the SFQC, students must navigate through fields and woods.
Candidates normally receive two scores on each of the six
military orienteering exercises: a time score (recoded into
minutes for the analyses) and a summary performance rating
(3=Outstanding; 2=Satisfactory; 1=Unsatisfactory) based on the
time score.?

L lligence and Physical Fitni cores. Basic
intelligence was measured by the Wonderlic Personnel test and
fitness was measured by scores on the standard Army Physical
Fitness Test (APFT). Both measures were obtained during SFAS in-
processing. These measures were included in several analyses in
an attempt to replicate results of earlier Q Course research
(Pleban et al., 1988; 1989).

SFOC Land Navigation Scores. The criterion measure is

performance on the final land navigation field examination.
Fricke (1990), former commander of Phase I training, describes
the exam as "a go/no-go practical exercise over varying terrain
in which the student must navigate a course 18 kilometers long
and find four points in nine hours. The course begins at 2 a.m.,
forcing the student to navigate part of the course in darkness.
Students who fail the exam will take remedial training and re-
test 15 days later" (p. 5). Students who fail the re-test are
either dropped from the Q Course or recycled into another class.

Analyses

Correlational and mean difference analyses were conducted to
determine which variables were significantly related to land
navigation performance. Multivariate discriminant analyses were
also conducted to identify predictors that explained unique
variance in land navigation performance.

For most analyses the criterion was a dichotomous pass/fail
criterion coded "1" if the student passed the land navigation
field exam on the first try, and "2" if the student did not pass
the exam on the first try. We also conducted exploratory
analyses in which students who failed on the first try were
divided into two final outcome groups: those who later passed a
re-test (during the same or a later course) and those who failed
all re-tests. The purpose of creating the three outcome
criterion was to capture more of the real criterion variance.
Results based on this grouping should be interpreted with
caution, however, because of the small sample sizes and the

2In some cases, however, candidates fail to complete an event (e.g., they get lost, give up, or exceed the maximum time
and are picked up). When this occurs, the individual receives an unsatisfactory rating for the event and no time score is recorded.
In order to make the analyses of time scores comparable to those of the ratings, we attempted to use the same sample with each.
Thus, individuals who failed to complete an event were assigned a time score equal to the maximum actual score for the event, plus
five minutes. Across each of the six events, these individuals comprised no more than 6.5% of the ‘sample.

9



Appendix A

Psychometric Properties of the Project A Spatial Tests?

Campbell & Zook (1991, p. 38; 1992, pp. 96-97) reported a
series of factor analyses of scores on the spatial tests and the
ASVAB subtests that were conducted at various stages of Project A
and its follow-up, the Career Force project. Pertinent results
are summarized in Table A-1. As can be seen, all three analyses
isolated distinct ASVAB and spatial factors. Another consistent
finding was that the Map test had the highest loading on the
ASVAB factor and Maze had the lowest. Maze, on the other hand,
had the highest loading on the spatial factor.

This finding is somewhat replicated by another analysis of
the Concurrent Validation data reported by Campbell and Zook
(1991). For each Project A measure, the authors computed a
"Uniqueness Estimate," the proportion of total variance that was
reliable but unrelated to ASVAB - i.e., the test’s reliability
minus the R? obtained when it is regressed on the ASVAB subtests.
The uniqueness estimates were: Map .46 (lowest of the six spatial
measures); Orientation .60; Maze .74 (second highest of the
spatial tests). Once again, Map appears to be the most
influenced by general cognitive ability and Maze the least.

One final bit of evidence for the relative g-loadings of the
measures comes from Busciglio’s (1990) analysis of the Project A
Concurrent Validation data. The author employed stepwise
regression analyses to assess a total of 132 predictor-criterion
relationships in which the Project A measures could increment the
validity of an empirically determined best possible combination
of ASVAB subtests. In these procedures, the ASVAB subtests were
entered first, significant subtests were retained, and then the
Project A tests were entered and significant incremental
predictors were determined. Since the analyses used a very broad
range of criterion measures - many of a nonspatial nature - it
can be argued that overall incremental validity would come from
tapping general cognitive skills. The results, as shown in Table
A-2, indicate that the Map test was the strongest incremental
predictor and the Maze test was the weakest.

Other factor analyses using the spatial measures alone
reveal more about the three tests in the present study. For
example, Campbell and Zook (1992) reported that exploratory
factor analyses on the Concurrent Validation sample and two
samples from the Longitudinal Validation supported a two factor
solution: 1) power tests, including Map and Orientation,

All studies cited in this Appendix are included in the list of references.

A-1



reading written exam (11%) or the land navigation field exam
(50%).

In contrast to their earlier results (Pleban et al., 1988),
Pleban et al. (1989) found a significant correlation (r=.29)
between Wonderlic scores and pass/fail status in Phase I. The
correlation between the Wonderlic and go/no-go status on the land
navigation field exam was about the same magnitude (r=.28) .

There was also a strong correlation between the Wonderlic and
scores on the map reading written exam (r=.52).

The Pleban et al. (1989) analyses also identified prior
training as a factor in land navigation performance. Ranger
qualified students, for example, had markedly higher Phase I pass
rates (84%) than the class as a whole (62%). It is possible that
soldiers who volunteer for Ranger school have more aptitude for
SF than the average soldier. A simpler explanation, however, is
that Rangers do better in SF training because of their prior
training and experience in relevant skill areas (e.g., land
navigation, patrolling) .

The importance of prior experience in land navigation was
also shown in Peters, Bleda, and Fineberg’s (1979) research. In
a small (n=30) sample of Infantrymen, Peters et al. (1979)
examined background characteristics, Armed Forces Qualification
Test (AFQT) scores, perceptual style (field dependence), and
self-ratings of general sense of direction as predictors of
performance on a dead reckoning task. Only one variable, the
number of times the soldier had participated in land navigation
exercises previously, was significantly related to performance.
Furthermore, poor navigators demonstrated obvious deficiencies in
basic compass, map reading, and pace counting skills, supporting
the authors’ conclusion that insufficient training or experience
could explain performance problems.

A more recent study using a field performance criterion was
conducted by the present authors (Busciglio, Teplitzky, &
Welborn, 1991) in an assessment setting. The sample included
almost 500 candidates in the Special Forces Assessment and
Selection (SFAS) program. Predictors included Wonderlic and
physical fitness test scores, in addition to three measures of
spatial ability, ARI’s Map, Maze, and Orientation tests.
Dependent variables included times and ratings on six military
orienteering events, plus composite measures of performance.

Results showed that two of the spatial tests (the Map test,
and to a lesser extent, the Orientation test) were positively
related to military orienteering performance. Correlations of
Map and Orientation test scores with orienteering times and
ratings ranged from .20 to .27 for five of the six events.
Correlations with a composite measure of performance (based on
ratings) were .33 for the Map test and .30 for the Orientation

3



Table 3

T-Test Results and Correlations for Predictor Variables and Land
Navigation (Pass vs. Fail First Try)

Land Navigation Performance

Pass (N=167) Fail (N=65)

Predictor M sD M sD t xr
Spatial Scores
Map 13.70 4.65 10.88 5.30 3.99*** ~255***
Orientation 16.72 5.73 14.71 6.28 2.34* .153*
Maze 19.47 3.37 18.09 3.94 2.66** -173**
Orienteering Times (in Minutes
I Day 100 45.83 107.73 49.67 -1.13 -.074
I Night 86.23 43.25 95.07 49.86 -1.34 -.088
II Day 119.10 43.53 131.92 49.91 -1.93 -.126
II Night 102.13 46.89 114.13 48.56 -1.74 -.114
III 146.16 51.10 153.42 54.60 -0.95 -.063
Iv 249.47 74.48 273.00 84.28 -2.08* -.136*

Orienteering Ratings

I Day 2.04 0.44 1.94 0.46 1.57 -103
I Night 2.25 0.53 2.15 0.54 1.18 077
II Day 1.87 0.34 1.74 0.44 2.13* -156*
II Night 1.97 0.34 1.95 0.37 0.32 -021
III 1.90 0.33 1.85 0.40 1.12 .074
Iv 1.96 0.23 1.86 0.35 2.07* .161*
Ini ligen and Fitni

Wonderlic 26.04 5.65 24.12 5.75 2.30* .150*
APFT 239.90 22.89 239.18 24.05 0.21 .014

Note. Mean Orienteering times have been rescaled for security reasons; proportionality across events and magnitude of effects
(PASS VS. FAIL) in original data have been retained. Correlations are point-biserial. ***p<.001. **p<.01. *p<.05.

all three spatial tests. They also had better times on one
orienteering event (IV), higher ratings on two events (II Day and
IV), and better scores on the Wonderlic.

