rifle and pistol
marksmanship POIs.

Figure 2 shows, in flowchart format, how this competency-based delivery approach
would work. Soldiers would first be pretested by firing LMTS ALT-C (for rifle) or
LMTS APQC (for pistol). Based on their obtained pretest scores, soldiers would receive
either a "Go" or "NoGo" depending upon the LMTS-based cutoff score fired, with this
cutoff score set beforehand by the unit commander. Say, for instance, that the cutoff
score on the LMTS pretest is set at 30, the score associated with an 80% probability of
live-fire qualification at the Marksman level for rifle, or at 86, the score associated with
an 80% probability of live-fire qualification at the Marksman level for pistol. Soldiers
firing at or above these cutoff scores would receive a Go and be considered device-
qualified. Soldiers firing below the cutoffs would be identified as needing remediation
(to be delivered via the USAR's LMTS-based rifle or pistol sustainment training POT).
Thus, remediation is provided only for those in need of it, thereby, making the most of
valuable training time while saving range time and ammunition in the process. Those
completing remediation would then be posttest on LMTS ALT-C for rifle or LMTS
APQC for pistol. Those receiving a Go on the posttest would be considered device-
qualified, whereas those receiving a NoGo would undergo further remediation until they
are able to meet the posttest cutoff score and its associated live-fire expectancy standard
of 80% probability of live-fire qualification.

Pre/Posttest +,

NoGo__} Train

Go

Device
Qualified

Figure 2. Flowchart of delivery strategy

The rifle and pistol prediction tools also provide empirically derived sets of
marksmanship performance probabilities for use in determining live-fire qualification
standards on LMTS. Such standards, in the form of cutoff scores, would be required to
support a decision to use LMTS scores in lieu of live-fire scores for purposes of yearly

1



Predicting Rifle and Pistol Marksmanship Performance
With the Laser Marksmanship Training System

Introduction

The delivery of basic small-arms marksmanship training has been a challenge for the
U.S. armed forces since the days of the Continental Army (Government Accounting
Office, 1995). Despite modern weaponry and an accumulated body of time-tested
training methods (Evans, Dyer, & Hagman, in publication), the challenge today seems no
less formidable than at any time in the past. Budget cuts, coupled with increased
ammunition costs and reduced access to live-fire ranges, have all but mandated the use of
cutting edge technology to meet current marksmanship training standards (Krug &
Pickrell, 1996). In the Reserve Component (RC), budget cuts and range access problems
are exacerbated by ever-present training time constraints (Hagman & Phelps, 1999), plus
the necessity for conducting most training at home station where live-fire range facilities
are often not readily available.

These considerations have prompted the U.S. Army Reserve (USAR) to search for
more effective and efficient ways to train and evaluate small arms marksmanship through
the use of training devices (San Miguel, 1998). The objective of this search is the
development and evaluation of indoor (i.e., home station), device-based rifle and pistol
marksmanship sustainment training programs that will produce proficiency levels that
meet or exceed unit readiness requirements while minimizing the resources needed to do
so (Plewes, 1997, Oct 9). This objective is currently being pursued through a partnership
involving the U.S. Army Research Institute (ARI) and the U.S. Army Reserve
Command's (USARC's) marksmanship executive agent (i.e., the 84th Institutional
Training Division [DIVIT]) and Small Arms Training Team (SATT).

Based on a relative capabilities analysis of candidate training devices conducted by
USARC (Memorandum for Record, 1997, Dec 14), the device selected to support small
arms marksmanship training is the Laser Marksmanship Training System (LMTS;
BeamHitTM, 1999). LMTS is a laser-emitting device, designed for indoor use, that
enables targets to be engaged with Army-issue weapons without the use of live
ammunition. Different versions of LMTS have been developed for rifle (M16A1/A2)
and pistol (M9). In both versions, the major components include a laser transmitter, a
mandrel to which the transmitter is attached/aligned, a variety of laser sensitive targets,
and a dedicated computer with optional printer (Figure 1). One end of the mandrel holds
the laser transmitter and the other end slips into the barrel of the weapon. For both rifle
and pistol, vibrations from the weapons' (mechanical) firing mechanism activate the laser
when the weapons are dry fired, and the location of the emitted beam is first "picked up"
by the laser-sensitive target(s) (Dulin, 1999) and then recorded and stored on the
computer for future analysis and printout.

