Research Note 85-72

TOW Gunner Selection

J. A. Cartner,, H. C. Straset, K. L. Evans,

O F. H. Holler, and T. J. Tierney

ARI Field Unit at Fort Benning. Georgia

Submitted by

ARI Field Unit at Fort Benning, Georgia

Seward Smith, Chief

C-,TTraining Research Laboratoryn T

LU Harold F. O'Neil, Jr., Director . -LJ

U. S. Army

Research Institute for the Behavioral and Social Sciences

ThSdcmn a enapoe July 198511 frpublic release and sale; its85 h) 1

distibuionis unlimited. 85 J

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U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

L. NEALE COSBY

ED)GAR M. JOHNSON Colomici. IN

Tcchnical Director Commiundcr

By Oa

copy#

IThis report has been cleared for release to the Defense Technical Information Center (OTICI. it has been given nol

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report are those of the author(s) and should not be construed as on official Department of the Army position, policy. or decision, unleos so designated by other official documentation.
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ARI Research Note 85-72 3 X

4. TITLE (amd Subtitle) S. TYPE OF REPORT & PERIOD COVERED

TOW GUNNER SELECTION September 1977-March 1979

6. PERFORMING ORG. REPORT NUMBER

7. AUTHOR(q) S. CONTRACT OR GRANT NUMBER(*)

J. A. Cartner, H. C. Strasel, K. L. Evans,

F. H. Heller, and T. J. Tierney

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U.S. Army Research Institute, Fort Benning Field AREA & WORK UNIT NUMBERS

Unit, P.O. Box 2086

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IS. SUPPLEMENTARY NOTES

19. KEY WORDS (Contnlue an roverse aids If neessa ad Identify by block number)

Personnel selection-, Anti-tank gunnery ., selectionan

Gumer-selection

ITraining device success'

Training effectiveness and selection' *-. ( /',(

24L ANETRACT (Cotllaw anroveren o. N nf.eoomy and Identify by block nomaber)

S-' Gunner selection was addressed in a" two-stageS fr. )(1) Advanced Infantry Training graduates entering TOW training at Fort Benning were examined

prior to and during training. A number of personal, demographic, and behavioral measures were taken and discriminant analyses were run to try to differentiate trainees who succeeded at training (Qualified on the M-70 simulator)

from those who did not. (2) Subsequently, a 4'*ftest was conducted at the

TRADOC Combined Arms Test Activity (TCATA) in which over 200 soldiers were

trained, and then fired live missiles. Similar demographic data, )(Continued) _

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ARI Research Note 85-72

20. Continued)

tc., were collected on this group and similar discriminant analyses were

performed. The aim of these analyses was to predict/select those gunners who

would actually hit a tank target in live fire. Four separate selection models

were developed: two for training success, and two for live fire success.

Selection models were successfully developed for training on the M-70

simulator. However, the TCATA test showed that M-70 success was not significantly related to live fire success. Attempts to select gunners for the live

fire situation were successful statistically, but the contribution of the selection model was found to be very small in terms of likelihood of successful

gunnery. This is largely due to the fact that unselected and virtually untrained gunners were found to perform very well with the TOW system in the

TCATA test. The test groups achieved hit probabilities, even with minimum

training, which closely approximate the designed system potential. b- , v

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TOW GUNNER SELECTION

CONITENTS

Page

INTRODUCTION AND SUMMARY.......... .........

PROBLEM .. ... ..... ...... .... .. 1

RESEARCH APPROACH...................2

SUMMARY OF FINDINGS.......... .......... 4

~1Selection/Prediction for M-70 Training Success........4

Selection/Prediction for Live Fire Success..........7

M-70 Training vs. Live Fire.................11

Discussion......... .............. 15

TECHNICAL SUPPLEMENT........... ......... 17

BACKGROUND.......... ........... 17

The TOW System..... ...... ........... 1

The Training System...................18

Prediction of Missile Gunnery...............19

METHOD........... ........... .... 23

Selection for TOW Training..................23

Selection for Live Fire..................25

RESULTS...........................28

The M-70OModels.....................29

The Live Fire Models....................34

REFERENCES.......... ........... ... 42

APPENDICES A & B........................43

iii

- *. . .* - .' i - . C - a:%
TOW GUNNER SELECTION

INTRODUCTION AND SUMMARY OF FINDINGS

In the past decade the Army has fielded a new class of anti-armor

weapons for Infantry use. These new weapons differ from the earlier

anti-armor systems in one major respect. While the earlier weapons were

ballistic weapons which required aiming, lead, etc., to hit the target,

-" the new weapons fire wire-guided missiles, which also require continuous

tracking of the target throughout the missile's flight. Thus not only

does the soldier have the usual tasks of target acquisition, sighting,

and aiming, he must also maintain continuous sight alignment on the target to bring the missile to the target. This differs g~reatly from the

"fire and forget" characteristics of the earlier weapons, e.g. - the

Bazooka, and the 90 mm Recoilless Rifle. The heavy anti-tank weapon,

TOW (Tube-launched, Qptically-tracked, Wire-guided), and the medium

range weapon, Dragon, are the two such weapons currently fielded.

* Introduction of these systems into the Army inventory brought to

light a potential training and/or personnel selection problem. It was

believed that the sustained tracking task required considerable special

training and might require abilities beyond the capacity of most Infantry

soldiers. Accordingly, the Training and Doctrine Command (TRADOC) instruct-

-I. ed the infantry School (USAIS) to conduct a series of training effectiveness analyses (TEAs) of these systems and their associated training programs. USAIS subsequently requested research support from the Army Research

Institute - Fort Benning Field Unit, to assist in these TEAs. This research

has been directed toward assistance in design and conduct of the TEA programs and more specifically toward the question of whether gunner selection

techniques were either required or possible for these systems. A specific

work unit was initiated in 1976 to examine the feasibility of development

of selection models for both TOW and Dragon. This report summarizes the

findings of the TOW-related research and presents models developed for

prediction of gunner success in both simulator training and live firing.

Dragon related research will be reported separately.

4.. PROBLEM

TOW training suffers from a constraint not usually found in weapons

systems. This is due to the extreme cost of the missile itself. This

cost is such as to preclude live firing (even of inert rounds) in initial

* training. Only a limited number of missiles are available for demonstration firing in the initial training and for annual practice. This means

that essentially all training must be accomplished without live firing.

To meet this need, the M-70 tracking simulator system was adopted as the

major training device for tracking and as the criterion for successful

17
trainees as well.1 When the M-70 system was adopted for training, essentially nothing was known about the degree to which its use approximated

live firing of the missile system. Similarly, the criterion scores for

use with the M-70 to "qualify" gunners for TOW were developed arbitrarily

and with no known relationship to live fire tracking or hit probabilities.

The M-70 scores are measures of the percentage of time the gunner is ontarget during a tracking period (representing the missile flight time).

Arbitrary cut off scores determine whether the gunner qualifies as Expert,

First Class, or Second Class. This application was based on the assumption

that a gunner who could maintain the sight alignment on target continuously

throughout the track was more likely to hit the target than one who could

not. The concern with training effectiveness and of possible selection of

gunners arose when it was noted that these arbitrary M-70 cutoff scores

were causing a considerable portion of TOW trainees to be classed as

Unqualified. In TOW Trainer classes during 1975-1976 at Forts Polk, Bragg

and Benning, as high as 50% of some classes were found unqualified. While

this percentage was an extreme case, it and similar numbers caused the

TRADOC and USAIS concern with gunner training and selection techniques.

Accordingly, ARI initiated research into the TOW training problems and

the associated question of the feasibility of selection of TOW gunners

to improve training results and, presumedly, subsequent live fire performance. ARI has investigated the development of selection models for the

M-70 training task and for live fire performance of TOW gunners. ARI also

investigated the relationship between M-70 performance and the live fire

performance of gunners.

RESEARCH APPROACH

An initial step in the development of selection models was a detailed

analysis of the TOW gunner's task requirements. This was essential to an

understanding of the physical and psychomotor requirements on the gunner

and was the basis for determination of the gunner characteristics which

might impact on success or failure at the task. From these analyses and

from literature searches, about forty five variables were identified as

being potentially related to gunner performance. These variables include

anthropometric measures (e.g. hand length), demographic measures (e.g.

education), aptitude measures (ASVAB scores), self-report behavioral items

(e.g. smoking), and other behavioral measures (e.g. pursuit rotor performance). (All variables are listed in Appendix A.)

Criterion measures used for the predict ion/select ion model for training

success were M-70 criterion scores. Actual hit/miss results were the

criterion for the live fire prediction model. Radial miss distance for

1 Descriptions of both the TOW system and the M-70 simulator system are

p esented in later sections of the report.

2
live fire performance was also considered for use in this prediction model,

and was investigated in the analyses of the live fire data.

