Measuring Human Capabilities: An Agenda for Basic Research on the Assessment of Individual and Group Performance Potential for Military Accession (2015)

4

Spatial Abilities

Committee Conclusion: A spatial ability measure, Assembling Objects (AO), is included in the Armed Services Vocational Aptitude Battery (ASVAB). Research suggests incremental validity for spatial measures over general mental ability measures in predicting important military outcomes. Research also suggests that sex differences vary across different operationalizations of spatial ability. Together, these findings suggest exploring varying approaches to the measurement of spatial abilities to ascertain whether the AO test is the best measure of spatial ability for military selection and classification. The committee concludes that spatial ability merits inclusion in a program of basic research with the long-term goal of improving the Army’s enlisted accession system.

The current ASVAB is largely a measure of acquired knowledge and ability (see Roberts et al., 2000). The potential for developing measures of fluid intelligence as a supplement to the current ASVAB is treated in detail in Chapter 2. Another domain in which skill is generally not acquired by formal instruction is that of spatial ability: the capacity to unravel, understand, and remember the spatial relations among objects. The AO subtest of the ASVAB is an indicator of this skill, but is not currently used in Army selection or placement decisions. Spatial ability is not a monolithic and static trait, but made up of numerous subskills, which are interrelated among each other and develop throughout a lifetime. While the committee treats this topic separately in this chapter, it is important to examine how individual differences in spatial abilities intersect with, and are distinct from, the cognitive-control and inhibitory capabilities covered in Chapter 2,

the cognitive biases covered in Chapter 3, and the “hot cognition” processes covered in Chapter 6.

An argument can be put forward that this kind of visual-spatial ability is becoming increasingly important with the development and proliferation of new technologies, such as imaging, computer graphics, data visualization, and supercomputing. Highly demanding spatial tasks include the construction of mental representations of object configuration from images on several screens representing different perspectives, as in some fields of interest to the military. In these fields of work, powerful computer graphic technologies are being used to create complex visual images of processes that occur in the natural world. Despite their importance in many fields and in science education, spatial skills rarely work in isolation from other abilities, such as logical reasoning, efficient memory retrieval, and verbal skills, and deficits in one area can often be compensated for by excellence in others. An important type of exceptional talent in math and science, however, is the ability to easily switch from one efficient mode of representation to another (e.g., from a conceptual to a spatial mode and vice versa).

It is clear that spatial abilities can be measured in a large-scale group setting (as is done with the current ASVAB) and contribute to military performances (e.g., relationship with hands-on performance tasks; see Carey, 1994). The individual-differences literature is replete with recent articles describing the importance of rapid stimulus selection and thinking with symbols (examples are Hegarty and Waller, 2005; Lathan and Tracey, 2002; Malinowski and Gillespie, 2001). Spatial abilities have been found to be predictive of real-life events (Carey, 1994), including map reading and arterial positioning (see McHenry et al., 1990, for findings from Project A data).

DEFINING SPATIAL ABILITIES

A recent upsurge of empirical evidence suggests spatial abilities are an important predictor of performance (see Lubinski, 2010), especially in scientific and technical fields (National Research Council, 2006; Shea et al., 2001; Stieff et al., 2014; Wai et al., 2009). Spatial abilities are important for understanding an individual’s spatial relationship to and within surroundings (e.g., orienteering) and also for understanding representations of multidimensional figures in one-dimensional displays (e.g., data visualization). Within visual perception abilities, spatial abilities can be defined as “how individuals deal with materials presented in space—whether in one, two, or three dimensions, or with how individuals orient themselves in space” (Carroll, 1993, p. 304). Furthermore, spatial abilities signify “an ability in manipulating visual patterns, as indicated by level of difficulty and com-

plexity in visual stimulus material that can be handled successfully, without regard to the speed of task solution” (Carroll, 1993, p. 362).

Spatial abilities are multifaceted, and tests to measure individual differences in spatial abilities must separate these facets to distinguish them within the domain of spatial abilities as well as from other measures of general intelligence. Spatial ability tests measure practical and mechanical abilities important for success in technical occupations, but they are not supposed to be measures of abstract reasoning abilities (Horn, 1989; Smith, 1964). Similarly, test design is challenged by the important role afforded to spatial imagery in accounts of creative thinking (Shepard, 1978) and for the observed high and positive correlations between spatial ability tests and other measures of intelligence (for reviews, see Lohman, 1996; Lohman et al., 1987). Furthermore, spatial abilities measure psychological factors such as attention, important for everyday demands on working memory to maintain and transform images (Kyllonen and Christal, 1990).