Current plans call for using LMTS technology to develop device-based rifle and
pistol marksmanship sustainment training programs that will accomplish the following:
(a) train marksmanship fundamentals for rifle (steady position, aiming, breath control,



Technical Report 1106

Predicting Rifle and Pistol Marksmanship
Performance With the Laser Marksmanship
Training System

Monte D. Smith
L-3 Communications

Joseph D. Hagman
U.S. Army Research Institute

October 2000

United States Army Research Institute
for the Behavioral and Social Sciences

Approved for public release; distribution is unlimited.

corms gy 00



LMTS-based ALT-C Firing. LMTS ALT-C firing was conducted in a tent set up
next to the live-fire range and followed the same procedures used for live fire. All LMTS
rounds were fired under a dry-fire mode wherein shooters used their trigger-pulling hand
to re-cock the weapon after each round by recycling the charging handle located at the
rear of the upper receiver assembly. A total of seven officers and NCOs from the 34°
DIVIT and SATT supervised the conduct of LMTS-based ALT-C firing procedures,
whereas target scoring was done automatically by the device.

Analytic Approach

The objective of the current research was to determine the relation between LMTS-
and live-fire-based rifle ALT-C scores. To do so, a split-group, cross-validation design
(Tatsuoka, 1969) was followed whereby the sample of 95 soldiers was initially divided
randomly into two subgroups (Norusis, 1993). Group 1 was used to develop a prediction
equation between device and live-fire scores. This equation was then applied to Group 2
soldiers to see if their live-fire scores could be predicted successfully from an equation
based on Group 1 data.

Results
Group 1 Data (N = 48)

For Group 1, LMTS hit scores ranged from 5 to 39 (M = 27.96, SD = 9.08). Live-
fire hit scores ranged from 14 to 39 (M = 29.33, SD = 7.32. A least squares regression-
based prediction equation of the form Y' = B, + Bi(X:) was developed in which Y' was
the predicted live-fire criterion score, By was the intercept (or theoretical live-fire score
when the LMTS score equals zero), B; was the empirically derived regression coefficient
linking changes in the live-fire criterion variable with changes in the LMTS predictor
variable, and X; was the obtained LMTS ALT-C score. A significant linear relation, Y' =
16.44 + .46(X:), SE = 6.07 was found between LMTS and live-fire performance, F(1, 46)
= 22.39, with the rejection region for this and all other analyses equal to .05. In addition,
the correlation (r = .57) between predicted and actual live-fire scores was significant.
Thus, Group 1 LMTS scores were both linearly related to, and reasonably good
predictors of, ALT-C live-fire performance.

Group 2 Data (N = 47)

For Group 2, LMTS hit scores ranged from 14 to 40 (M= 29.13, SD = 7.71. Live-
fire hit scores ranged from 13 to 40 (M = 31.17, SD = 6.59). Following cross-validation
procedures described by Tatsuoka (1969), the Group 1 regression equation was used to
predict Group 2 live-fire scores, and then the relative amount of variance accounted for in
each group was compared. A significant linear relation, Y' = 2.57 + .96(X,[predicted]),
SE = 5.70, was found between actual and predicted (from Group 1) live-fire scores for
Group 2, F(1, 45) = 16.49. The resulting correlation (r = .52) was significant, and the
associated Group 2 7” of .27 did not differ significantly from the 7 of .33 found for
Group 1, indicating that the Group 1 prediction equation accounted for a comparable



marksmanship training methods (See Smith, in publication, for the research design.), the
present investigation sought to determine the degree of correspondence between LMTS-
and live-fire-based marksmanship performance for both rifle and pistol. If found to be
sufficiently strong, this relation can be used to (1) identify which soldiers are most in
need of sustainment training (i.e., those predicted to be unlikely live-fire qualifiers), (2)
determine when sufficient sustainment training has been provided (i.e., when the
predicted likelihood of live-fire qualification is good), and (3) predict live-fire
qualification results on the basis of LMTS scores.