Both training and personal data for the prediction/selection model

for the training (M-70 performance) were collected from 307 soldiers

undergoing TOW training subsequent to AIT at Fort Benning during January

through April 1977. The resultant prediction/selection models are

necessarily based on success in the training program in effect at that

time.

Data for the live fire selection model were collected by the TRADOC

Combined Arms Test Activity (TCATA) during a test of TOW training effectiveness designed by USAIS, TCATA, and ARI and conducted at Fort Hood, TX,

during March through May of 1978.2 Personal characteristics data to be

collected for all gunners were defined by ART as were questionnaires to

address the attitudes of gunners toward the system and the training

programs. Measures of Effectiveness (MOE) collected included the hit/miss

of the live round and the radial miss distance from the center of mass

(RDCM). Different groups of gunner/trainees were trained under different

programs during the TEA, however, the TCATA analysis showed that the training program used had no significantly different effects on the MOE. Therefore, for purposes of the selection model development, all groups were

combined. This yielded a total of 222 soldiers with relatively complete

data on all personal characteristics and on the MOE. For 54 of these

trainees, much M-70 training performance data were also collected; and,

for all 222 personnel, a restricted set of ten M-70 tracks was measured,

either in the first training session, or, for those trained without the

M-70, after live firing.

Development of the selection models for both M-70 performance and

live fire performance followed the same techniques. Data were first

intercorrelated to determine which variables would be most useful in

development of the selection model and to eliminate predictor variables

which were closely correlated with others and thus redundant. Where a

pair of variables was correlated at +.75 or higher, the variable with

least rational relation tc the criterion was eliminated. Multiple correlations were then applied to the data to estimate the degree of predictability of the criterion and relative contribution to that prediction

by each variable. Finally, discriminant analyses were applied to the data

sets with the object being to discriminate between the persons who

surpassed or failed tc meet a defined criterion (those who hit and those

who missed, in the live fire). Details of the analyses specific to each

model development are presented in later sections of the report.

2

This test has been reported in detail by TCATA: Training Effectiveness

Analysis (TEA) - TOW (Part I). HQ, TRADOC Combined Arms Test Activity,

Ft Hood, TX. Sept 1978.

3
SUMMARY OF FINDINGS

Findings are summarized separately for the development of the selection models based on M-70 performance criterion and those based on the

live fire performance.

Selection/Prediction for M-70 Training Success

In developing the selection models for successful M-70 training, the

criterion used was based on the combined performance scores obtained in

the 5 milliradian (Mr) task (Task A)and the 25 Mr task (Task C). This

combined score was used, and Task B was ignored, because preliminary

analyses showed Task Bto be highly correlated with both Tasks A and C,

while these were less highly correlated. Specific criteria were developed

for each of eight possible "training success" levels defined in part by

the then-current levels established on tasks A and C for Expert, First

Class, and Second class gunners. The eight criterion levels were: 1650

points or better; 1500 or better (equivalent to Expert scores on the two

tasks); 1430 or better; 1370 or better; 1300 or better (equivalent to

First Class); 1230 or better; 1170 or better; and, 1100 or better (equivalent '- Second Class). These multiple criteria were developed primarily

* to evaluate the effect of the different criterion levels on the effectiveness of the prediction/selection models. It was also felt that the evaluation might be useful in reassessment or redesignation of qualification

criteria when these data could subsequently be related to live fire performance.

-* Discriminant analyses were performed against each of these eight

criteria using data from 209 cases randomly selected from the 307 cases

available from the Fort Benning Post-AIT TOW training group. The remaining 98 cases were used as a "hold-out" sample for validation of the success

of the discriminant function and its use in classifying these persons.

Two separate models were constructed. The first used initial M-70 training scores (the means of the first four training trials on each of Tasks

A and C) as discriminating variables. The second model includes only

variables available prior to the start of tra'.ning. Each model was

examined in relation to each of the eight criterion levels.

M-70 Included Model Results. The detailed results of the discriminant

analyses with the initial M-70 scores included are presented in a later

section. Table 1 summarizes the results of selection for the criterion

levels corresponding to Expert, First Class and Second Class. The table

* shows the percentage of cases successfully classified (and those selected

or rejected appropriately) for both the calculation and the validation

cases. Table 2 lists the variables foune to contribute significantly to

dir-criu.,natioiL fo~r these criterion levels. Although the percentage of

correct total classifications varies somewhat by criterion level and is

relatively low, what is more important is the percentage of correct selections and rejections. These percentages change dramatically with the

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case, the percent of correct selections goes from 38% at the Expert

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correct rejections goes from 89% at the Expert level to only 38% at the

Second Class level. These percentages of correct selection, in particular,

indicate a fair degree of success of this model for predicting success in

training. This is directly implied by comparing these correct selections

2 with the observed training success performance obtained in the TOW Training program at the time of the data collection. During early 1977, when

these data were collected, approximately 20% or less of trainees were

qualifying as Expert and about 80% were qualifying as Second Class Gunners

or better. These percentages were demonstrated by the actual qualification

scores of the 307 cases in this sample as well. If this sample had been

selected using the model developed, only about 80% of the trainees would

have continued in training, but of those about 38% would have qualified

as Expert and about 93% would have qualified as Second Class or better

Gunners.

M-70 Excluded Model Results. Again detailed results are presented

later. Table 3 summarizes the results of selection by a model which does

not include the initial M-70 training scores. Again, the results are

shown only for the criterion levels related to the M-70 qualification

levels used at the time of data collection. Table 4 lists the significantly discriminating variables for each of the three criterion levels.

From the percentages for correct selections shown in Table 3, it can be

seen that application of this model would also have contributed to a

higher percentage of selected trainees qualifying at each level. For the

expert level, 27% of the selected trainees successfully qualified at that

level compared with 20% in the non-selected total group. Similarly, for

qualification at the Second Class level or better the selected group

would have provided about 91% qualifiers as opposed to an actual level

of about 80% for the non-selected total group.

Selection/Prediction for Live Fire Success

In assessing live fire performance during the TCATA TOW TEA test, two

major MOEs were used: actual hit/miss of the target and radial miss distance

measured from the center of mass of the target (RDCM). To develop the selection model it was necessary to choose one of these two measures as the basic

criterion measure. TCATA used RDCM in the preliminary analysis of selection

factors reported (TCATA report, pp. 2-23 thru 2-32). There appeared to be

equally strong reasons for the use of either criterion, so both were investi-

* gated.

Initial correlation and multiple regression analyses were run to examine

the interrelationship of RDCM and hit/miss and their relationships to the

available predictor data. Table 5 shows dat the initial multiple regression

to predict RDCM yielded an R = .578. This value indicates that all predictor

variables taken together can account for about 33% of the variance in RDCM.

The similar regression for prediction of hit/miss scores yielded an R =.481.

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Table 5

Correlation and Regression Analyses

for RDCM and Hit/Miss Data

Multiple Regression:

Criterion R R2

Hit/Miss .481 .231

RDCM .578 .334

Simple Correlation of r = .548

Hit/Miss with RDCM (n = 186, p <.Ol)

41

10
This value indicates only about 23% of the variance in hit/miss can be

predicted by the variables taken together. The simple intercorrelation

of hit/miss scores with RDCM was found to be .548, indicating a fair

degree of relationship, accounting for about 30% of the variance. However,

this intercorrelation is not sufficiently high to allow the assumption of

equivalence of the two criteria (MOE). Given this value and the essential

aim of the TOW system: to hit the target, the hit/miss criterion was chosen

as the basis for selection model developmert.

The development of the live fire selection models was based on the

total set of available data. This included all 222 gunners firing in the

TOW TEA test. All gunners were used, regardless of different training,

because the TCATA analysis had shown no difference in performance (either

pH or RDCM) as a function of the training program. As for the M-70 selection

models, the initial models were developed on about 2/3ds of the group and

then validated through classification of the remaining personnel. Two separate

models were developed, one including the ASVAB aptitude scores and one without

these scores.

Table 6 shows the results of application of these two models. It can be

seen that neither selection model is very successful. The ASVAB model was most

successful in accounting for 31.1% of the variance in the criterion with

thirteen variables included. This model yielded 86.9% correct classifications

(both correct selections and correct rejections) and provided for 88.3% correct

selections in the calculation group. In the validation group, the model yielded

only 82% correct classifications and 86.9% correct selections. The second

model was even less successful, accounting for only 9.9% of the variance with

three variables. Here, the correct classifications were 84.7% of the calculation group and 85.1% of the validation group. Correct selection of hitters

was 85.1% for this model. Variables contributing significantly to these

discriminant models are listed in Table 7.

These two models indicate there is little benefit to be gained from

selecting personnel for TOW gunnery. This is a direct implication of the

comparison of the percentage of correct selections with the percentage of

the unselected gunners who actually hit the target. Overall, bout 84.4% of

the gunners hit the target (based on 205 missiles, excluding system failures).