The predictor/criterion point-biserial correlations show the
same pattern of significant results. The correlational results
also partially replicate findings from earlier Q Course research.
Like Pleban et al. (1989), we found no significant relationship

13



Technical Report 1015

Predicting Land Navigation Performance in the
Special Forces Qualification Course

Henry H. Busciglio and Martha L. Teplitzky
U.S. Army Research Institute

Selection and Assignment Research Unit
Michael G. Rumsey, Chief

Manpower and Personnel Research Division
Zita M. Simutis, Director

U.S. Army Research Institute for the Behavioral and Social Sciences
5001 Eisenhower Avenue, Alexandria, Virginia 22333-5600
Office, Deputy Chief of Staff for Personnel
Department of the Army

October 1994

Army Project Number Manpower and Personnel

2Q263007A792
Approved for public release; distribution is unlimited.



Oltman, P. K., Raskin, W., & Witkin, H. A. (1971). Group embedded

figures test. Palo Alto, CA: Consulting Psychologists
Press.

Peters, J. I., Bleda, P. R., & Fineberg, M. L. (1979). Effects of
illumination level and sense o irection on land naviga-

tion performance (ARI Technical Report 362). Alexandria,
VA: U.S. Army Research Institute for the Behavioral and

Social Sciences. (AD A071 104)

Peterson, N. G. (Ed.). (1987). Development and field test of the

al 2. oje (ARI Technical Report 739).
Alexandria, VA: U.S. Army Research Institute for the
Behavioral and Social Sciences. (AD A184 575)

Pleban, R. J., Thompson, T. J., Valentine, P. J., Dewey, G. I.,
Allentoff, H. L., & Wesolowski, M. A. (1988). Selection and
assessment ecial Forces Qualification C se candi-

dates: Preliminary issues (ARI Research Note 88-37).
(AD A196 245)

Pleban, R. J., Allentoff, H. L., & Thompson, T. J. (1989).

Preliminary assessment of selected predictors of special

force: ualifi ion cour: success (ARI Research Report
1539). Alexandria, VA: U.S. Army Research Institute for the
Behavioral and Social Sciences. (AD A213 201)

Scholl, M. J. (1988). The relation between sense of direction and
mental geographic updating. Intelligence, 12, 299-314.

Scholl, M. J., & Egeth, H. E. (1982). Cognitive correlates of
map-reading ability. Intelligence, 6, 215-230.

Simutis, Z. M., & Barsam, H. F. (1983). Terrain visualization and
map reading. In H. Pick & L. Acredelo (Eds.), Spatial
Orientation. New York: Plenum Press.

Stasz, C., & Thorndyke, P. W. (1980). The influence of visual-
spatial ility and stu ocedures on maj earning skill
(Rand Note N-1501-ONR). Alexandria, VA: Office of Naval
Research.

Thorndyke, P., & Stasz, C. (1980). Individual differences in
procedures for knowledge acquisition from maps. Cognitive

Psychology, 12, 137-175.
Weitzman, D. 0. (1979). Individual differences in geographic
orientation and spatial memory representation. Paper

presented at the American Psychological Association annual
conference (Sep. 1979), New York.

24



possibility that re-test results reflect practice effects rather
than basic spatial aptitude.

Results
D riptive istics

Means (M) and standard deviations (SD) for the predictors
are displayed in Table 1, for both the present sample and the
original SFAS sample (Busciglio et al., 1991). In the SFQC
sample there is a very slight increase (about one to two tenths
of a standard deviation) in the means on the spatial test and
military orienteering ratings relative to the initial SFAS sample
(Busciglio et al., 1991). This indicates that a small number of
the poorest performers on these measures were not admitted to the
Q course. The restriction in range is so slight for these
measures, however, that the potential for significant
correlations between these predictors and the land navigation
criterion variable should not be seriously diminished.

Table 2 shows intercorrelations among the predictor
variables for the entire sample. The three spatial tests exhibit
moderately high intercorrelations (r=.48 to .52) and Map test

scores were strongly related to Wonderlic scores (r=.66). These
results are very similar to those obtained for the entire SFAS
sample (Busciglio et al., 1991). Intercorrelations among the

orienteering times are nearly all significant, but quite low
(x=.12 to .36) and similar in magnitude to those obtained in the
SFAS sample. Correlations among the orienteering ratings,
however, are largely nonsignificant and lower than those obtained
in the SFAS sample. This reflects the impact of the reduced
variance in the SFQC sample; there are very few students in the
SFQC with unsatisfactory ratings on more than two events.

Mean Differences on Predictor Variables across Criterion Groups

Pass vs. fail first try. In these analyses, we examined
mean spatial, orienteering, intelligence, and fitness scores for
trainees who passed the SFQC land navigation course on the first
try (n=167, 72%) and those who did not (n=65, 28%). Table 3
shows the means for both groups, the results of t-tests to assess
the statistical significance of the mean differences, and point-
biserial correlations between each predictor and the criterion
variable.*

The t-test results showed that those who passed land
navigation on their first try had significantly higher scores on

Readers should consider the t-test and correlational significance levels as suggestive only, since no attempt was made
to control the experiment-wide error rate; for instance, at alpha=.05, approximately 1 of the 17 comparisons shown in Table 3 will
appear significant due to a Type | error.

10



land navigation on their first try) tend to have higher Map test
scores than other trainees, while the poorest performers (those
who fail both the first test and later re-tests) are more likely
to have unsatisfactory IV ratings.

Map Test Cut-Score Analyses

The results above suggest that it might be appropriate to
use the Map test to identify SFAS candidates likely to have
trouble with land navigation in the Q Course. To explore this
possibility, we performed a series of hypothetical cut-score
analyses with Map test scores.‘ These analyses are intended to
provide an estimate of the potential costs and benefits of using
spatial ability as a prerequisite for the Q Course.

We began by dividing students into six nearly equal sized
groups, based on Map test scores. Then we determined first time
pass rates for each group. As shown in Table 5, less than half
(48%) of the students in the lowest scoring group passed the land
navigation test on their first try. The pass rate generally
increases with Map score range, first steeply and then more
gradually. These results, in general, suggested two possible
cut-scores, 7 and 11.

Table 5

Land Navigation Pass Rates for Different Map Test Score Ranges

Map Test Number Percent Percent Pass
Score Range in Group of Sample ist Try
Oo- 6 33 14 48
7 - 10 38 16 63
11 - 13 43 18 77
14 - 16 43 19 72
17 - 18 44 19 82
19 - 20 31 13 87
TOTAL 232 100

In Table 6 we show how cut-scores of 7 and 11 on the Map
test would have affected class size and overall 1st time pass
rates, if applied to the present sample. A minimum Map test

‘Another research opportunity revealed here is to explore different ways to Use data from the military orienteering events
to select trainees for SFQC. Such analyses, however, should be conducted using the FY91-93 SFAS Database, a much larger and
more recent sample than what is available here. The present authors are planning such research - see the Discussion section for
more on this topic.

16



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Weitzman, D. 0. (Unpublished paper). Individual differences in
spatial memory: Thinking backwards. Alexandria, VA: U.S.
Army Research Institute for the Behavioral and Social
Sciences.

Zazanis, M. M., Diana, M., & Teplitzky, M. L. (1994). FY89-92
Special Forces Qualification Course class database:
nical manual a code_ bo. (ARI Research Product
94-15). Alexandria, VA: U.S. Army Research Institute for
the Behavioral and Social Sciences. (AD A284 723)

25



find a relationship between spatial abilities and land navigation
performance in this sample if the relationship is substantial
across the full range of spatial ability levels.