Experiment 1: Rifle
Method
Participants

Ninety-five soldiers from an Idaho Army National Guard armor brigade voluntarily
participated in the research as part of their yearly rifle qualification firing at Orchard
Range near Boise, Idaho. None of these soldiers had prior experience firing LMTS.

Procedure

To control for possible sequence effects’, approximately half the soldiers fired live-
fire ALT-C first, and then LMTS ALT-C. The other half fired this sequence in reverse,
with no more than an hour occurring between the two firings under either sequence.

Live-fire ALT-C Qualification. M16A2 rifle qualification firing was conducted in
accordance with procedures stipulated in FM 23-9 (Headquarters, Department of the
Army, 1989) with shot grouping and weapon zeroing accomplished immediately
beforehand. Soldiers shot at paper targets placed 25m downrange (Headquarters,
Department of the Army, 1989; Appendix G). Each target contained 10 silhouettes,
scaled to represent distances of from 50m to 300m. Soldiers first assumed the prone
supported firing position and were given two 10-round magazines with instructions to fire
two rounds at each silhouette. Two minutes were given to fire these 20 rounds (including
the magazine change) and no more than two hits could be scored on any silhouette.
Soldiers then assumed the prone unsupported firing position and were given two
additional 10-round magazines and instructed to fire two more rounds at each silhouette.
Again, 2 min were allowed for firing (including the magazine change) and no more than
two hits could be scored on any silhouette. All scoring was done by members of the
participating unit and verified by the range noncommissioned officer (NCO) in charge
before being entered for record. Hit numbers associated with specific shooting
classifications were as follows: 0-25, Unqualified; 26-32, Marksman, 33-37,
Sharpshooter; 38-40 Expert. All statistical analyses were based on first-run hit scores
(ie., the number of hits obtained on the soldiers’ first qualification attempt).

1 All potential sequence effects for rifle and pistol (sec Experiment 2) were subsequently found to be
statistically nonsignificant (p> .05) and, therefore, no mention of their analysis is provided hereafter.



CONTENTS (Continued)

Table 1.

Figure 1.

. Marksmanship Ratings Obtained on LMTS and Live-Fire APQC ...

. Flowchart of delivery strategy

Page
LIST OF TABLES
LMTS-Based Predicted Chances of First-Run Qualification at Marksman (> 26 hits),
Sharpshooter (> 33 hits), and Expert (> 38 hits) Levels on ALT-C. ..0......0 cece 6

LMTS-Based Predicted Chances of First-Run Qualification at Marksman (> 80 score),
Sharpshooter (> 120), and Expert (> 160) Levels on APQC..

LIST OF FIGURES

LMTS computer/monitor, sample electronic target, and laser transmitter with attached
mandrel 2



Headquarters, Department of the Army. (1988). Combat training with pistols and
revolvers (Field Manual 23-35). Washington, DC: Author.

Headquarters, Department of the Army. (1989). MI6AI and MI6A2 rifle marksmanship
(Field Manual 23-9). Washington, DC: Author.

Krug, R. E. & Pickrell, G. A. (1996, February). SIMITAR sharpens the Guard. Army, 57-
59.

Memorandum For Record. (1997, Dec.14). Small Arms Simulation Training Systems
Comparison. :

Norusis, M. J. (1993). SPSS for Windows Base System User’s Guide Release 6.0.
Chicago: SPSS, Inc.

Plewes, T. J. (1997, Oct 9), Memorandum entitled "U.S. Army Reserve (USAR) Weapons
Training Strategy for the 21st Century.” Author.

Purvis, J. W., & Wiley, E. W. (1990). Trainer's Guide: Personal Computer (PC) Version
of the Basic Rifle Marksmanship Program for the Multipurpose Arcade Combat
Simulator (MACS) (Res. Prod. 90-13). Alexandria, VA: U.S. Army Research
Institute for the Behavioral and Social Sciences. (ADA219302)

San Miguel, D. (1998). USARC weapons training strategy for the 21st Century. The
Officer, 47, 48-49.