The best percentage for correct selections with the models is 88.3%, for the

thirteen variable selection model. This yields only 3.9% improvement in the

hit ratio if the gunners had been preselected using this model. Using the

• %second model, the gain would have been only 0.7% (85.1% - 84.4%).

*M-70 Training Vs. Live Fire

14 The relationship of M-70 training performance to live fire performance

and the significance of qualification scores were issues for examination in

the TOW TEA Test. The TCATA analyses treated these questions for the 108

gunners taking part in the comparison test (the add-on Test, see Paras 2.4.7

and 2.4.8, pp. 2-34 thru 2-40, TCATA Report). These analyses indicated no

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3 Table 7

Significantly Discriminating Variables in Live Fire

-~ Selection Models in Order of Contribution

Selection with Selection without

ASVAB Scores ASVAB Scores

1 GM Score Left Eye Acuity

2 Left Eye Acuity Right Eye Acuity

3 TG Score Smoking

4 SC Score

5 CO Score

6 OF Score

7 Shotgun Exp.

8 Pistol Exp.

9 Eye Color

)10 Smoking

11 Months of Service

12 Right Eye Acuity

13 Wearing Corrective Lenses

* 13

1%%

~:< ~L
differences between dry tracking and tracking with the M-70 in terms of

either RDCM or hit/miss results (pH) for the 108 soldiers. The conclusion

was that use of the M-70 did not produce a significant improvement in gunner

performance. The analyses also indicated little relationship between M-70

. tracking performance and RDCM for the M-70 trained group. TCATA concluded

here that: "a) The M-70 does not accurately predict gunner performance;

and, b) the distinction between expert, first class, and second class

gunners is meaningless."

The data TCATA bases these conclusions on are presented in the following extract from the TCATA report, p. 2-38:

TABLE 2-22. M70 SCORES VERSUS RDCM CORRELATIONS

Mean

Mean RDCM

Task Score (meters) r-valuea

Group 5B (17 gunners)

A 482 0.84 -0.62

B 738 0.84 -0.54

C 638 0.84 -0.42

Overall .- 0.39

Group 6B (16 gunners)

A 572 1.52 -0.30

B 794 1.52 -0.53

C 734 1.52 -0.22

Overall .- 0.40

Group 7B (16 gunners)

A 658 1.36 -0.13

B 817 1.36 -0.09

C 720 1.36 -0.17

Overall .- 0.13

aThe minus r-values show an inverse correlation; as scores increase over

the sample, RDCM decreases.

(One change has been made in this table: the mean scores for Group 6B were

reversed for Task A and Task C in the original; the above figures have

been corrected.)

The high r-values reported by TCATA for Group 5B, Tasks A and B, and

for Group 6B, Task B, were of concern to ARI. These three values reported

above are significant at less than the .05 level, indicating a trend in

increasing correlation between M-70 performance and RDCM as rougher roads

are used for training and qualification. (Group 7B trained and qualified

using a smooth road for the target vehicle; Group 6B trained on a rough

14
road, but qualified on a smooth road; while Group 5B was both trained and

qualified with the vehicle using a rough road.) Were this trend found to

be real, the question of M-70 value in training and qualification would

have remained unresolved.

ARI reexamined this question by redoing the correlational analysis

above and investigating the correlation of qualification scores with the

Hit/Miss criterion. Table 8 shows these values.

Table 8

Correlations of M-70 Qualification with

RDCM and Hit/Miss (Groups 5B, 6B, and 7B)

Group 5B (17 Gunners) r(QxRDCM) r(QxHit/Miss)

Task A -.15 .20

Task B -.53 -.23

Task C -.42 .13

Group 6B (16 Gunners)

Task A -.30 .64

Task B -.53 .62

Task C -.22 .62

Group 7B (16 Gunners)

Task A -.12 -.24

Task B -.08 -.18

Task C -.16 -.20

One important difference from the TCATA reported data was found: the

correlation between RDCM and qualification score for Group 5A, Task A, was

found to be only -.15, as compared with a reported value of -.62. To

resolve this contradiction, ARI rechecked the original individual data

values in the TCATA report against our data base (TCATA's Table 2-6 gives

live fire data and Table D-2-5 shows individual qualification scores.) No

error was found in the data base, therefore, it is assumed that the TCATA

value is a typographical error. The value shown in Table 8 is accurate.

The remaining data in Table 8 do not indicate any strong relation

between M-70 qualification and either RDCM or Hit/Miss. The high and

statistically significant correlations shown for Group 6B appear to be

actually chance results, based on the very small number of gunners who

missed (Group 5B, 1 of 18 missed; Group 6B, 2 of 16 missed; and, Group 7B,

2 of 16 missed.) The fact that such correlations do not appear for either

5B or 7B also indicates this is likely a statistical anomaly rather than

real.

15
Based on these data, as corrected, there appears to be no real relationship between M-70 qualification scores and either RDCM or Hit/Miss with the

live missile.

Discussion and Conclusions

The data and analyses summarized above indicate there is little to be

gained from either selection of gunner trainees or use of the M-70 as a

training device for gunner trainees. Although the development of selection

models is possible, as shown previously, the application of these to the

population (as represented by the gunners used in the TCATA test) provides

only minimal increases in the hit probability for the selected groups. This

implies that the costs of application of the selection techniques would outweigh the hit payoffs, since selection will yield very little benefit to

the system performance.

With respect to the utility of the M-70 as a training device; the basic

TCATA data show that essentially untrained gunners achieve hit probabilities

nearly as high as those of fully trained gunners, using the M-70 feedback on

.4 tracking performance. These data indicate that the M-70 feedback provides

very little training value above that provided by dry tracking with the TOW

equipment alone.

As an-evaluation device, the TCATA data show that the M-70 is totally

inefficient: there is no indication of a predictive relationship between

M-70 qualification scores and either live fire miss distance (RDCM) or live

fire hit probability.

The following conclusions are drawn from the above analyses:

(1) Formal selection models should not be developed for TOW gunners.

If informal selection methods are desired by field commanders, these should

be very simple and based on the findings of this research. Such an informal

procedure should consist of selecting as gunners those soldiers who have

perfect vision (20/20 in both eyes and no other observed defects) and who

are non-smokers. Such selection will maximize the probability that these

gunners will hit targets, but the gain in probability is likely to be very

small.

(2) Further use of the M-70 as a training device or as an evaluation

tool should be carried out only if there are no costs associated with such

use. Further developments or purchases of M-70 should be pursued only if

such developments can be demonstrated, with empirical data, to have a

measurable training benefit - a true contribution to hit performance.

(3) Criteria for elimination of trainees from TOW training can not be

developed since live fire performance can not be predicted from training

performance, given the measures available. This has become a trivial question given that trainees (no matter how trained) succeed at live fire with

probabilities which closely approximate system performance specifications.

16
TOW GUNNER SELECTION

TECHNICAL SUPPLEMENT

BACKGROUND

This portion of the report presents the detailed development of

the selection/placement models used to determine the feasibility of TOW

gunner selection. It discusses the TOW and the training system used as

well as early attempts at gunner selection for TOW and similar systems.

It also describes preliminary research leading to the methods developed

and applied in selection/prediction for the M-70 training situation and

for the live firing of the TOW.

Training soldiers in the technique of anti-armor guided missile

-~ gunnery has uncovered difficulties unforeseen at the time the weapons

were fielded. The primary difficulty is that insufficient soldiers

were qualifying in anti-armor guided missile gunnery to fill the needs

V. of the active Army. Further, in the TOW system, little has been known

about the utility of the currently used TOW simulator, the M-70 trainer.

Specifically it is not known whether or not the M-70 trains to increased

probability of live-fire hit or whether it trains merely to itself as a

criterion.

Several methods are available for increasing the numbers of soldiers

qualified to operate tactical guided missiles. One method is to place in

a training program (according to some set of criteria) those soldiers who

possess characteristics which indicate a good probability of meeting or

exceeding some minimal acceptable performance criterion after training.

Ideally, a set of convenient measures could be used to place likely

candidates in training programs and thus increase the number of qualifying soldiers produced from the training programs. A concomitant decrease

in numbers of soldiers found to be unqualified after training should reduce training cost per qualified soldier.

Two assumptions must be borne in mind while reading this report.

They are necessary to understanding the limits bounding the information

presented herein. First, the placement models considered here must be

referred to their underlying training programs and in a sense are operationally defined by these training programs. Second, the M-70 placement

models and the live-fire placement model should not be equated as the

5. former presupposes criteria which operationally and functionally differ

from the latter. Succinctly, a soldier's performance in the M-70 tz.aining

is not necessarily indicative of live-fire performance.

17

4%.
4 -- 7 -

THE TOW SYSTEM

The TOW system is composed of three interactive elements. These

are the weapon and training device, the program of instruction, and the

* gunner. Each will be described briefly.