The utility of spatial abilities as performance predictors has a long history of research, test development, and longitudinal outcome assessment (with some results being contradictory and debated). Many researchers have expressed the view that spatial abilities are as important as verbal comprehension in the prediction of real life events (for overview, see Humphreys and Lubinski, 1996). It is difficult to distinguish spatial abilities from fluid intelligence or broad reasoning (Horn, 1989) mainly because most of the test material for fluid intelligence is visual in nature. Examples include Project Talent’s Abstract Reasoning (Project Talent Office, 1961) and Raven’s Progressive Matrices (Raven, 1992). Research also shows that prevalent standardized tests of cognitive abilities fail to identify talent for outstanding achievement in domains not conducive to recognition or expression through verbal mechanisms prevalent in modern academic and testing realms (Lohman, 1994; 2005), a finding demonstrated even among those in the highest tiers of general cognitive ability (Kell et al., 2013; Robertson et al., 2010).

TESTING SPATIAL ABILITIES FOR MILITARY ENTRANCE

The military’s interest in spatial abilities testing dates back to World War I, and by WWII a spatial-visualization test was included in the Army General Classification Test (for a historical overview, see Humphreys and Lubinski, 1996). The range of military occupational specialties to which the military services select and assign recruits, including many that demand abilities beyond verbal and mathematical reasoning, suggests that inclusion of measures of spatial ability in the military’s entrance test battery would facilitate the identification of potentially highly successful recruits who might otherwise be overlooked or placed in suboptimal occupations.

The value of spatial abilities tests is well known to the U.S. Army Research Institute for the Behavioral and Social Sciences (ARI). The current ASVAB includes AO, a test for a specific facet of spatial abilities (Powers, 2013). The Army’s Selection and Classification Project (Project A), conducted by ARI, identified AO as a potential performance predictor in Army occupations (Buscigilo et al., 1994; Campbell and Knapp, 2001). Currently, AO is assessed through 25 questions (tested in 15 minutes) on the paper-and-pencil ASVAB version and through 16 questions (tested in 16 minutes) in the computer adaptive version.¹ AO tests the individual’s “ability to determine correct spatial forms from separate parts and connection points” (Held and Carretta, 2013, p. 2). Figure 4-1 displays two sample questions from the AO test.

AO was included along with several other spatial abilities tests as part of the Enhanced Computer-Administered Test (ECAT) battery described by Alderton and colleagues (1997). Wolfe (1997) reported incremental validity of .013 for a composite ECAT spatial score over the current ASVAB for predicting training school grades, and incremental validity of .03 for performance on hands-on performance tests. Additionally, Carey (1994) reported that AO added incremental validity to the ASVAB in predicting mechanics’ job performance in a hands-on performance test of both automotive (.012) and helicopter mechanics (0.15). Thus the incremental validity of AO is modest and varies by criteria. But modest increments can be of considerable applied utility in settings where large numbers of screening decisions are made.

At this time, AO scores are not used for selection purposes by any military service (the scores are not part of the Armed Forces Qualification Test, AFQT), and only the Navy currently uses the AO results for occupational classification (Held and Carretta, 2013).

Consistent with Lohman’s (1979) identification of three basic spatial abilities factors, analysis of spatial abilities in ARI’s Project A considered spatial relations, spatial orientation, and visualization. The currently used AO test was developed through job analysis of abilities important to Army occupations during Project A’s study time frame, 1983 to 1988, and refined through subsequent field testing and validation studies. As discussed below, some tests of spatial abilities demonstrate subgroup differences between sexes; however, such differences were not found in AO (Peterson et al., 1990). For this reason in particular, the Navy adopted AO for classification purposes, as it sought to reduce or eliminate adverse impact for minority groups seeking technical occupations. Sex and minority-group differences in performance on AO have been shown to be lower than for some other

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¹ See http://www.official-asvab.com/whattoexpect_rec.htm [June 2014] for the most up-to-date information on the content of the ASVAB.

FIGURE 4-1 Sample questions from the Armed Services Vocational Aptitude Battery AO test.
SOURCE: Official site of the ASVAB. Assembling Objects. Available: http://officialasvab.com/questions/app/question_ao1_app.htm [January 2015].

technical tests, such as Auto and Shop Information, which has the largest effect size among the ASVAB subtests (Held and Carretta, 2013). Furthermore, a recent ARI assessment of AO (Anderson et al., 2011) concluded that adding AO to the AFQT composite score would increase the AFQT’s prediction of performance and job knowledge in jobs that require spatial aptitude, with little or no subgroup differences.