Schendel, J. D. (1985, January-February). The Weaponeer and marksmanship. Infantry,
32-35.

Schendel, J. D., Heller, F. H., Finley, D. L., & Hawley, J. K. (1985). Use of Weaponeer
Marksmanship Trainer in predicting M16A1 rifle qualification performance. Human
Factors, 27, 313-325.

Schroeder, J. E. (1986). Light pen marksmanship trainer (U.S. Patent No. 4,583,950
issued April 22, 1986)

Smith, M.D. (in publication). Sustaining rifle marksmanship proficiency in the U.S.
Army Reserve (USAR). Alexandria, VA: U.S. Army Research Institute for the
Behavioral and Social Sciences.

Tatsuoka, M. M. (1969). Selected topics in advanced statistics: Validation studies.
Champaign, IL: Institute for Personality and Ability Testing.

14



Technical Report 1106

Predicting Rifle and Pistol Marksmanship
Performance With the Laser Marksmanship
Training System

Monte D. Smith
L-3 Communications

Joseph D. Hagman
U.S. Army Research Institute

Reserve Component Training Research Unit
Ruth H. Phelps, Chief

U.S. Army Research Institute for the Behavioral and Social Sciences
5001 Eisenhower Avenue, Alexandria, Virginia 22333-5600

October 2000

Army Project Number Personnel Performance
20363007A792 and Training

Approved for public release; distribution unlimited.

iii



Procedure

Live-fire APQC Qualification. M9 pistol qualification firing was conducted in
accordance with procedures stipulated in FM 23-35 (Headquarters, Department of the
Army, 1988). Soldiers fired four separate tables involving the use of paper targets placed
25m downrange. Each target contained an E-type silhouette with scoring rings
(Headquarters, Department of the Army, 1988; Appendix G).

On each APQC table, the first round was fired double action with the remaining
rounds fired single action. On Table 1, which was shot from the standing position, seven
rounds were fired from a single magazine within 21 s. Tables 2-4 used two magazines
and, therefore, required a rapid magazine change. Table 2 was fired from the kneeling
position, with six rounds in the first magazine and seven in the second, and had a time
limit of 45 s. Table 3 used two magazines, each with five rounds, and was fired from the
crouch position with a time limit of 35 s. The fourth table, also limited to 35 s, was fired
from the prone unsupported position and also used two magazines, each with five rounds.

A total of 40 rounds were fired during the APQC (7, 13, 10 and 10 on Tables 1-4,
respectively). Each round could earn up to five points, depending upon which ring on the
target was impacted, yielding a possible score range on the entire test of 0 to 200.
Number of hits could range from 0 to 40. Qualification required a score of at least 80,
plus 24 or more hits. One hundred sixty (or more) points were required for an Expert
rating, 120-159 for a Sharpshooter rating, and 80-119 for a Marksman rating. All scoring
was done by members of the participating unit and verified by the range NCO in charge
before being entered for record. Again, only first-run scores were analyzed.

LMTS-based APQC Firing. The LMTS APQC was conducted in a tent set up next
to the pistol live-fire range and followed the same procedures used for live fire.
Electronic targets, scaled to simulate a 25m distance, were placed 10 ft from the firing
line. All rounds were fired under a dry-fire mode, using a two-hand (fist) grip, wherein
shooters used their support-hand thumb to sweep up and manually re-cock the pistol’s
external hammer after the first round was fired). A total of seven officers and NCOs
from the 84" DIVIT and SATT supervised the conduct of LMTS-based APQC firing
procedures, whereas target scoring was done automatically by the device.

Analytic Approach

As with the rifle investigation, a split-group, cross-validation approach (Tatsuoka,
1969) was used to test for generalizability of the results. To this end, the sample of 81
soldiers was divided randomly into two subgroups (Norusis, 1993). Group 1 was used to
develop a prediction equation between device and live-fire scores. This equation was
then applied to Group 2 soldiers to see if their live-fire scores could be predicted
successfully from an equation based on Group 1 data.



analysis revealed a significant linear relation, Y' = 53.31 + .58(X1), SE = 27.12, F(1, 79)
= 21.81, between the predictor variable (LMTS APQC score) and the criterion variable
(live-fire APQC score). The correlation (r = .47) between LMTS and live-fire scores was
significant, with the former accounting for a little more than a fifth of the variance in the
latter (77 = .216; adjusted 7? = .206).