The TOW is a heavy anti-armor weapon which fires a tube-launched,

optically tracked, wire-guided missile. It is operated with a four-man

crew: squad leader, gunner, assistant gunner, and vehicle driver. The

TOW hardware consists of a tripod, a traversing unit, a missile guidance

unit, a battery set, the TOW round (packed in an integral launch tube),

and a tracking unit which incorporates an optical sight. An infrared (IR)

receiver assembly in the tracker receives a signal from an infrared flare

in the after end of the fired missile. The tracker electronically compares

the missile position with the gunner's line of sight. The resulting error

signals are translated to steering commands. These signals, transmitted

through the tracking wire, control the missile's steering vanes during

* flight. Effective range is 65-3000 meters, The ground-mounted TOW is

usually fired from the kneeling position. The tripod provides a threepoint support platform for the system.

THE TRAINING SYSTEM

The primary training device for the TOW is the M-70 trainer. The

M-70 was adopted because of the great cost per round of both armed and

inert TOW missiles. The trainer consist of an instructor console, a

remote IR source tracking target, and a missile simulator round which are

used with the TOW launcher assembly. The trainer provides practice with

feedback on the gunner's performance in tracking the IR target source.

It does this by measuring and recording the soldier's tracking deviations

in azimuth and elevation as his line of sight is compared to the actual

position of the infrared (IR-source) target. A weighted mean deviation

in azimuth and elevation is computed and reported as "percentage of time

on target" for each tracking trial. A deviation from the simulated tracking envelope, i.e., exceeding designed tracking limits, terminates the

* trial and is reported as a "launch excursion."

The M-70 can be fitted with an M-80 blast simulator diaphragm.

This produces an explosion designed to simulate gryroscopic activation

and ignition of the TOW missile. The M-80 also provides an approximate

1.5 second delay between trigger press and ignition, which is the same

as for the TOW missile. Target ranges are simulated for training with

the M-70 by varying target velocities at constant ranges and/or by vary-

* ing both tracking times and velocities to simulate various missile

* flights.

The TOW program of instruction (POI) provides instruction in

assembly, maintenance, deployment, firing, target tracking, and safety.

The institutional course defined by TC 23-24 consists of 39.5 houis of

18
instruction distributed over 5 days and has been reviewed and analyzed

elsewhere (Maxey, 1977). As other POI are derived from this institutional

program, a summary of it will be useful for understanding the models and

analyses which follows. Training in simulated firing and tracking of targets in this POI is done with the M-70 training system. Day One requires

36 tracking runs at near and far simulated ranges. Target speeds vary

from zero to 25 MPH. At the range u-2d, this approximates tracking at

angular rates of zero to 25 milliradians per second (MR/sec). Trials are

distributed in left-to-right and right-to-left fashion. Day Two requires

tracking similar to Day One with the inclusion of a "stop and go" tracking

exercise. A total of 39 trials is run on Day Two. Day Three is similar

to Day One. Day Four requires night tracking and the tracking of shortand long range targets. Also included in Day Four is a rapid firing exer-

- cise. Day Five requires qualification firing, also using the M-70 system.

To qualify, the trainee fires simulated rounds in the M-70 fitted

with the M-80 blast simulator diaphragm. Ten simulated rounds each are

fired at tracking rates of 5, 15, and 25, MR/sec, equally distributed in

right-to-left and left-to-right tracks. Of one thousand possible points

per tracking task (10 trials with a maximum of 100% time-on-target per

trial), the gunner must have 550 points each in the 5 and 25 MR/sec tasks

and 750 points on the 15 MR/sec task in order to qualify. The score on

the lowest-ranking task is equated to an overall qualification rating of

"Expert," "1st Class," "2d Class," or "unqualified" to the trainee. In

all cases in training and qualification, an incomplete track or "launch

excursion" is scored as zero.

The TOW gunner qualifies in the current POI based on his tracking S. ability as measured by the M-70. In the M-70 system, the gunner's hands

guide the TOW launch tube in azimuth and elevation by direct linked viscous damped controls. The launcher holds the optical sight and tracking

receiver, measurement of the error angle (defined by comparison of the

line of sight to the IR-source position) produces an error signal. This

error signal is averaged and at the end of the simulated flight is displayed for the gunner. Hence, to qualify the gunner must exercise a

great deal of motor control over the launcher so that he can keep the

sight reticle at the center of visual mass of the target. This requires

gross and finevisuomotor adjustments. Figure 1 shows the gunner in the

kneeling firing position. As suggested by this figure, both trunk and

extremity visuomotor control are necessary parts of the TOW tracking task.

PREDICTION OF MISSILE GUNNER

When the TOW hardware and training system were developed, no detailed

task analyses were performed to define the Gunner's task and the required

skills and capabilities. The M-70 was developed to reproduce as faithfully as possible the characteristics of the actual TOW system performance,

based on the best information and assumptions of the designer. The M-70

19

4..
T- K- 1 -2 7. 7 -1- 

-- -- -- -

-4

-o".

Figure 1

19a
was not in fact designed to be a training system but for other purposes.

The US Army then chose to adopt the M-70 as the best available approximation to a trainer because it did allow tracking practice without the

high cost of the TOW round. The POI for TOW was then adopted from the

POI of a medium antitank guided missile, the Dragon.

No significant attempts have been made to predict soldiers'

performance either on the M-70 system or in live fire. A few attempts

have been informally reported which made use of doubtful methods - and

small numbers. Several attempts, however, have been made to predict

Dragon performance on the Launch Effects Trainer, the Dragon Trainer.

The pertinent literature is reviewed below.

Stewart, Christie, and Jacobs (1974) attempted to predict performance on the Dragon Launch Effects Trainer (LET). Using soldiers

(N = 125), they took motor, visual, visuomotor coordination, personality,

and intelligence measures. In all, 32 independent measurements per

subject were obtained. These 32 variables were selected by a task

analysis procedure and by ratings from "subject-matter experts." Dependent measures were summed qualification scores for each tracking task,

including night tracking. Dragon LET qualification scoring is highly

similar to that of TOW M-70 scoring.

Six variables were found to account for 36.5% of the criterion

variance when all independent variables were regressed in a forward stepwise fashion. The most predictive of these six variables accounted for

about 25% of the variance, the least predictive for about 1%. Of these

six predictors, four were measures of visuomotor coordination, one was a

confidence measure, and one was the meter scores obtained by gunners

with the LET during stationary familiarization firings. The last

variable accounted for about 4% of the criterion variance, whereas the

*. visuomotor coordination measures (taken together) accounted for about

30% of the variance. The number of hits made in LET familiarization

firings accounted for only about 1% of the criterion variance. Measures

of visual ability and measures of aptitude accounted for no more than

about 1% each of the criterion variance.

The Stewart, et. al., study is of interest because characteristics

found measurable by a well-known pursuit-tracking device (Fleishman,

1958; Fleishman and Hempel, 1955, 1956) were fairly predictive. Both

the first-ranking predictor "average time on target per trial (rate

control)" and the fourth-ranking predictor "number of times on target

(rate control)," were measured by this device. Moreover, neither

purely visual or purely motor tasks (i.e., motor tasks without visual

control) accounted for much of the criterion variance.

Cartner and Tierney in an unpublished pilot study found several

relationships which expand the findings of Stewart, et. al. They

performed analyses on four sets of data collected from Dragon trainees

at Fort Polk, LA., Fort Benning, GA., and during Dragon Operational

Test III-A (OT ITl-A).

20

°' " . .% " -. " ':. ", ' " . ' °" .' .'° '. '." -.-.- -.. .. . '... ." ." *.%-*. . -. .*- -.... ..- , .*, ,
In the first analysis, data from Dragon training, collected early

in the POI, were correlated with hit-miss data from the qualification

* tasks of the POI (N = 68). Scores from the first day of training

accounted for 31% of the variance in qualification scores. Scores

from the first half of training accounted for 35% of the variance of

qualification measures, the additional I days of training adding

only 4% to the explained variance. After three days of training, 39%

of the variance in qualification scores was explained by scores from

the third day of training (an additional 4%). Hence, only 8% additional

variance was accountable by the two days of training beyond the first

day.

Applying the current institutional POI (TC 24-20) minimum qualification standard of 70% LET-measured "hits" per tracking task (or the

minimally qualified "second class" gunner standard), Cartner and Tierney

found 50% of the trainees in this study were attaining the minimum

standard on all tasks after the first day of training, 41% after the

first half of training, and 57% after three days of training. At the

end of training 71% qualified.

In another analysis, Dragon instructors and trainees were interviewed.

Based on these interviews and the pursuit tracking literature, a list of

variables in three categories was devised. These categories contained

background, anthropometric, and tracking performance measures. Specific

variables measured included ocular dominance, handedness, eye color,

frequency of smoking behavior, height, weight, arm length, visual acuity,

lateral and vertical phoria, shoulder width, and first-day-of-training

-~ performance. Measuring a sample (N = 37)of soldiers from Fort Bennir.,

Dragon classes, these data were regressed in stepwise fashion against

summed qualification scores.