Method

Sample

A total of 297 candidates successfully completed one of the
two SFAS classes (3/89 and 4/89) in which we administered the
spatial ability tests. SFQC data (i.e., land navigation scores)
were gotten by matching the social security numbers of the SFAS
graduates with social security numbers from the FY89-92 SFOC
Longitudinal Database (see Zazanis, Diana, & Teplitzky, 1994).
The 232 soldiers we found in the SFQC database made up the sample
for this research.

Measures

Proj A ial Tests. A researcher employed by the
Special Warfare Center administered the three paper-and-pencil
spatial tests (Map, Maze, and Orientation) to candidates in the
3/89 and 4/89 SFAS classes (spring 1989) during the in-processing
and preliminary testing phase of the program. Candidates were
told that the instruments were for research purposes only, and
would not be used for evaluation purposes.

All three spatial tests were originally developed in Project
A, ARI'’s effort to develop and validate a comprehensive battery
of personnel tests (see Campbell & Zook, 1991). The spatial
tests were designed to measure cognitive ability domains not
covered by the Armed Services Vocational Aptitude Battery
(ASVAB), the instrument now used by the Army for its entry-level
enlisted selection and classification decisions (Peterson, 1987).
Literature reviews and surveys of subject matter experts were
used to isolate the constructs that appeared to be most promising
for this purpose.

The Map and Orientation tests were developed to measure a
construct called Spatial Orientation - the ability to "maintain
one’s bearings with respect to points on a compass and to
maintain appreciation of one’s location relative to landmarks in
the environment" (Peterson, 1987, p. 3-29). On the Map test, the
examinee works with a schematic map that contains familiar
landmarks (e.g., forest, lake). Given the direction of one
landmark to another, the examinee must figure out the direction
from a given third landmark to a specific fourth one. The Map
test consists of 20 items and has a 12 minute time limit.

The Orientation test contains 24 items with a 10-minute time
limit. Each item contains a picture within a circular or
rectangular frame. The bottom of the frame has a circle with a

7



PREDICTING LAND NAVIGATION PERFORMANCE IN
QUALIFICATION COURSE

THE

SPECIAL

FORCES

CONTENTS
Page
INTRODUCTION . «© 1. ee 6 ee ee ee ee ee ee ee es 1
Background Pe 1
Land Navigation Research . ~~. + e+ e+ 6 e+ ee ee eee 2
Spatial Abilities Research .. ~. +s e+ e+e ee eee 4
METHOD . . 1 6 6 6 © © 6 eo ee ee ee we ee ee et 7
Sample 6 6 we ee ee ee ee ee ee ee ee 7
Measures a 7
Analyses Pe ee ee we 9
RESULTS . 6 6 6 6 ee ew ee ee we ww ee ee eee ee 10
Descriptive Statistics eee rary 10
Mean Differences on Predictor Variables
Across Criterion Groups ..... 6+ s+ 6 6 ee ee ee 10
Unique Variance Explained by Predictors .......--. 15
Map Test Cut-Score Analyses . . 2. 6 + + 2 ee se eee 16
DISCUSSION . . 2. we ee ee ee ee ee ee eee ee 18
REFERENCES . . 2 6 6 © © © © © © © ee ee ee we ee ee 23
APPENDIX A. PSYCHOMETRIC PROPERTIES OF THE PROJECT A
SPATIAL TESTS . «©. 6 6 es ee we ew we ew we ew A-1
LIST OF TABLES
Table 1. Means (M) and Standard Deviations (SD) for
Predictor Variables in SFQC Sample and Original
SFAS Sample eS 11
2. Intercorrelations for Predictor Variables ers 12
3. T-Test Results and Correlations for Predictor
Variables and Land Navigation (Pass vs. Fail
First Try) 2. 6. 6 ee ee ee ee ee ee ee 13
4. Results of ANOVA Testing Mean Differences in
Predictor Variables Across Three Land Navigation
Performance GroupS . . 6. 6 6 6 ee ee ee eee 14

ix



alternative interpretation rests on the fact that of all the
military orienteering events, event IV is most similar to the
land navigation field exam in terms of length and physical
difficulty. It is possible that candidates who fail the event
are more likely to fail land navigation simply because they lack
the strength, endurance, or determination to persist in a long
and difficult task. Future research might clarify this issue by
examining how other measures of fitness and motivation (e.g.,
ruckmarch times) are related to land navigation performance.

Future research might also suggest ways to fine-tune the
efficiency of the military orienteering events as assessment
events. For example, an analysis of land navigation pass rates
as a function of different time score categories might suggest
different standards for satisfactory performance. Ideally this
would be accomplished by recording orienteering scores but
suspending their use in selection decisions. However, useful
analyses could still be conducted even if this were not possible.
Another possibility is to make one or two events more demanding
in terms of the spatial ability and/or orienteering skills
required and track the relationship between performance on these
events and land navigation. :

Overall, however, the lack of a strong linear relationship
between military orienteering scores and land navigation suggests
that current SFAS selection criteria are effectively screening
out most low potential candidates. Major changes would be
indicated only if the correlation between MO performance and land
navigation were quite high.

Another, more involved project would attempt to clarify
underlying causal relationships and interactions across several
types of predictors. These might include: 1) a map test that is
more sophisticated and clearly knowledge based, 2) other abstract
spatial ability measures, and 3) self-reports or "biodata"
measures of past training and experience in map-reading,
orienteering or navigation. For example, one set of analyses
could attempt to determine the importance of prior experience and
acquired map skills relative to spatial-visual abilities as
determinants of field performance. Path analyses could also help
clarify the potential mediating role of map reading skills in the
relationship between abstract spatial-visual abilities and land
navigation performance.

At a minimum, it would be worthwhile to replicate the
present analyses using a larger sample of current Q course
students. If the Map test or some similar instrument were
administered just before the land navigation course, results
showing the potential utility of this type of test as a selection
tool could be obtained fairly quickly. We are also planning this
type of research with another Project A spatial test, Assembling
Objects, that has shown great promise in previous settings.

22



Thorndyke and Stasz’s (1980; Stasz & Thorndyke, 1980)
results suggest that training can improve performance to some
extent; however, the effectiveness of training depends on, or is
moderated by spatial ability. Thorndyke and Stasz (1980) found
that subjects who showed better spatial recall adopted a more
systematic approach to a map learning task and employed more
spatial-visual strategies (e.g., imagery, pattern encoding) in
memorizing and using map information. In fact, even experienced
map users did well on the recall task only if they used these
learning strategies.

In a follow-up study, Thorndyke & Stasz (1980) attempted to
determine if less skilled subjects could be trained to use the
more effective strategies. They found that performance improved
with as little as 30 minutes of training and practice. They also
found, however, that high visual memory subjects benefitted most
from training, and used the effective strategies more frequently
and with better results.

Kozlowski and Bryant (1977) found somewhat similar results.
Subjects who reported having a "good sense of direction" (and who
also appeared to have better spatial-visual abilities) showed
improved performance over several trials of a tunnel maze
learning task, while "poor sense of direction" subjects did not.
In a similar vein, Weitzman (1979) found that NCO’s with greater
spatial ability did better at using cues or prior information
about the task to improve their performance.

In the research cited above, the training provided to
subjects was minimal, yet the moderating effect of spatial
ability on training effectiveness was clearly apparent. In
contrast, land navigation training in the SFOQC is long and
intensive. Nevertheless, it is possible that a similar ability
by training interaction may be operating in the Q Course.

The fact that pre-training measures (e.g., the Map test) are
related to post-training performance suggests that even intensive
instruction cannot fully compensate for individual differences in
spatial ability. The Map-test cut-score analyses, for example,
showed that only about half of the low ability trainees (scores
below 7) passed the field exam the first time. In contrast, pass
rates for the moderate and high ability students ranged from 77%
to 87%. One interpretation is that high spatial aptitude
students benefit more from the map reading and orientation
training they receive, and this accounts for their higher first
time pass rate.®

*Of course, another hypothesis is that spatial ability and training are additive factors in determining land navigation
performance (i.e., the relationship between spatial test scores and land navigation performance is unaffected by training). A-strong
test of this hypothesis would require measuring land navigation both before and after training.