Table 2.
Marksmanship Ratings Obtained on LMTS and Live-Fire APOC.
[MTSAPQC SS CLive Fire APQ@
Cumulative Cumulative
Number % % Number % %
Expert 40 49.4 49.4 34 42.0 42.0
Sharpshooter 34 42.0 91.4 27 33.3 75.3
Marksman 7 8.6 100.0 15 18.5 93.8
Did Not Q1 0 0.0 5 62 100.0
Tot E1000 8100.0

Based on the obtained regression equation, a trainer can predict that soldiers with an
LMTS ALC-C score (X1) of 46, for example, will, on the average, fire a minimum
Marksman qualification score (Y') of 80. Those with and LMTS score of 115 will, on the
average, fire a Sharpshooter qualification score of 120. And finally, those with an LMTS
score of 184 will, on the average, fire the minimum Expert qualification score of 160, and
so forth. Assuming that the actual probability of firing these predicted qualification
scores will follow a normal distribution, with M/ = 46 and SEina = 27.61 (Marksman), M =
120 and SEina Y = 27.3 (Sharpshooter), and M = 160 and SEina Y = 27.45 (Expert; see
Hays, 163, p. 523), the probability of an individual soldier shooting a qualification score
greater than or equal to 80, 120, and 160 was calculated for a selected range of LMTS
scores by using the ARI Live-Fire Prediction Tool.

Table 3 shows this range of LMTS scores along with their predicted mean
qualification scores and the associated probabilities of shooting greater than, or equal to,
80 (Marksman), 120 (Sharpshooter), and 160 (Expert) during qualification firing. With
this table, a unit trainer can predict that a soldier with an LMTS score of 139 (Column 1),
for instance, would be predicted to fire a qualification score of 134 (Column 2) and have
better than a 90% chance of firing Marksman (Column 3), a 70% chance of firing
Sharpshooter (Column 4), and a 10-20% chance of firing Expert (Column 5). A soldier
with an LMTS score of 155 would be predicted to fire 143 on the live-fire range and have
better than a 90% of firing Marksman, an 80% chance of firing Sharpshooter, and a 20-
30% chance of firing Expert, and so forth.



REPORT DOCUMENTATION PAGE

1. REPORT DATE (dd-mm-yy) 2. REPORT TYPE 3. DATES COVERED (from. . . to)
October 2000 Final September 1999 — August 2000

4. TITLE AND SUBTITLE 5a. CONTRACT OR GRANT NUMBER

Predicting Rifle and Pistol Marksmanship Performance with the Laser DASW01-99-D-0012

Marksmanship Training System

5b. PROGRAM ELEMENT NUMBER

63007
6. AUTHOR(S) 5c. PROJECT NUMBER
Monte D. Smith (L-3 Communications) and Joseph D. Hagman (U.S. A192
Army Research Institute) 5d. TASK NUMBER

207

5e. WORK UNIT NUMBER

CoOL

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER

L-3 Communications

(Link Simulation & Training Division)
10700 Parkridge Blvd, 2" Floor
Reston, VA 22333-5600

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. MONITOR ACRONYM
U.S. Army Research Institute for the Behavioral and Social Sciences
5001 Eisenhower Avenue ARI