Scores from the first day of performance on the LET accounted for

29% of the variance in criterion scores. An additional 6% of the variance

was attributable to arm length which increased the multiple correlation

coefficient from R = .54, to R = .59. Adding height and weight to the

regression equation increased _the amount of criterion variance explained

to 41% (R = .64, p- .01). The addition of eye color, hand and eye

dominance, frequency of smoking behavior, and shoulder width (in that

order) increased the multiple correlation coefficient to R = .65 '4 (p < .01), a trivial increment.

A third analysis was performed on data from a group of 27 Fort

Benning soldiers. The best set of predictors of qualification were

(in order) tracking performance on the first day of training, arm length,

acuity of the right eye, height, weight, vertical phoria, lateral phoria,

and acuity of the left eye. Again performance scores on the first day of

LET training and arm length accounted for some 36% of the variance in

% qualification scores.

21
It would appear then, that some classes of variables are reasonably

predictive of a trainees' performance on the LET. As Stewart, et. al.,

found, performance on the pursuit tracking device predicts to a certain

extent performance on the LET. Further, the Stewart, et. al., analyses

suggest that early performance on the LET predicts to a certain extent

subsequent performance on the LET.

The LET-predicting-LET finding was substantiated by Cartner and

Tierney's findings. Further Cartner and Tierney found that anthropometric

differences may account for some criterion score variance.

Cartner and Tierney additionally then analyzed data from Dragon

OT III-A. Looking at variables concomitant to Dragon live -fire, some

"no difference" findings were of considerable interest. For example,

the probability of hitting targets was not affected by the position of

the firer (standing, sitting, or kneeling), the type of target (tank,

armored personnel carrier, or bunker), the target orientation (frontal,

lateral, or oblique), or the range of engagement (near or far).

Cartner and Tierney have adapted and expanded the methods used for

LET performance prediction (Stewart, et. al., 1974) to M70 performance

predictions. They analyzed a set of data collected from TOW trainees

(N = 87) at Fort Polk, LA. All soldiers received four days of training

- according to the TOW POI. Qualification trials were made on the last

day of training.

Performance on the M70 on the first day of training was found

generally to be a good predictor of qualification trials performance.

Specifically, first day performance on the 5 MR/sec tracking task

accounted for 23% of the variance in qualification performance of the

5 MR/sec task, (p :.01); 11% of the variance in the 15 MR/sec task

(p.Ol); L and 25% of the variation in the 25MR/sec task (p !.01).

For the other tasks, first day performance did not predict any later

qualification tasks.

After three days of training, performance on the 5 MR/sec task

explained 37% of the variance (pS..O01) in the 5 MR/sec qualification

task; 30% of the variance in the 15 MR/sec qualification task (p <.001)

and 37% of the variance in the 25 MR/sec qualification task (p .001).

The 15 MR/sec task explained 32%, and 46%, respectively, of the 5 MR/sec

and 25 MR/sec qualification tasks (pz .001). Performance on the third

day in the 25 MR/sec task explained 16%, (p L.01), 7% (p .05), and

15% (p!.0l) respectively of qualification in the 5MR/sec, 15 MR/sec,

and 25 MR/sec tracking tasks.

Based on these preliminary attempts at gunner prediction and

selection, the present study was designed. Briefly, this research is

directed toward a definitive examination of the feasibility of selecting

.e-. TOW gunners. The research was directed first toward selection of trainee

based on prediction of training success using the M-70. The second stage

in selection research was directed toward selection of gunners based on

success in live fire. The latter reearch was to be performed using data

derived from a field test of TOW training effectiveness during early 1978

at the TRADOC Combined Arms Test Activity (TCATA).

22

.41% ,, ,% . . , , :. .; - . . . .. . . • . " • . .
METHOD

The following sections address the methods followed in each of the

selection model developments. The first addresses the development of

two M-70 placement models. The second addresses development of the TOW

live-fire model.

SELECTION FOR TOW TRAINING

Data collected were arranged in a Subjects X Measurements format

to facilitate multivariate statistical manipulationRelevant data were

a set of predictor measures for each subject and a set of criterion

measures for each subject. Data were collected from mid-January to

mid-April 1977 in three simultaneous operations. One operation involved

measuring performance on the M-70 trainer during training and qualification. A second operation recorded pertinent background data from each

soldier's Official Record Jacket (DA 205). A third operation involved the

measurement of each soldier along various dimensions prior to training

on the M-70.

Subjects. Subjects (N = 307) were male, late-adolescent soldiers

of the 1st Advanced Individual Training Brigade (Infantry) at Fort Benning,

Georgia. Soldiers were not randomly assigned to TOW training. Selection

for guided missile training was based on the soldier's post-AIT assignment.

If to be assigned to USAREUR where TOW is available, the soldier went to

TOW training. This procedure, while not random is sufficiently haphazard

to warrant treatment of the sample as a randomly selected group. Soldiers

from 14 TOW classes were measured. Class sizes ranged from 7 to 31 trainees

(median = 23). Data from 13 subjects were discarded due to incomplete or

uninterpretable records.

Performance Measurements. The performance measurements were M-70

meter readings at the termination of tracking, 0 MR/sec, 5 MR/sec,

15 MR/sec, and 25 MR/sec targets. Scores were recorded for each subject

in his first four attempts to track targets with the M-70 in each task.

Scores were subsequently recorded for the last four qualification trials

at each rate. Thus, measurements assessed the goodness of track for the

first four and the last four attempts of each subject at each tracking

task. M-70 measures were recorded at firing ranges by a trained noncommissioned officer immediately after each tracking trial.

Background and Other Measurements. Twenty (20) items of background

data were recorded from each subject's Official Record Jacket (DA 205).

These included age, complexion (light or dark), height, weight, last

physical training test score, handedness, years of education, whether

corrective lenses were worn, months of military service, M16AI rifle

qualification, prior participation in contact and noncontact sports, and

composite scores of the Armed Services Vocational Aptitude Battery (ASVAB).

23

-a!
(General Technical (GT), general mechanical (GM), electrical (EL),

clerical (CL), motor maintenance (MM), surveillance and communications

(SC), combat (CO), field artillery (FA), scientific and technical (ST),

and operator and food service (OF) aptitude scores were collected.)

Other measurements were made prior to TOW training by personnel

trained in these measurement techniques. These included each traineels

shoulder width, arm length, ocular dominance, reported smoking behavior,

visual acuity, visual phoria, and eye color (light or dark).

Background data were collected in conformity with the Privacy Act

of 1974 and under 10 USC 8012 and 5 USC 301. These data were drawn

from each soldier's Official Record Jacket by persons regularly assigned

to the Adjutant General of the Infantry Center, Fort Benning, Georgia.

The above variables were selected because of demonstrated utility

in prior studies or because of indications from the psychological

literature that they might be predictive. A third group of variables

was included because of ease of measurement. The last consideration was

a determining factor in the inclusion/exclusion for each independent

variable as one of the purposes of this study was to identify readily

measurable quantities useful to the decision-maker in the field. This

person would be responsible for applying any feasible placement model

developed from this study. Variables fell into several convenient

classes of anthropometry, measures of M-70 performance, demography,

self-reported background items, measures of aptitudes and measures of

training performance and conditions.

Analytic Technique

The data were subjected to preliminary reduction prior to development of the selection models through discriminant analysis. Certain

variables were known a priori to have high intercorrelations. Thus,

correlation coefficient matrices were calculated for anthropometric,

visual, and ASVAB score variables. Only one of a pair of variables

correlating p - .75 were maintained. For example, 15 MR/sec tracking

correlated highly with 5 MR/sec and 25 MR/sec tracking (training and

." qualification), this variable was deleted.

The qualification tracking scores for all subjects were taken as

the criterion variables for the regression and discrimination analyses.

Tracking scores at qualification for the 5 MR/sec and 25 MR/sec tasks

were added for each subject to establish his criterion score.

Eight arbitrary criterion levels were established against which

to discriminate. These were a combined score on Tasks A and C of 1)

1650 or better; 2) 1500 or better; 3) 1430 or better; 4) 1370 or better;

5) 1300 or better; 6) 1230 or better; 7) 1170 or better; and, 8) 1100 or

better. Criterion levels 2), 5) and 8) were determined by adding the

minimum current qualification scores for Tasks A and C for Expert, First

Class, and Second Class Gunners, respectively (adding the 5 MR/sec and

25 MR/sec qualification levels). Intermediate values were established

by linear interpolation.

24

, ~io, PON.J ''"-''.-' - - - ' -- " ' : ' \ .' . " \I' -
Discriminant analysis was performed using data from 209 cases randomly selected from the 307 available No Bayesian corrections were made for

class inclusion. The equations derived from the discriminant analysis

were then applied to the remaining data collected from the 98 other

subjects. A stepwise discriminant paradigm was employed; inclusion/ .4% exclusion criterion was set F = 1.00. Only one discriminant function

per criterion level was calculated. Although the intended use for a

model such as this appears to be "select out" persons prior to TOW/M-70

training, classification function coefficients were observed for both

the "Go" and "No Go" groups. Additionally, standardized and unstandardized discriminant function coefficients were calculated.