19



ACKNOWLEDGMENTS

We would like to express our appreciation to the following
individuals for their valuable assistance:

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

Sciences
Clinton Walker

U.S. Army John F. Kennedy Special Warfare Center and School
COL Travis Griffin
LTC David McCracken
MAJ Juan Orama

Special thanks also to Michael Rumsey, Selection and
Assignment Research Unit Chief, and to Paul Gade and Fred Mael
for their astute and constructive comments on earlier drafts of
this paper.



FOREWORD

The increase in the variety and complexity of Special Forces
missions throughout the world has created a need for systematic,
comprehensive procedures for assessing Special Forces candidates.
In response to this need, the U.S. Army John F. Kennedy Special
Warfare Center and School (USAJFKSWCS) started the Special Forces
Assessment and Selection (SFAS) program in June of 1988 to iden-
tify candidates with a high potential for success in the Special
Forces Qualification Course (SFQC). At the same time, the Spe-
cial Warfare Center asked the U.S. Army Research Institute for
the Behavioral and Social Sciences (ARI) to collaborate on
research designed to examine and fine-tune the Special Forces
(SF) selection process. ARI has a commitment, confirmed in the
June 1991 Memorandum of Agreement with the U.S. Army Special
Operations Command, to support Special Operations Forces through
research on the skills and aptitudes required in our elite
forces.

This particular project examines spatial ability tests, SFAS
military orienteering scores, and other measures as predictors of
performance on the Q Course land navigation field exam. The
spatial ability measures were paper-and-pencil tests developed
and validated by ARI’s Selection and Assignment Research Unit as
part of Project A. The military orienteering and land navigation
events were designed and administered to SF candidates by the
Special Warfare Center during the normal course of their assess-
ment and training programs. Research in this area is important
because land navigation is critical in special operations and
these skills are difficult and costly to teach.

The research was a collaborative effort by ARI and
USAJFKSWCS, sponsored by the Chief Psychologist of the Special
Warfare Center and completed under the Selection and Assignment
Research Unit’s research program on Special Screening Tests for
Critical MOS. The results have been briefed to the sponsor and
were found to be useful because they not only highlight the
importance of abstract spatial abilities but they also provide
the first empirical examination of the relationship between SFAS
military orienteering events and land navigation. Further
research should allow us to fine-tune diagnostic and selection
instruments and ultimately enhance the effectiveness of SF
assessment and training.

EDGAR M. JOHNSON
Director



dot inside it. The picture or scene, said to be immovable, is
not in an upright position. The task is to mentally rotate the
frame so that the bottom of the frame is positioned at the bottom
of the picture. After doing so, the subject must then pick where
the dot will appear in the circle, among five alternative
answers.

The Maze test was developed to measure Spatial Visualization
- Scanning. Spatial visualization is the ability to "mentally
Manipulate components of two- and three-dimensional figures into
other arrangements." Scanning is the ability to "visually survey
a complex field to find a particular configuration representing a
pathway through the field" (Peterson, 1987, p. 3-5). Each item is
a maze with several entrances and exits. Subjects must determine
which one of the entrances will lead to an exit. Examinees have
5 1/2 minutes to complete the 24 item test.

A number of authors have reported data on the reliability of
these three tests (cf. Campbell & Zook, 1991, 1992). In general,
the results support the assertion that all measures have adequate
internal consistency and test-retest reliability. Several factor
analytic and correlational studies have also been conducted,
primarily to determine whether or not the spatial tests were
redundant with more general measures of cognitive ability (see
Appendix A for a detailed description of this research). The
results of these studies suggest that (a) all three tests measure
important aspects of general spatial ability; (b) the influence
of general cognitive skills is strongest on the Map test and
weakest on the Maze test; (c) Map and Orientation are power tests
while Maze is a speeded test; and (d) Map and Orientation do, in
fact, converge on an "Orientation" construct.

SFAS Military Orienteering Scores. Four of the 21 days of

the SFAS program are devoted to military orienteering. Only a
basic (skill level I) familiarity with land navigation concepts
is required for these events. However, to simulate the
operational environment, candidates are given little feedback on
their performance and must carry a heavy rucksack as they
navigate their way from one point to the next. SFAS cadre
observe that physical endurance, motivation and the ability to
operate comfortably at night appear to be important to success in
SFAS military orienteering.

The military orienteering events take place between the
seventh and tenth days of SFAS, immediately before the end of
Phase I. On the seventh and eighth days, daytime events (I Day
and II Day) are followed by nighttime events (I Night and II
Night). The third (III) and fourth (IV) events take place on the
ninth and tenth days, respectively. The last event (IV) is the
longest and most similar to the SFQC land navigation exam. An
important difference between the SFAS and SFQC events, however,
is that in SFAS, candidates can navigate along roads, whereas in

8



3. Students with very low scores on the Map test had
considerably lower first time pass rates (48%) on the
land navigation field exam than other students (76%).

Utilization of Findings:

Land navigation performance in the SFQC appears to be a
function of both spatial aptitude and orienteering skills and
techniques acquired through experience. The modest effect sizes
for the spatial measures in this research do not allow us, at
this point, to recommend the use of the Map, Orientation, or Maze
tests as selection criteria for SF training. The results do,
however, suggest that spatial aptitude is a factor in training
and performance and that additional research in this area is
warranted. Future analyses, for example, might focus on deter-
mining the extent to which general intelligence can compensate
for the lack of spatial aptitude. In the interim, the Map test
might be used as an efficient, low-cost way of providing prospec-
tive Special Forces trainees with feedback about their prospects
for success in land navigation training. Such feedback might
encourage self-selection out of the program or personal efforts
to improve skills through study and practice. For purposes of
selection screening, we are planning research with another Proj-
ect A spatial test, Assembling Objects, that has shown great
promise in previous settings.

viii



between APFT scores and land navigation performance. Also, while
our correlation between Wonderlic test scores and performance on
the land navigation test (r=.15) is lower than that found in the
earlier research (r=.28 in Pleban et al., 1989), it is still
positive and significant.

Pass first try vs. pass re-test vs. fail all re-tests. For
the three outcome analyses, the 65 trainees who did not pass land
navigation the first time are divided into those who later passed
a re-test (n=46, 20% of total sample) and those who failed all
re-tests (n=19, 8%). Analysis of variance (ANOVA) results to
identify significant differences are displayed in Table 4.

Table 4

Results of ANOVA Testing Mean Differences in Predictor Variables
Across Three Land Navigation Performance Groups

Cell Means for Different Levels of

Land Navigation Performance
Pass lst Try Pass Re-test Fail Re-Test

F Ratio (N=167) (N=46) (N=19)

Spatial Scores

Map 7.97 13.70 10.98 10.63,
Orientation 2.85

Maze 3.72* 19.47 17.91 18.53
Orienteering Times

I Day 0.64

I Night 1.17

II Day 1.86

II Night 1.68

III 0.53

Iv 2.20
Orienteering Ratings

I Day 1.24

I Night 0.84

II Day 3.11* 1.87 1.72 1.79
II Night 0.06

III 0.97

Iv 6.09** 1.96 1.91 1.74
Intelligence and Fitness

Wonderlic 3.31* 26.04 23.61 25.37
APFT 0.23

Note. Cell means printed for predictors with significant F ratios only. Cell means not differing significantly (by Tukey HSD post-
hoc tests) are connected by underlining. ***p<.001. **p<.01. *p<.05.

14



Technical Report 1015

Predicting Land Navigation
Performance in the Special Forces
Qualification Course

Henry H. Busciglio and Martha L. Teplitzky
U.S. Army Research Institute

pric

ELECTE

October 1994 rr
JAN 19 1995

United States Army Research Institute
for the Behavioral and Social Sciences

roved for public release; distribution is unlimited.