ATTN: TAPC-ARI-ID
Alexandria, VA 22333-5600

11, MONITOR REPORT NUMBER
Technical Report 1106

12. DISTRIBUTION/AVAILABILITY STATEMENT
Approved for public release; distribution is unlimited.

13. SUPPLEMENTARY NOTES

14. ABSTRACT (Maximum 200 words): To develop an LMTS-based tool for predicting small arms, live-fire marksmanship qualification
performance, Idaho Reserve Component (RC) soldiers fired for qualification on LMTS and on the live-fire range with either the
MI16A2 rifle (N = 95) or M9 pistol (N = 81). A statistically significant relation between LMTS and live-fire qualification scores was
found and validated for both rifle (r = .55) and pistol (r = .47) and then used to develop weapon-specific tools for RC trainers to use in
predicting the probability of individual soldier, first-run, live-fire, rifle and pistol qualification based on scores fired on LMTS. Use of
these prediction tools will enable RC marksmanship trainers to schedule LMTS-based training more efficiently by targeting only those
soldiers in need of remediation (i.e., those predicted to be unlikely live-fire qualifiers), as well as to identify when enough training has
been provided (i.e., when the predicted likelihood of live-fire qualification is good). These tools also provide the RC unit commander
with a set of LMTS-based, empirically derived live-fire performance standards to support (a) implementation of a competency-based
rifle, as well as pistol, sustainment training program of instruction using LMTS, and (b) use of LMTS-based qualification firing in
place of live-fire qualification firing when outdoor range facilities are not readily available.

15. SUBJECT TERMS
Rifle Marksmanship Training Pistol Marksmanship Training Laser Marksmanship Training System (LMTS)
Reserve Component U.S. Army Reserve

19. LIMITATION OF | 20. NUMBER 21, RESPONSIBLE PERSON
ABSTRACT OF PAGES (Name and Telephone Number)

16. REPORT 17. ABSTRACT | 18. THIS PAGE Joseph D. Hagman

Unclassified | Unclassified | Unclassified Unlimited 22 208-334-9390



U.S. Army Research Institute
for the Behavioral and Social Sciences

A Directorate of the U.S. Total Army Personnel Command

EDGAR M. JOHNSON
Director

Research ‘accomplished under contract
for the Department of the Army

L-3 Communications
Technical Review by

MSG Donald Riley, DCSOPS, 84" Division (Institutional Training)
Jean L. Dyer, U.S. Army Research Institute

NOTICES

DISTRIBUTION: Primary distribution of this Technical Report has been made by ARI.
Please address correspondence concerning distribution of reports to: U.S. Army
Research Institute for the Behavioral and Social Sciences, Attn: TAPC-ARI-PO, 5001
Eisenhower Ave., Alexandria, VA 22333-5600.

FINAL DISPOSITION: This Technical Report may be destroyed when it is no longer
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and Social Sciences.

NOTE: The findings in this Technical Report are not to be construed as an official
Department of the Army position, unless so designated by other authorized documents.


amount of live-fire ALT-C score variance in the two groups. Thus, the predictive model
was found to be valid and, therefore, likely to maintain similar efficiency when used to
predict the live-fire scores of other RC samples.

Pooled Data

The results of the individual group analyses identified and confirmed the presence of
a positive linear relation between LMTS and live-fire performance. For this relation to
be of practical value, however, it should afford marksmanship trainers the capability to
predict which soldiers will fire the minimum ALT-C qualification scores of 26 for
Marksman, 33 for Sharpshooter, and 38 for Expert. To provide the best possible basis
from which to make such predictions, and given the similar outcome of the separate
group analyses, scores from the two groups were pooled (N = 95) and an overall
regression equation was computed.

Regression-Based Prediction Model. For the pooled sample, LMTS scores ranged
from 5 to 40 (M = 28.54, SD = 8.40), with 70.5% of soldiers (67 of 95) firing at least the
minimum qualification score of 26 on their first run (Q1). Live-fire scores ranged from
13 to 40 (M = 30.24, SD = 6.99), with 74 out of 95 soldiers (77.9%) firing Q1. A least-
squares regression analysis revealed a significant linear relation, Y' = 17.16 + .46(X1), SE
= 5.86, F(1, 93) = 40.61, between the predictor variable (LMTS ALT-C score) and the
criterion variable (live-fire ALT-C score). The correlation (r = .55) between LMTS and
live-fire scores was significant, with the former accounting for almost a third of the
variance in the latter (r7 = .303; adjusted 77 = .296).