Two training selection models were constructed. The first includes

M-70 training scores (the mean of the first four training trials on the

5 MR/sec and 25 MR/sec tasks) as discriminating variables. The second

model excludes these M-70 scores, using only variables other than M-70

measurements as discriminants.

SELECTION FOR LIVE FIRE PERFORMANCE

Data for the development of the live fire model were obtained during

the conduct of a TRADOC Combined Arms Test Activity (TCATA) test of TOW

training effectiveness at Fort Hood, TX, from March to June of 1978. This

test, sponsored by the Infantry School (USAIS), has been reported in detail

by TCATA and will not be detailed hereP* This discussion will cover only

the data collection and analyses necessary to the examination of the selection model.

Subjects and Training. Three groups of gunners were trained under

three different training programs in the TCATA test. Group I (N=114) was

trained on a minimum program consisting of 6.5 hrs. of miscellaneous TOW

subjects (fundamentals of operation, maintenance, safety, target identification, etc.) and 1.5 hours of tracking practice in a crew of three, giving

only hour of hands-on dry (without feedback) tracking per person. This

consisted of ten trials of the 5 MR/sec Task A.

The test initially intended to compare the performance of this group

with that obtained by two groups to be trained later with 14 hours (medium

program) and 39 hours (maximum program) of training. The latter two groups

were to have used the 1-70 trainer in tracking practice. However, performance in live fire by the minimally trained Group I personnel was sufficiently good that TCATA and TRADOC determined the latter two groups unnecessary. A substitute test comparison was developed to help determine the

effectiveness of M-70 training on TOW live fire performance. This was

called the "Add-on Test" by TCATA and is reported as such. The "Add-on"

*The discriminant program from the Statistical Package for the Social

Sciences (SPSS) Version 6.2 was used fcr all discriminant analysis.

**Training Effectiveness Analysis (TEA)-TOW Part I, Hq, TCATA, Fort Hood,

TX, Sept 78.

25
test groups were trained and fired and these data were available for use

in this analysis.

*1 The "Add-on" test subjects were divided into two additional groups.

Group II (N=54) and Group III (N=54) each received about 20 total hours

of TOW instruction. This included the fundamentals training received by

the Group I personnel, and about 12 hours of tracking experience, with 4

hours as gunner and 8 hours as a crewmember for each soldier. Group II

tracking training used the TOW with the M-70 trainer so each gunner

received feedback on his performance after each trial. Group III training

used the TOW without the M-70 tracking non-infrared targets, and the

gunner received no feedback on the quality of his tracking for any trials.

Approximately 120 tracking trials were performed by each gunner in both

Groups II and III. For Group II, these were distributed as 80 trials on

the 5MR/sec Task A and 20 trials on each of the 15 MR/sec Task B and the

25 MR/sec Task C. Group III trainees performed 80 dry tracking trials

on the 5 MR/sec Task A and 40 on the 15 MR/sec Task B.

Predictor Measures. All demographic, aptitude, anthropometric and

self-report data collected during the development of the training-selection

model, indicated above, were also collected for each subject involved in

this test. Additionally, several behavioral measures were collected and

detailed attitude and expectation questionnaires were designed to be administered before training, after training and after live fire. Behavioral

measures taken were two scores derived from standard trials on a standard

pursuit rotor device (time on target and number of errors) and a steadiness

test. The questionnaires developed by ARI were administered only to the

Group I trainees. TCATA determined that, since the "Add-on"' test groups

were not part of the original experiment, these data for Groups II and III

were irrelevant. Appendix A lists the predictor measures collected in this

part of the research.

Performance Measurements - M-70. Performance measures were obtained

for each subject in all three groups. For Groups I and III these were

collected after live fire. Group II data were collected during training.

Data collected were records of the M-70 meter scores and strip chart

recordings of the azimuth and elevation error signals generated during

tracks by the M-70 tracker. M-70 meter scores were obtained for each man

on his initial ten tracks with the M-70 trainer on the 5 MR/sec Task A.

Strip chart recordings were collected only for the first and final tracks

of each man at each Task, regardless of Group. M-70 meter scores were to

be used to determine the relation of current scoring to live fire measures

described below. Tracking error data were to be correlated with tracking

data collected during the flight of the actual missile in live fire. Due

to TCATA Test Director decision during the test, there was an anomaly in

the data collection process for Group 11. This resulted in the three subgroups (5B, 6B, and 7B in TCATA's designation) being trained and qualified

under different conditions (smooth tracking roads vs. rough grassy tracking

roads).* Preliminary analyses of these data by TCATA indicate that the

*See TCATA report, Para 2.4.8, pp. 2-36 thru 2-40, and Appendix E.

26
resulting M-70 tracking scores are sufficiently different for the three

subgroups to preclude certain detailed analyses of the data.

Performance Measurements - Live Fire. Live fire data were collected

by TCATA for each missile firing. The details of the firing environment

and the data collection procedures are presented in the TCATA report

(Para 2.3 Execution, and especially pp. 2-9 through 2-12). Briefly,

each gunner was presented with a field situation and directed to engage

4,, a specified M47 Tank target following a relatively smooth road at a

speed of 12-15 mph and a range of from 2,950 to 2,750 meters. During

the engagement, flight data were collected with video tape recorders.

One camera was mounted on the TOW optical tracker (aligned generally with

the optics), and a second camera was located down range to cover the

target. Tapes from these cameras were analyzed, by single frames, to

extract error measures. The first camera tape yielded deviations of the

line of sight from the target center of mass during missile flight. The

second, covering the target, allowed measurement of the radial miss

distance from center of mass as the missile crossed the target plane

(RDCM). In addition to the RDCM measure, the actual values of azimuth

and elevation errors at the impact plane were recorded. Reduction was

accomplished by TCATA personnel and the report indicates these measures

were accurate to t .25 meter. Actual hit or miss of the observed round

was verified through this analysis also, and the result was recorded for

each gunner.

The deviation errors during the flight were recorded for use in subsequent comparative analyses with the tracking errors recorded on strip

charts during tracking with the M-70 trainer. These were to be used in

analysis of the relationship between M-70 tracking and live fire tracking.

These latter analyses were not performed, based on the results reported

later.

Analytic Technique

Analysis of the live fire data and the use of regression and discriminant analysis to predict live fire success was largely parallel to the

analysis described earlier for the prediction of the M-70 training success.

One additional requirement necessary here was the determination of the most

appropriate criterion measure for prediction. The TCATA test staff collected data on both the radial miss distance from the center of mass (RDCM) and

the hit/miss success of each gunner. Both measures of effectiveness (MOEs)

have some degree of face validity and could be useful criteria for successful performance. Thus, it was necessary to evaluate the goodness of these

two alternative criteria for prediction. This was accomplished by assessing

the relationship between the two and the degree of multiple relationship

between the predictor variables and each criterion measure. Simple correlation of the two values for the gunners with available data (N-186)

resulted in an r - .548, indicating that either criterion would account

for about 30% of the variance in the other. This value is relatively

27
high but not sufficiently high to assume equivalence between the two

measures. Multiple regression was used to examine the relationships of

all predictor variables to the two MOE and these resulted in R = .481

for hit/miss scores and R = .578 for RDCM values. These equate to prediction of about 23% of the variance in hit/miss and about 33% of the

variance in RDCM values. Although the predictive value is higher for

the RDCM measure than for hit/miss, two facts directed the choice of

hit/miss as the final criterion for use in prediction/selection model

development: 1) actually hitting the target is the ultimate measure of

whether a gunner is good or not, since that is the point of target engagement. Although it could be argued that a nearer hit is better than a

peripheral hit, it can also be argued that the center of mass is not

necessarily the best of all places to hit a tank (e.g. - a motor hit or

a turret hit might be considered more effective than a center of mass

hit - although the difference is probably negligible); and, 2) of the

total of 222 gunners in the TCATA test who fired missiles, RDCM was

available for only 193. Use of this as the criterion would thus result

in lowering the total N by 29 gunners. Based on both these considerations,

the hit/miss result was determined to be the more appropriate criterion

for development of the prediction/selection model.

The total set of 222 gunners for whom data were available were used

for development and validation of the discriminant models. The aggregation of the three groups into a single set was based on the finding by

TCATA that the different training programs had no statistically differential effects on the hit probability of the different trainees. For

these purposes, the groups performed nearly identically, thus they were

aggregated into a single data base for prediction/selection model development. Discriminant analyses were then run using the full set of prediction variables to attempt to differentiate between hitters and missers.