19050117 101



Predicting Land Navigation Performance in the
Special Forces Qualification Course’

Introduction

Background

Land navigation is a critical skill in Special Forces (SF).
In the performance of their missions, SF soldiers are frequently
called upon to navigate through unfamiliar territory, often over
difficult terrain, under the cover of darkness. Consequently,
there is a strong emphasis on land navigation in SF training. In
fact, the Special Forces Qualification Course (SFQC or Q Course)
includes the most comprehensive land navigation program taught by
any Army school (Fricke, 1990). In a week-long block of
instruction, students learn to identify terrain features, find
their positions on a map, measure ground distance, and navigate
cross-country using a map and a compass (Fricke, 1990).

Historically, land navigation has been one of the most
difficult components of the Q Course, with failures on the final
field exam accounting for a large proportion of the attrition
from training (Pleban et al., 1988). Dissatisfaction with the
high Q Course attrition rate (40% to 50%) was one of the factors
that led to the development and implementation of the Special
Forces Assessment and Selection (SFAS) program in 1988. SFAS is
designed to identify candidates who are well suited for SF and to
screen out volunteers who lack the qualities and potential to
complete SF training. Successful completion of the program has
been a prerequisite for the Q Course since June of 1988.

SFAS has been successful in reducing Q Course attrition;
however, the land navigation portion of the training is still
problematic. For example, records maintained by the Special
Warfare Center and School show that in classes 2-90 to 5-90 the
percentage of soldiers who failed the land navigation exam on
their first try ranged from 23% to 46%. Although well over half
of these students passed the re-test exam (second try pass rates
ranged from 52% to 85%), land navigation is still difficult for
many SF trainees.

The primary purpose of this research is to examine the
relationship between three measures of spatial ability and
performance on the SFQC land navigation field exam. This
research builds on earlier work showing the relationship between
spatial ability and performance on military orienteering events
in SFAS (Busciglio, Teplitzky & Welborn, 1991). The analyses are
designed to provide decision makers with data on the potential

+A shorter version of this report was presented at the 1993 Military Testing Association conference. Although a slightly
different sample was used, our overall findings and conclusions are the same.

1



CONTENTS (Continued)

Table 5.

Page
Land Navigation Pass Rates for Different
Map Test Score Ranges 16
Outcomes Associated with Two Hypothetical
Map Test Cut-Scores ee 17



These results, considered in the context of related
research, suggest several courses of action. First, it appears
that the Map test or some alternative spatial-visual ability test
could be used to identify and screen out the few SFAS candidates
who are unlikely to benefit from training in the Q Course.®
Additional research would be warranted to identify the most
appropriate instrument and optimal cut-score in light of current
organizational needs and constraints. A replication of the
present study is especially important because of recent changes
in the structure of the Q Course, possible changes in land
navigation pass rates, and an expected increase in the quality of
future SF candidates as a result of more selective Army
recruiting. As noted earlier, the quality as well as the number
of prospective applicants must be considered with manpower
requirements and resource constraints in decisions about the
practical utility of additional pre-requisites.

A more conservative interim step would be to use the current
Map test or a test tailored specifically for the Q Course as a
diagnostic tool to identify candidates who need to improve their
map skills. Low scoring candidates could be given instructional
Materials and performance standards they are expected to achieve
before they attend the Q Course. Implementation of such an
option could be designed to allow researchers to evaluate the
predictive ability of any new test, both with and without
feedback or counseling for low ability students. Ina related
vein, adding a short block of instruction (or even just providing
a handout) on effective map learning strategies might improve the
performance of individuals who do not naturally use spatial-
visual strategies.

Finally, our results with the orienteering events suggest
several additional research possibilities. For example, it is
interesting that the ANOVA results using three criterion groups
showed that the "pass first try" group had higher Map scores than
other groups, whereas students who failed both the first test and
the re-test were distinguished only by lower MO IV ratings. Of
the few trainees (17, 7% of the sample) who received
unsatisfactory ratings on MO IV, 29% failed both the first test
and at least one re-test, in contrast to only 6.5% of rest of the
sample. Had all 70 of the SFAS candidates who received
unsatisfactory event IV ratings been allowed to attend the Q
Course, the relationship between these ratings and land
navigation performance would undoubtedly have been stronger.

One interpretation for the modest relationship we did obtain
is that candidates who fail event IV lack the experience and/or
spatial ability to pass the land navigation course. An

®Perhaps using an easier form of the Map test to more finely discriminate among low aptitude individuals.

21



General intelligence or cognitive abilities measured by
standard verbal and math tests are also likely to be important
factors in trainability. Intelligence is likely to determine how
easily students can assimilate land navigation course material,
particularly considering the compressed time period available for
learning and practice in the Q Course. Intelligence is also
likely to affect performance on specific tasks that require
verbal comprehension or analytical skills. Scholl and Egeth
(1982), for example, found that tests of verbal and math
abilities were better at predicting performance on a relief test
than spatial orientation and visual memory tests. The superior
predictive power of general intelligence tests in this case
appears to be due to the nature of the criterion task. Unlike
the map recall tests used by Thorndyke & Stasz (1980), the test
in Scholl and Egeth’s study required subjects to follow fairly
complicated written instructions and use multi-step calculations
to estimate altitudes.

These results suggest that, despite the weak relationship
between Wonderlic scores and the land navigation field exam in
the present research, intelligence is probably an important
determinant of performance on other components of the course
(e.g., written tests and math-dependent exercises). Abstract
spatial-visual abilities, on the other hand, may be most critical
on field exercises when conditions preclude constantly checking
one’s map and navigators must rely on mental images of their maps
or survey representations of the terrain to guide them (Weitzman,
unpublished paper) .”

The relative importance and differential predictive power of
intelligence and spatial-visual abilities are difficult to sort
out because in this and other research (Scholl & Egeth, 1982),
these measures are highly correlated. However, research using
more finely differentiated predictor and criterion measures might
clarify how intelligence and spatial abilities jointly or
interactively affect land navigation performance.

In summary, our conclusion that spatial-visual abilities are
related to land navigation performance is consistent with a large
body of previous research in this area. Of the three spatial
tests examined here, Map appears to be the best measure of the
relevant spatial abilities. Cut-score analyses show that
students with very low scores on this test have trouble passing
land navigation and may require more training to perform to
standards - if they are to achieve those standards at all.

7We once again point out that intelligence (Wonderlic) test scores were strongly correlated (r=.52) with performance on
the Q course written map reading exam in the Pleban et al. (1989) research, although the same test was only modestly (r=.28)
related to performance on the field exercise.

20



PREDICTING LAND NAVIGATION PERFORMANCE IN THE SPECIAL FORCES
QUALIFICATION COURSE

‘XECUTIVE SUMMARY

Research Requirement:

The land navigation phase of the Special Forces Qualifica-
tion Course (SFQC) is comprehensive and difficult. Inability to
pass the 18-kilometer go/no-go land navigation field exam is the
single largest cause of failure in the field phase of SF train-
ing. The primary purpose of this research was to assess the
utility of three new Project A spatial ability tests and six
Special Forces Assessment and Selection (SFAS) military orien-
teering events as predictors of performance on this critical
exam. We hypothesized that spatial ability and skill in military
orienteering (i.e., navigating over unfamiliar territory from a
drop-off point to a prescribed destination) would be positively
related to land navigation performance.

Procedure:

Candidates entering two SFAS classes took the Project A Map,
Maze, and Orientation tests, along with tests of general cogni-
tive ability (the Wonderlic Personnel Test), and physical fitness
(the Army Physical Fitness Test, or APFT). Scores on the six
SFAS military orienteering events were obtained at the end of the
program. About half of all SFAS candidates were selected for the
SFQC, and these are the soldiers for whom we obtained the crite-
rion measure--performance on the land navigation field exam.
Univariate and multivariate analyses were conducted along with
analyses designed to illustrate the potential utility of various
hypothetical cut-off scores.