Based on the obtained regression equation, a trainer can predict that soldiers with an
LMTS ALT-C score (X;) of 19, for example, will, on the average, fire a minimum
qualification score (Y') of 26. Similarly, it can be predicted that, on the average, an
LMTS score of 34 will be associated with the minimum Sharpshooter qualification score
of 33, and an LMTS score of 38 will be associated with the minimum Expert
qualification score of 40”, and so forth. Assuming that the actual probability of firing
these predicted qualification scores will follow a normal distribution, with M = 26 and
SEina Y' = 5.91 (Marksman), M = 33 and SEina Y' = 5.89 (Sharpshooter), and M = 38 and
SEina Y' = 5.92 (Expert; see Hays, 1963, p. 523), the probability of an individual soldier
shooting a qualification score greater than or equal to 26, 33, and 38 was calculated for a
selected range of LMTS scores by using the ARI Live-Fire Prediction Tool (Hagman,
1998, in publication).

Table 1 shows this range of LMTS scores along with their predicted mean live-fire
scores and the associated probability of scoring greater than or equal to 26, 33, and 38
during qualification firing. With this table, a unit trainer can predict that a soldier with an
LMTS score of 26 (Column 1), for instance, will, on the average, fire 29 on the live-fire
range (Column 2) and have a 70% chance of successful qualification at the Marksman
level (Column 3), a 20-30% chance of qualification at the Sharpshooter level (Column 4),

2 Because the actual predicted live-fire score of 45 is outside the range of possible scores, the maximum
possible score of 40 is reported.



Results
Group I Data (N = 40)

For Group 1, LMTS scores ranged from 97 to 195 (MM = 158.73, SD = 23.05),
whereas live-fire scores ranged from 73 to 186 (M = 141.03, SD = 29.92). A least
squares regression-based prediction equation of the form Y' = By + By(X1) was developed
in which Y' was the predicted live-fire criterion score, B, was the intercept, B; was the
empirically derived regression coefficient linking changes in the live-fire criterion
variable with changes in the LMTS predictor variable, and X; was the obtained LMTS
APQC score. A significant linear relation, Y' = 30.25 + .70(X;), SE = 25.56 was found
between LMTS and live-fire scores, F(1, 38) = 15.45. In addition, the correlation (r =
.54) between predicted and actual live-fire scores was significant. Thus, Group 1 LMTS
scores were both linearly related to, and reasonably good predictors of, APQC live-fire
performance.

Group 2 Data (N = 41)

For Group 2, LMTS scores ranged from 81 to 184 (A= 149.39, SD = 25.04),
whereas live-fire scores ranged from 75 to 193 (M = 144.44, SD = 31.23). Following the
same cross-validation procedure used for rifle, the Group 1 regression equation was used
to predict Group 2 live-fire scores, and then the relative amount of variance accounted for
in each group was compared. A significant linear relation, Y' = 38.32 +
.79(Xi[predicted]), SE = 28.37, was found between actual and predicted (from Group 1)
live-fire scores for Group 2, F(1, 39) = 9.44. The resulting correlation (7 = .44) was
significant, and the associated Group 2 adjusted r of .17 did not differ significantly from
the adjusted 77 of .27 found for Group 1, indicating that the Group 1 prediction equation
accounted for a comparable amount of live-fire APQC score variance in the two groups.
Thus, the predictive model was found to be valid and, therefore, likely to maintain similar
efficiency when used to predict live-fire scores of other RC samples.

Pooled Data

The results of the individual group analyses identified and confirmed the presence
of a positive linear relation between LMTS and live-fire performance. For this relation to
be of practical value, however, it should afford marksmanship trainers the capability to
predict which soldiers will fire the minimum qualification scores of 80 for Marksman,
120 for Sharpshooter, and 160 for Expert. To provide the best possible basis from which
to make such predictions, and given the similar outcome of the separate group analyses,
scores form the two groups were pooled (N = 81) and an overall regression equation was
computed.

Regression-Based Prediction Model. For the pooled sample, LMTS scores ranged
from 81 to 195 (M = 154.00, SD = 24.38) with all soldiers firing a score of at least 80, for
a QI rate of 100%. Live-fire scores ranged from 73 to 193 (M = 142.75, SD = 30.45)
with 93.8% of all soldiers achieving Q1 (see Table 2). A least squares regression