The analysis used 2/3rds of the gunners to develop the prediction model

(the calculation case) and used the remaining third of the gunners to

assess the validity of the discriminant function so developed. After

initial runs, non-discriminating variables were discarded and two sets

of predictive variables were chosen based on the initial discriminant

scores and the classification scores assigned. One set included the

scores from the Armed Services Vocational Aptitude Battery (ASVAB) while

the second set did not include these scores. Final discriminant runs

were made with these reduced variable sets. The results are reported

below.

RESULTS

This section presents separately the results of the two separate

prediction/selection efforts: that to predict/select TOW gunners to be

successful in training on the M-70 device; and, that to predict/select

gunners for successful performance on the live firing of the TOW system.

28
* THE M-70 MODELS

Two models were developed to select trainees for entry into M-70

training for TOW gunnery: The first included initial TOW performance

as a predictor variable together with the anthropometric, demographic

and behavioral variables listed in Appendix A; the second used only the

* '~Ivariables available prior to any TOW training.

SW. Prediction of Training Success with M-70 Performance Included

-/ Discriminant analyses were performed as described in the Analytic

Technique above. The computer outputs of the multiple runs against each

of the eight criterion levels used (Cf. p24) are presented as Tables BlB8a in Appendix B. These tables include the order of entry of the

variables into the analyses, the standardized and unstandardized discriminant scores, and the classification function scores for each analysis,

and the centroid values for each of the "GO" and "NO GO" groups. The

"GO" group was defined prior to each analysis as that portion of the

calculation group who actually attained a score on Tasks A and C combined

equal to or exceeding the criterion value.

Table 8 shows the set of variables found to be significant discri-

* minators for each criterion level in the calculation group. These are

listed in the order of contribution to the discrimination of the two

groups, based on the standardized discriminant scores. As seen, the

variables found to discriminate vary somewhat at each criterion level.

However, the initial M-70 tracking performance on both the 5 MR/sec and

25 MR/sec tasks, arm length, eye color, height, and either GM score or

CO score (both from the ASVAB) tend to be involved in most predictive sets.

Table 9 presents a summary of the results of the discriminant models

by criterion level. It will be seen that these models account for a

I' minimum of 20.7% of the variance in final M-70 performance at the minimum

criterion level for the calculation case. Variance accounted for ranges

up to 26.9% for the prediction of the criterion equivalent to the thencurrent Expert performance on Tasks A and C combined. This table also

shows the degree of success of each model for both the calculation case

and the validation case (application of the models to the classification

of the hold out group: (N-98)). The first comparison is between the percent

of total correct classifications. The second column under the calculation

case and the first column under the validation case give this comparison.

- It can be seen that these percentages range from 70% to about 82% for the

calculation case and fall only to 59% to 79% for the validation case, thus

indicating some consistency of the models in transfer to the validation

case. However, it should also be noted that the 82% high value for the

calculation case is not especially high. Going to the next column to the

right for both cases allows comparison of the percentage of correct selections given by each model. Here it is important to note that the percentage of correct selections varies inversely with the criterion level

29
t

Table 8

Discriminating Variables by Rank and Criterion Level

for M-70 Included Model

Rank 1650 or Better 1500+ 1430+ 1370+

1 Eye Color Trng 25 MR Score Trng 5 MR Score Trng 25 MR Score

2 Trng 5 MR Score Trng 5 MR Score GM Score Arm Length

3 Trng 25 MR Score GM Score Trng 25 MR Score GM Score

6 Smoking Prior Sports Eye Color CO Score

Participation

5 PT Score PT Score Arm Length Trng 5 MR Score

6 Height Eye Color CO Score Height

7 Rt Eye Acuity Handedness PT Score Eye Color

8 Rt Eye Acuity

9 Height

10 Age

Rank 1300+ 1230+ 1170+ 1100+

1 Arm Length Arm Length Arm Length Arm Length

2 Trng 5 MR Score Trng 25 MR Score Trng 25 MR Score Trng 25 MR Score

3 CO Score Eye Color Height Height

4 Trng 25 MR Score Height Eye Color Eye Color

5 Height Prior Sports CO Score Smoking

Participation

6 Prior Sports PT Score GM Score PT Score

Participation

7 Age PT Score Prior Sports

Participation

8 Smoking Prior Sports

Participation

9 Smoking

30
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preictd. hisis true for both the calculation case and the validation

case. Conversely, the percentages of correction rejections (the last

colun ineach set) varies directly with the level of the criterion

predited.The percent correct selections is simply the percent of those

predcte bythe model to be GO on the criterion level who actually were

obsevedto be GO on the measured criterion. Similarly, the percent

cretrejections is the percent of those predicted to be NO GO who

wrsoobserved in measurements. Thus these values are direct measures

ofteefficiency of the model in either selecting trainees "into" or

flot f"the training program. For example if the highest criterion

levl wreused, and the validation case trainees were examined for

actul secionfor training, this model would have correctly rejected

97% of those who would not have performed on the M-70 at this criterion

level. However, it would have selected into training a group, of which

only 20% would have passed the criterion level. It also should be noted

that this model and criterion level would only have selected about five

gunners of the 98 for training. Thus, this model is very stringent and

exclusive rather than inclusive. Conversely, if the lowest criterion

were to be used for selecting from the validation group those who should

- be trained, 93% of those selected would have passed the criterion, while

* only 38% of those rejected would actually have been failures if trained.

This model would have selected about 74 of the 98 for training and thus

would have yielded 69 successful trainees. This, then, with the lower

criterion level, yields a more inclusive model and a much higher successful inclusion rate. It should be L~ ed that the 93% successful selection

rate exceeds the rate that was prevalent in TOW training at Fort Benning

at the time these data were collected - the then-current success rate

(2nd Glass or better - equals 1100+) was about 80%. It should also be

noted that this rate was since sharply increased through differential

training developments by the Weapons Group within USAIS. Recent success

rates have exceeded 90% consistently.

Prediction of Training Success without M-70 Performance

Discriminant models for each criterion level were also run without

the inclusion of the initial M-70 training data as predictors. Tables

B9 through Bl6a in Appendix B show the summary output of these discriminant

* ,~.analyses. Again, these include the variables input to the analyses, the

classification and discriminant function scores, etc.

Table 10 shows the variables found to discriminate significantly for

*each criterion level. As for the previous models, the variables contributing

to prediction at each criterion level are listed in their order of contribution of discrimination of the GO and NO GO groups. It will be noted that

the set of variables again varies somewhat between criterion level predictions. However, again there is some degree of consistency across the

variable sets. Arm length, eye color, height, and prior sports participation appear most consistently. Smoking, physical fitness (PT) scores, and

the GM and CO scores from the ASVAB also enter into several of the predictions,

while right eye acuity and handedness are found to discriminate in the upper

j%, level criterion predictions.

32
Table 10

Discriminating Variables by Rank and Criterion Level

for M-70 Excluded Model

4 1500+

1650 or Better (Expert) :.430+ 1370+

Rank Variables Variables Variables Variables

1 Eye Color Prior Sports Arm Length Arm Length

Participation

2 Smoking Eye Color Eye Color CO Score

3 Height GM Score Prior Sports GM Score

Part ic ipat ion

4 PT Score Right Eye PT Score Eye Color

Acuity

5 Right Eye Handedness Handedness Height

lip Acuity

6 PT Score Prior Sports

Participation

7 Height

8 Arm Length

1300+ 1100+

(1st Class) 1230+ 1170+ (2nd Class)

Rank Variables Variables Variables Variables

1 Arm Length Arm Length Arm Length Arm Length

*2 CO Score Eye Color Eye Color CO Score

3 Prior Sports Height CO Score Eye Color

Part ic ipat ion

4 Height Prior Sports Height Height

L Part icipat ion

5 Eye Color PT Score GM Score GM Score

*6 Smoking CO Score Prior Sports Smoking

Participation

-7 Age PT Score Prior Sports

Participation

8 Smoking Smoking PT Score

33
Table 11 summarizes the results of this set of models. The maximum

variance in the performance criterion accounted for by any model is 22.3%

and this value ranges downward to 10.2% for the highest criterion level.

This table also shows the percentages of total correct classifications,

correct selections and correct rejections for each of the calculation

case and the base case. It should be read the same as Table 9.

Comparisons of the Training Prediction Models

Meaningful comparisons can be made between the two models including/

excluding the initial M-70 performance by examination of Table 12. This

shows the changes in the various measures of model success resulting from

deletion of the M-70 as a predictor. As indicated, nearly all changes are

negative, with the amount of variance accounted for by the predictors

decreasing for all criterion levels. The average decrease is about 7%

and ranges from 1.2% at the lowest criterion level to 13.6% at the Expert

level. Similar decreases in success are indicated for all three measures

of correct classifications, correct selections, and correct rejections.

In general, it can be stated that the models based only on personal char-

* acteristics of the trainees do less well at predicting training success

than did the models which included initial M-70 performance as a predictor,

which is to be expected.