Findings:
The major results of our analyses were as follows:

1. In general, the spatial scores were more useful for
predicting land navigation performance than were the
orienteering, fitness, or intelligence test (Wonderlic)
scores.

2. The Map test was the only predictor to account for
unique variance in whether or not students passed land
navigation on their first try.

vii



Table 1

Means (M) and Standard Deviations (SD) for Predictor Variables
in SFQC Sample and Original SFAS Sample

SFQC SAMPLE SFAS SAMPLE
(n=232) (n=492)

Predictors M sD M sD
Spatial Tests

Map 12.91 4.99 12.45 5.24
Orientation 16.16 5.95 15.45 6.18
Maze 19.08 3.59 18.55 3.77
Orienteering Times (in Minutes)

I Day 100 47.0 100 46.7
I Night 86.58 45.3 82.85 38.6
II Day 119.69 45.7 113.89 35.1
II Night 102.80 47.6 98.76 41.3
III 145.50 52.1 141.51 47.4
Iv 250.15 77.9 240.49 68.2
Orienteering Ratings

I Day 2.01 0.45 1.91 0.50
I Night 2.22 0.53 2.13 0.55
II Day 1.83 0.37 1.77 0.42
II Night 1.97 0.35 1.90 0.40
III 1.89 0.35 1.79 0.43
Iv 1.93 0.27 1.83 0.39
Intelligence and Fitness
Wonderlic 25.50 5.73 24.89 5.93
APFT 239.70 23.17 232.58 26.07

Note. Orienteering ratings were: 3=Outstanding, 2=Satisfactory, and 1=Unsatisfactory. Mean Orienteering times have been
rescaled for test security reasons; proportionality across events in original data has been retained.

11



and 2) speed tests, including Maze (see Table A-3). However, the
same authors reported that a LISREL confirmatory factor analysis
using data from one of the Longitudinal Validation samples
favored a three factor solution: 1) figural reasoning, 2)
orientation - composed of Map and Orientation, and 3) speed,
including Maze. When the authors applied the Schmid-Leiman
(1957, as cited in Campbell & Zook, 1992) transformation, it was
discovered that all the tests loaded more highly on a
second-order factor that included all the spatial tests than on
the three specific factors (see Table A-4). From the analyses
above, we have drawn the following general conclusions:

1) All three tests measure important aspects of general spatial
ability.

2) The influence of general cognitive skills is strongest on
the Map test and weakest on the Maze test.

3) Map and Orientation are power tests while Maze is a speeded
test.

4) Map and Orientation do, in fact, converge on an

"Orientation" construct.

Table A-3

Factor Analysis Results for Project A Spatial Tests
(from Campbell & Zook, 1992)

Loadings
Factor I Factor II

Test cv Lvl Lv2 Cv Lvl Lv2
Power tests:

Assembling Objects -54 .55 .54 -47 .49 .50
Figural Reasoning -59 .54 .54 -40 .46 .42
Map -60 .59 .58 -37  .38 = .38
Orientation -56 .57 .56 +34  .37 .35
Speed tests:

Maze .38 .38 37 .57  .57 155
Object Rotation -32 .36 .34 -52 .54 .52

Note. CV is Concurrent Validation sample from Project A (N = 7939). LV1 and LV2 are two different samples
from the predictor data collection phase of Career Force Longitudinal Validation (Ns = 6929 and 6436, respectively).



Table A-4

Schmid-Leiman Results for Project A Spatial Tests

(from Campbell & Zook, 1992)
Loadings

General Specific Factors:
Test Factor Speed Figural Orientation
Assembling Objects 753 -000 065 000
Figural Reasoning +720 .000 -062 000
Map +685 000 .~000 278
Orientation +656 -000 -000 +266
Maze +624 367 -000 .000
Object Rotation 592 347 -000 000

Note. Sample from predictor data collection phase of Career Force Longitudinal Validation (N = 4723).



score of 7, for example, would have eliminated 14% of the sample
and resulted in a first time pass rate of 76% - a modest
improvement over the current pass rate of 72%. A cut-score of 11
on the Map test would have excluded 30% of the sample and raised
the first time pass rate another 3% to 79%. Of course, the
trade-off for the slightly higher pass rates at cut-scores of 7
and 11 is that relatively large proportions of those excluded
(48% and 56%, respectively) would have successfully completed
land navigation on the first try.

Table 6

Outcomes Associated with Two Hypothetical Map Test Cut-Scores

Cut-Scores
7 11
Percentage of current
sample admitted 86% (199) 70% (161)
First time pass rate
for those admitted 76% (151) 79% (127)
First time pass rate
for those excluded 48% (16) 56% (40)

Note. Current pass rate is 72%.

As Table 6 also shows, the stricter cut-scores would produce
substantially fewer SFQC graduates (151 at a cut-score of 7 and
127 at a cut-score of 11). This happens despite the slightly
higher pass rates, because so many candidates would have been
screened out, and thus not available for the class.

If it is important to produce the highest number of
graduates possible, a cut-score even lower than 7 might be most
efficient. Only a few people would be excluded, and presumably,
these would be the candidates with the lowest probability of
passing the first time. Unfortunately, in the present sample
the number of students with scores at or below 6 is too small to
allow us to project outcomes. Additional research is clearly
warranted, however, to replicate these results and assess the
impact of cut-scores below 7.

The optimal cut-score, of course, depends on organizational
objectives and the availability of qualified candidates. If there
are more qualified candidates than needed, and the primary goal
is to reduce the number of re-tests that have to be administered,
then stricter cut-scores are called for, even if they eliminate

17



ARI Technical Report 1015
13, ABSTRACT (Continued)

to pass land navigation, The Map test and military orienteering scores

might, however, be useful as diagnostic tools. Students with low scores could
be advised that they are likely to be at a disadvantage in the SFQC and
instructed to improve their map reading and navigation skills before attending.
For purposes of selection screening, we are planning research with another
Project A spatial test, Assembling Objects, that has shown great promise in
previous settings.

ii



test. Despite the considerable overlap between the two tests
(Map/Orientation: r=.50), both also explained unique variance in
the composite measure when all three test scores were included as
predictors in a regression equation. In combination, the Map and
Orientation tests explained 13% of the variance in the rating
composite. The Maze test did not enter the regression as a
significant independent predictor.

The spatial test/military orienteering correlations are
intriguing because they show that short paper and pencil tests
have the potential to predict performance on a very different
criterion - the time it takes a soldier to make his way from a
starting point to a landmark several kilometers away. Despite
the variety of factors likely to affect both orienteering times
(e.g., physical endurance, motivation, night vision) and paper
and pencil test scores (e.g., reading level, effort, fatigue)
spatial tests and orienteering do appear to have certain
cognitive requirements in common.

Hunt (1991) reached a similar conclusion based on research
with civilian orienteering enthusiasts. Hunt found that expert
orienteerers performed better than moderately experienced
orienteerers, who in turn performed better than novices, on two
abstract measures of spatial ability: two and three dimensional
spatial rotation tasks, and a spatial orientation test requiring
perspective taking.

On the basis of these and other performance differences,
Hunt (1991) concluded that "Orienteering skill is not limited to
being able to get around in the woods. It seems to be an ability
to build up abstract spatial models of large-space from superior

observation of salient visual cues" (p. 25). An experienced
Ranger instructor put it more simply, noting that "tactical land
navigation requires... the ability to see this flat piece of

paper [the map] as a three dimensional picture" (Johnston, 1991).