THE LIVE FIRE MODELS

Discriminant analyses were applied to the data resulting from the

TCATA TOW TEA test Phase I as described earlier. The entire set of TOW

gunners was used to develop and validate the discriminant models since

the TCATA data showed that the training programs had no significant

effect on live fire hit probability.

Preliminary analysis of data sets included multiple regressions and

simple correlations to eliminate from consideration those variables either

too highly intercorrelated with others or totally unrelated to the criterion

of hit/miss. Following these steps, the discriminant analysis programs

of the Statistical Package for the Social Sciences (Nie, et. al., 1976) were

run with two sets of remaining variables. The first set included all ASVAB

scores and those variables selected by prior evaluation (listed in Table 13).

The second set consisted of all variables listed in Table 13 except the

ASVAB variables. Selection of these variables for the final discriminant

models was based on a preliminary discriminant run on the total group which

indicated these variables were most importantly related to the discrimination capability.

Table 6, in the summary section, summarizes the results for the two

discriminant models in terms of effectiveness of selection. It can be

seen that the model using the ASVAB scores was most successful in both

initial discrimination and when applied to the validation group. This

model accounted for 31.1% of the variance in live fire performance and

yielded 86.6% total correct classifications in the calculation group,

with 88.3% correct selections and 66.7% correct rejections. For the validation group, this model yielded 82% total correct classifications, 86.9%

34
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Table 13

Final Set of Variables Included in

Live Fire Discriminant Analyses

ASVAB Scores

S.GM - General Maintenance

-~EL - Electronics

MM - Mechanical Maintenance

CO - Combat

FA - Field Artillery

GT- General Technical

CL - Clerical

OF - Operator and Food

ST - Skilled Technical

SC - Surveillance and Communicat ions

5~5.Other Variables

Right Eye Acuity

Left Eye Acuity

Wearing Corrective Lenses

- Eye Color

Lateral Phoria

Smoking Behavior

Prior Rifle Experience

Prior Shotgun Experience

Prior Pistol Experience

M16 Qualification

Months in Service

Hand Length

Handedness

f-37
correct selections, and 33.3% correct rejections. The second model,

excluding the ASVAB scores, fared less well. This accounted for only

9.9% of the criterion variance and yielded only 84.7% total correct

classifications in the calculation group, with 86.2% correct selections

and 50% correct rejections. For the validation group, this model yielded

* 85.1% correct classifications and these were all correct selections - the

model did not reject any gunners as unlikely to hit the target. These

data are illustrated numerically in Table 14 for the validation group

results using the ASVAB included model and in Table 15 for the model

using only the remaining variables. These are also compared to actual

live fire successes for the validation group, which amounted to 85.1%

for this subset of the gunners.

The best these models could be expected to produce is represented

by the thirteen variable model including the ASVAB scores; on the calculation case this yielded 88.3% correct selections. When compared to the

overall live fire success rate of the unselected gunners in the test -

84.4% - this yields only a 3.9% improvement in potential performance.

In the validation case the percent correct selections was only 86.9%, or

a 2.5% improvement over the unselected and virtually untrained gunners

in the test. These comparisons indicate that further development of

selection models for TOW gunner placement is likely to be both impractical

and not cost-effective.

Table 7 in the summary section shows the variables which were found

to discriminate among hitters and missers in the two models. If USAIS

and the US Army should choose to institute any informal selection process,

these variables should be used as guidelines. Since visual acuity shows

up in both selection models, it would seem feasible to make this check in

units, etc., prior to training or assignment to TOW duties. The data

indicate that gunners with 20/20 vision in both eyes and not wearing

corrective lenses for any purpose are likely to make the better gunners.

Similarly, the data indicate a slight preference for non-smokers, although

this relationship is weaker than that for visual acuity.

Additional Analyses Planned But Not Performed

It was intended that a variety of additional analyses would be performed in support of the TCATA TEA test and in relation to the questions

* -, surrounding selection and prediction of TOW live fire capability. Several

analyses of tracking performance on the M-70 as it related to tracking in

the live fire situation were planned. These were to include both meter

scores and in-flight errors measured from strip charts recorded from the

M-70 tracker as compared to in-flight deviations during live fire. TCATA

analyzed the M-70 meter scores in relation to live fire, both hit/miss

and RDCM, and found no significant relationships, although there was

some indication of a possible relationship between M-70 tracking/training

on a rough surface and live fire performance. Confounding of the data

collection situation during successive subgroup training and testing

(of Group II trainees) renders impossible the continuation of this analysis

with the current data.

38
Table 14

Validation Group Classification for Prediction of

Live Fire Success with ASVAB Scores Included

-. Predicted Performance

Live Fire Performance Would Hit Would Miss

Hit (N=57) 53 4

Miss (N=10) 8 2

Total (N=67) 61 6

(Excluding

- * System Failures)

Correct Selections = -L3 = 86.9% 61

Correct Rejections = -Z= 33.33% 6

Actual Success = =85.1% x 67

39
Table 15

Validation Group Classification for Prediction of

Live Fire Success without ASVAB Scores

Predicted Performance

Live Fire Performance Would Hit Would Miss

Hit (N=57) 57 0

Miss (N=10) 10 0

Total (N=67) 67 0

(Excluding

System Failures)

57 Correct Selections 85.1%

67

Correct Rejections = - = 0

57

Actual Success = 6 = 85.1%

40

II"I
The analysis of the in-flight error scores during M-70 training

and live fire tracking would still be possible. However, it is a very

personnel-intensive process, requiring individual reading of many strip

-\ charts to reduce the data. Further, given the outcome of the overall

TOW TEA test, it would appear that the need for this analysis is greatly

reduced.

It was also intended to reduce and report the data from a series

of questionnaires which were to have been administered to all trainees

in the test, before training, after training, and after live fire. Again,

* changes in test plans resulted in these questionnaires having been administered only to Group I of the trainees. Since these data would have been

only for a third or less of the trainees in the test and thus were unusable

for the prediction/selection effort, they were not analyzed.

N .

.41
REFERENCES

Fleishman, E.A. "Analysis of positioning movements and static

reactions," J. Exp. Psychol. Vol 55, 1958, pp. 13-24.

Fleishman, E.A. and Hempel, W.E. "The relation between abilities and

improvement with practice in a visual discrimination task," J. Exp.

Psychol. v. 49, 1955, pp. 301-310.

1 leisnr.an, E.A. and dempel, W.E., "Factorial analysis of complex

psychomotor performance and related skills," J. Applied Psychol, v. 40,

1956, pp. 96-104.

Maxey, J. L. TOW Weapon System, Analysis of TOW Gunnery, Fort Benning, GA:

Litton-Mellonics Task report. November 1977.

Nie, N. H., Hull, C. H., Jenkins, J. G., Steinbrenner, K. and Bent, D. H.

Statistical Package for the Social Sciences 2nd Ed., New York: McGraw Hill,

1975.

Stewart, S. R., Christie, E. I., and Jacobs, T. 0., Performance Correlates

of the Dragon Training Equipment and the Dragon Weapon System, Draft Final

Rept. NAVTRAEQUIPCENN61339-74-C-0056-1, Alexandria, Va., Humrro, March 1974.

TRADOC Combined Arms Test Activity, Training Effectiveness Analysis (TEA)-

TOW (Part I) Hq TCHTA, Fort Hood, TX, Sept. 1978.

4'. " " -""' '' ".. ."i.' ." 42 " ' i - , ." '. , ,.. . .i.--. , . : ,
APPENDIX A

Table of Variables Used in

TOW Gunner Selection

'AV
Table A

Variables Collected for Use in Prediction of

TOW Gunner Success

1. ASVAB Scores

GM - General Maintenance

EL - Electronics

MM - Mechanical Maintenance

SC - Surveillance and Communications

CO - Combat

FA - Field Artillery

TG - General Technical

CL - Clerical

OF - Operator and Food

* ST - Skilled Technical

2. Other Variables

Height

Weight

Shoulder Width

Trunk Length

Upper Arm Length

Lower Arm Length

Upper Leg Length

Lower Leg Length

Hand Length

Hand Span

Middle Finger Length

Handedness

Footedness

Pursuit Rotor Errors

Pursuit Rotor Time

Steadiness, Hand

Prior Sports Participation

Smoking Behavior

Color Blindness

Eye Color

Vertical Phoria

Lateral Phoria

Right Eye Far Acuity

Left Eye Far Acuity

Wearing of Corrective Lenses

Occular Dominance

Depth Perception

M16A1 Qualification Level

4A.,

A2
Table A (Cont'd)

:'S Other Variables (Cont'd)

Age

Total Months Military Service

Rifle Experience

Pistol Experience

Shotgun Experience

M-70 Average Meter Scores

Pay Grade

~,

'.:

A3
9779

APPENDIX B

A Summary Tables for Discriminant Analyses

Tables Bl - B8a: Tables for Discriminants on Training Success with

M-70 Initial Performance Included.

Tables B9 - Bl6a: Tables for Discriminants on Training Success without

M-70 Performance.

B

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