The research reviewed above suggests that both general
intelligence and spatial abilities affect how well, or how
quickly individuals can navigate in real-world, natural
environments. Simpler criteria, like performance on map-reading
tests or direction pointing tasks have also been predicted by
cognitive and/or spatial ability measures. This research,
reviewed below, suggests that spatial abilities may affect
overall land navigation performance by facilitating performance
on several different components of the larger task.

atial il es Resear

In the 1970’s, Kozlowski and Bryant (1977) showed that
people are often good judges of their ability to orient
themselves in the real world. Individuals who reported that they
had a "good sense of direction" consistently outperformed "poor

4



scores will be related to performance on the SFQC land navigation
field exam. More general cognitive ability measures, however,
are also likely to be related to land navigation performance
(Busciglio et al., 1991; Pleban et al., 1988; 1989).
Methodologically this is problematic because spatial ability
measures and scores on general cognitive ability, or intelligence
tests tend to be highly correlated. Busciglio et al. (1991), for
example, found a correlation of .65 between scores on the
Wonderlic and scores on the Map test, the best of the three
spatial predictors. This was higher than the correlation the Map
test displayed with the other two spatial tests (Map/Orientation
xr=.50; Map/Maze r=.42). Scholl and Egeth (1982) also found high
correlations (ranging from .47 to .66) between standard
intelligence measures (verbal and math tests) and spatial ability
(orientation and visualization) measures.

In the present research, multivariate analyses will be used
to determine if any of the three spatial tests explain variance
in the criterion when a measure of general intelligence
(Wonderlic) is also included. Military orienteering scores from
SFAS are also examined in relation to the criterion. In an
unrestricted sample one would expect a strong relationship
between military orienteering performance and success on a land
navigation exam. In this case, however, the relationship should
be attenuated by the fact that military orienteering events are
used as selection criteria in SFAS.

The present analyses include not only an examination of
correlations and differences across groups, but also exploratory
analyses designed to estimate the impact of establishing a
screening cut-off score on these tests. From an applied
perspective, results based on a real world sample of SFOQC
students provide the best assessment of the practical utility of
the spatial tests for screening or diagnostic purposes. From a
theoretical perspective, however, the sample is less than optimal
because it represents a unique, pre-selected population. First,
only soldiers who score above the Army average on the General
Technical (GT) composite of the ASVAB are even eligible for SFAS.
Second, SFAS candidates who fail three or more of the six
military orienteering events in SFAS are unlikely to be selected
for the SFQC.

In light of the strong relationship between general aptitude
and spatial abilities, and the weaker, but significant
relationship between spatial tests and military orienteering
performance, spatial ability scores are also likely to be higher
than one would find in the Army or the population at large. The
restricted range of scores on all three predictors (spatial
tests, general aptitude, and military orienteering events) means
that correlations between these measures and the criterion are
likely to underestimate the relationships one would find in a
less restricted sample. In other words, we are only likely to

6



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4. TITLE AND SUBTITLE

Predicting Land Navigation Performance in the Special 63007A

Forces Qualification Course 792
1223H

6. AUTHOR(S) 879300

Busciglio, Henry H.; and. Teplitzky, Martha L.

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U.S. Army Research Institute for the Behavioral and
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13. ABSTRACT (Maximum 200 words)
This research examined performance on the land navigation field test adminis—

tered in the Special Forces Qualification Course (SFQC) as a function of three sets
of possible predictors: (a) Project A paper and pencil tests of spatial ability
(Map, Maze, and Orientation), (b) performance on the military orienteering events

in the Special Forces Assessment and Selection program (SFAS), and (c) measures of
intelligence and physical fitness obtained in SFAS. Our multivariate analyses
showed that SFQC trainees who passed the land navigation test on the first try had
significantly higher scores on the Map test than those who did not. We also found
that those who failed land navigation had significantly lower ratings on orienteering
Event IV (the last and longest event in SFAS) than did those who passed land naviga-
tion either on their first try or on a retest.

Analyses of hypothetical cut-scores on the Map test were examined to provide
information on the potential utility of this measure as a screening tool. The
benefits (i.e., higher success rates when the cut-offs were used) were marginal
because even very lenient cut-offs would exclude many students with the potential

(Continued)
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Special Forces training Land navigation
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Table A-1.

Summary of Factor Analytic Results from Project A and
Career Force Samples (from Campbell & Zook, 1991, 1992)

Loadings on Loadings on

ASVAB factor Spatial factor
Test FT cv LV FT cv LV
Map -60 .33 .33 -52  .56 .56
Orientation -40 .21 .18 -46 .56 .59
Maze nr .07  .10 -70 .65 .65

Note. FT is Field Test sample (N=169; these analyses included the Project A perceptual-psychomotor tests;
CV is Concurrent Validation sample (N=7,884); LV is from the Longitudinal Validation (N=6875); nr - less
than .30, and thus not reported.

Table A-2.

Number of Equations for Which Individual Predictors are
Statistically Significant, by Type of Criteria, Across
MOS (from Busciglio, 1990)

Type of Criteria
(Maximum Possible*)

Comprehensive” Specific TOTAL

(86) (46) (132)
best 2 ASVAB subtests:
Mathematics Knowledge 68 28 96
Auto and Shop Information 74 20 94
worst 2 ASVAB subtests:
Number Operations 24 2 26
Electronics Information 18 4 22
Spatial:
Map 33 8 41
Orientation 13 4 17
Maze 5 1 6
best 2 Perceptual-~
Psyc: rt sts:
Target Ident. - % correct 32 13 45
Target Ident. - time 23 18 41

*Across all measures pertinent to all MOS. ‘Comprehensive measures refer to overall success on the job; specific are more
nearly defined areas, such as navigation, target identification, operating howitzer sights, tank gunnery, determining grid
coordinates, etc.

A-2



The overall ANOVAs show that scores on the Map, Maze, and
Wonderlic tests and ratings on orienteering events II Day and IV
were significantly different across groups. However, the more
conservative Tukey HSD posthoc tests (SAS version 5.0) found
significant differences across cell means for Map test scores and
IV ratings only.

The underlining of cell means in Table 4 shows that those
passing land navigation on the first try had significantly higher
scores on the Map test than did the other two groups, whose Map
scores did not differ significantly. Also, event IV ratings were
significantly lower for the small group of students who were
never able to pass a re-test.

Unique Variance Explained by Predictors

Overall, the results in Table 3 show that spatial tests,
intelligence test scores, and military orienteering times for one
event and ratings for two events are related to passing land
navigation on the first try. Similarly, Table 4 shows that when
the three outcome groups are used, Map test scores and ratings on
orienteering event IV are related to performance differences.

To determine which potential predictors make a unique
contribution to the prediction of land navigation performance we
performed backward stepwise discriminant analyses. In this
procedure, all predictors are entered into the prediction
equation as a block. Nonsignificant predictors are then removed
one at a time, based on their individual contribution to the
overall prediction. This process continues until all predictors
remaining in the equation are individually significant at a
certain alpha level (.05), and thus account for an independent
portion of the variance in the criterion. The high
intercorrelations among the paper and pencil measures (spatial
and intelligence tests) suggest that these measures, in
particular, are likely to be redundant as predictors of land
navigation performance.

The results of the discriminant analysis showed that the Map
test was the only predictor to account for a significant
proportion of unique variance in the pass vs. fail first time
criterion (r?=6.5%). Thus, the Map test is the best single
predictor of first time land navigation success, and when Map
scores are included in a prediction equation none of the other
variables add any significant explanatory power.

When the same procedure was performed using the three
criterion groups (pass first time/pass re-test/fail re-test) the
Map test (partial r’=5.5%) and ratings on event IV (partial
x°=4.0%) emerged as significant independent predictors of land
navigation outcomes. This is consistent with the ANOVA results
presented in Table 4. That is, individuals who excel (i.e., pass

15



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

EDGAR M. JOHNSON
Director
a
Technical review by
Paul A. Gade
Fred Mael

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NTIS CRA&l
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DISTRIBUTION: Primary distribution of this report has been made by ARI. Please address
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NOTE: The findings in this report are not to be construed as an official Department of the Army
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REFERENCES
Busciglio, H. H. (1990). The incremental validity of spatial and

perceptual-psychometer tests relative to the Armed Services
Vocational Aptitude Battery (ARI Technical Report 883).
Alexandria, VA: U.S. Army Research Institute for the
Behavioral and Social Sciences. (AD A220 903)

Busciglio, H. H., Teplitzky, M. L., & Welborn, C. (1991). Project
As ial tes and milita ienteering perf ance in

the Special Forces assessment and selection program (ARI

Technical Report 921). Alexandria, VA: U.S. Army Research
Institute for the Behavioral and Social Sciences.
(AD A233 432)

Campbell, J. P., & Zook, L. M. (Eds.). (1991). Improving the
selection, classification, and utilization of Army enlisted
personnel: Final report on Project A (ARI Research Report

1597). Alexandria, VA: U.S. Army Research Institute for
the Behavioral and Social Sciences. (AD A242 921)

Campbell, J. P., & Zook, L. M. (Eds.). (1992). Building and

retaining the career force: New procedures for accessing
and _ assigning Army enlisted personnel: Annual report, 1990
fiscal year (ARI Technical Report 952). Alexandria, VA:
U.S. Army Research Institute for the Behavioral and Social

Sciences. (AD A252 675)

Eckstrom, R. B., French, J. W., Harman, H. H., & Derman, D.

(1976). Manual for kit of factor-referenced cognitive
tests. Princeton, NJ: Educational Testing Service.

Fricke, J. R. (1990). The Special Forces Q-Course. Special
Warfare, 3, Winter.

Guest, J. A. (1988). Special Forces training: New initiatives to
enhance the force. Special Warfare, 1, April.

Hunt, E. (1991). Computerized assessment of individual
differences (Final Report, Contract # N00014-86-C-0065).

Alexandria, VA: Office of Naval Research.

Johnston, S. M. (1991). Land navigation. Infantry, Nov-Dec 1991,
14-16.

Koslowski, L. T., & Bryant, K. J. (1977). Sense of direction,
spatial orientation and cognitive maps. Journal of Experi-

mental Psychology: Human Perception and Performance, 3,
590-598.

23



many people who might otherwise have been successful. If, on the
other hand, the goal is to produce as many graduates as possible,
even if this means a relatively large number of re-tests, then a
more lenient cut-score is necessary.

Discussion

Most importantly, these analyses have shown that students’
scores on the Project A Map test are related to their performance
on the Special Forces Qualification Course land navigation
exercise. This finding is impressive because the Map test is a
short, paper and pencil measure and land navigation is a multi-
faceted performance criterion administered three months to two
years later.

There are several possible explanations for this
relationship. One is that the Map test predicts performance
simply because it measures map-related knowledge and skills that
facilitate performance on the land navigation field exercises.
Although proposed as a measure of a relatively stable, innate
spatial ability, the Map test, because of its similarity to
actual maps, may be easier for people who have acquired map
reading skills from prior training or experience. Previous
research has indeed found that individuals with relevant prior
training and experience are also likely to perform better on land
navigation tasks (Peters, Bleda, & Fineberg, 1979; Pleban et al.,
1989).

This interpretation, however, is not consistent with the
fact that the "less realistic" spatial tests, Orientation and
Maze, also had significant, albeit smaller, correlations with
both military orienteering (Busciglio et al., 1991) and land
navigation performance (see Tables 3 and 4). Scores on these
more abstract tests are less likely to be affected by prior
training or "real-world" experience in map-reading, orienteering
or land navigation.* Moreover, the fact that pre-training
measures predict post-training performance further supports the
argument that the spatial tests measure basic abilities that are
difficult to alter through training or experience.

Interpreting the effects of the Map test as evidence that
spatial abilities are related to land navigation performance is
consistent with much previous research (Hunt, 1991; Scholl, 1988;
Stasz & Thorndyke, 1980; Thorndyke & Stasz, 1980; Weitzman,
1979). This conclusion also raises an important practical
question - to what extent can training compensate for
deficiencies in basic spatial abilities?

5it should also be recalled that the Map test is significantly correlated with the Orientation and Maze tests (=.52 and .48,
respectively), as Table 2 shows.

18



utility of the spatial tests as screening criteria and diagnostic
instruments.

nd Navigation Research

In 1986, ARI researchers (Pleban et al., 1988) conducted a
preliminary examination of factors related to success in the four
week field training portion (Phase I) of the SFQC. Graded events
in this phase included map reading written exam, land navigation
field exercise, confidence course, patrolling written exam,
patrolling field exercise, and performance as a patrol member.
The sample for the research consisted of the 338 soldiers
attending the Q Course at Fort Bragg, North Carolina, between
September 1986 and January 1987. Out of this group, 67% passed
Phase I. Of those who did not pass Phase I, 84% were dropped
because they failed the land navigation portion of the course.

Analyses in the Pleban et al. (1988) study focused on
identifying differences between successful and unsuccessful Phase
I trainees in four areas: aptitude scores from the Armed
Services Vocational Aptitude Battery (ASVAB), intelligence
(measured by the Wonderlic Personnel Test), physical fitness, and
personality (Myers-Briggs Type Indicator). Because land
navigation failures accounted for nearly all the academic
attrition in the sample, the analyses can be interpreted as
providing information on the factors related to successful
performance in land navigation.

Results showed that general aptitude was the most promising
predictor of Phase I success for active duty soldiers. Among the
active component soldiers, successful trainees had significantly
higher scores (one half to one full standard deviation) than
unsuccessful trainees on five ASVAB composites (general
maintenance, combat, field artillery, operators and food, and
skilled technical). For reservists, on the other hand, ASVAB
scores were almost identical for successful and unsuccessful
trainees.

The most general measure of intelligence, the Wonderlic
test, was not related to success for either active or reserve
component soldiers (total sample r = .13, ns). Army Physical
Fitness Test (APFT) scores and the personality measures also did
not differentiate successful and unsuccessful Phase I trainees.

In a second study, Pleban, Allentoff, and Thompson (1989)
examined predictor relationships with scores on the six Phase I
graded events, as well as the final pass/fail outcome. Although
ASVAB scores were not available for these analyses, other
predictors were similar, including Wonderlic scores, background
characteristics, and personality measures (Jackson Personality
Inventory). The sample consisted of the 293 students from the
November 1987 SFQC class, 62% of whom successfully completed
Phase I. Of those who did not pass, 61% failed either the map

2



sense of direction" subjects on location and direction pointing
tasks. Scholl (1988), among others, built on this work, and
found that "good sense of direction" subjects outperformed "poor
sense of direction" subjects primarily on location pointing tasks
that required individuals to mentally shift their perspective or
rotate their frame of reference. In other words, people with a
good sense of direction were better able to imagine they were in
a different position relative to their actual location. Scholl
interpreted this as evidence that spatial-visual abilities
underlie performance differences on orientation, or direction
finding tasks.

Simutis and Barsam (1983) found a relationship between
spatial ability and another skill required for successful
navigation - the ability to identify terrain features from a
contour relief map. The sample consisted of 60 soldiers,
trichotomized into high, medium, and low spatial ability groups
based on composite scores on three spatial subtests from the Kit
of Factor-Referenced Cognitive Tests (Eckstrom, French, Harman, &
Derman, 1976). Researchers trained and then tested the soldiers
on a difficult computerized terrain visualization and
identification exercise. The high ability group performed
substantially better than the other two groups on the post-
training test.

Thorndyke and his colleagues (Thorndyke & Stasz, 1980; Stasz
& Thorndyke, 1980) investigated spatial abilities and the
different strategies people use to learn locations and recall
maps. First they showed that individuals high in spatial-
visualization ability, as measured by a test of visual memory and
the Group Embedded Figures Test (Oltman, Raskin, & Witkin, 1971),
are better able to recall the spatial attributes of map elements.
Next, they asked subjects to describe how they approached the map
recall task. Results showed that high spatial-visual ability
subjects tended to use map learning strategies that involved
encoding spatial configurations (e.g., forming mental images,
recognizing and using spatial patterns and relationships), as
opposed to verbal/associative strategies. The use of these
spatially oriented strategies was clearly related to superior
performance on map learning tasks.

Weitzman (1979) got similar results when he examined
differences in the strategies good and poor orientation subjects
used to process spatial information. Individuals skilled in
orientation tasks (i.e., better able to accurately point to the
location of familiar landmarks out of their field of vision) were
more likely to use spatial-visual strategies to represent and
recall geographic information than their less skilled
counterparts.

Taken together, the land navigation and spatial ability
studies lend strong support to the hypothesis that spatial test

5