STATE OF THE SCIENCE

As a leader in research on spatial abilities, the Army has access to a well-developed body of data on the internal and external validity of spatial ability constructs and tests. However, in considering the historical timeline of much of this research, the increased roles of technology in many modern military occupations, and developments in testing methods, the committee finds the science behind the predictive power of spatial abilities worthy of further exploration and consideration. Much has been learned about spatial abilities since the research findings conducted through Project A that developed the AO test, and modern technological developments have implications for many of the duties and tasks essential to soldier performance, as well as implications for the Army’s ability to test for those abilities. While much of the research conducted on spatial abilities has been and will continue to be conducted within applied research programs, there remains a great deal of foundational knowledge that is still needed about the multiple facets of spatial abilities. The following section briefly reviews the current state of the science in understanding and testing for spatial abilities.

Internal Validity: Measuring Spatial Abilities

The multifaceted nature of spatial abilities poses a challenge to identify and develop measures of the separate facets, as well as to understand their interrelationships. Since the early 1900s, researchers have sought evidence of a general spatial factor and its testable component parts. In addition to Lohman’s three basic factors (spatial relations, spatial orientation, and visualization), other major spatial factors identified and assessed over a century of research include, for example (see Carroll, 1993, for an overview):

• Visual memory—short-term memory of visually presented stimuli;
• Spatial scanning—tasks, such as following a maze or selecting a path;
• Perceptual speed—rate at which presented visual stimuli are matched;
• Serial integration—identification of pictures presented successively;

• Closure speed—time to match an incomplete visual presentation to a known object or feature: and
• Kinesthetic—coordinated body motion such as left-right judgments.

In a recent meta-analysis of studies on the trainability of spatial skills, Uttal and colleagues (2013) noted a lack of consensus on a typology of spatial abilities and proposed replacing the “spatial relations, spatial orientation, and visualization” typology with a classification system with two fundamental distinctions: intrinsic versus extrinsic information and static versus dynamic tasks. The authors found their typology more useful in categorizing studies for their meta-analysis of trainability studies than the typology based on factor-analytic studies.

Most research on spatial abilities has focused on what may be termed “small-scale” tasks (e.g., mental rotation of objects), with a focus on “large-scale” tasks (e.g., navigation, way-finding) emerging more recently (Hegarty et al., 2006). Recent work, culminating in a meta-analysis by Wang and colleagues (2014), argues that these are best viewed as two separate families of abilities. However, the mean correlation of .27 found in this meta-analysis between the two families indicates that they are not completely independent. Additional evidence of their separability comes from the finding that different areas of the brain have been identified as involved in these two families of abilities, with small-scale tasks linked to activation of the parietal lobes and large-scale tasks linked to the hippocampus and medial lobes (Kosslyn and Thompson, 2003; Morris and Parslow, 2004).

This distinction between small-scale and large-scale spatial abilities links to recent U. S. Air Force research on the construct of situation awareness. As defined by Dr. Mica Endsley, U.S. Air Force Chief Scientist, in her briefing to the committee, “Situation awareness is the perception of elements in the environment within a volume of time and space, the comprehension of their meaning, and the projections of their status in the near future.”² The inclusion of a future time element in this definition of situation awareness indicates the importance of abilities in contingency planning, a partially trainable skill with underlying individual differences in natural ability. The committee can envision facets of spatial abilities similarly linked with situation awareness also being important to many Army occupations and job duties, especially those involving combat maneuvers of remotely controlled technology.

To test individuals’ situation awareness abilities, Dr. Endsley described a direct measure, the Situation Awareness Global Assessment Technique,

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² Presentation to the committee on December 5, 2013. Presentation cited work contained in Endsley (1988). Full presentation materials available by request through this study’s public access file.

which has been validated for content (Endsley, 1993), construct (Endsley, 2000), and criterion (Endsley, 1990). This assessment technique requires subjects to monitor a simulation that is randomly frozen with all displays blanked out. The subject must then answer a series of rapid questions about the state of the simulation to assess the subject’s situation awareness at a specific point in time, including the subject’s assessment of the expected situation in the near future. In assessing situation awareness, an important distinction must be made between decision making and situation awareness. An individual’s ability to identify and comprehend the significance of available information about his or her environment is an important factor of spatial abilities that impacts the individual’s ability to make effective and accurate decisions. Although not always the case, poor decisions, sometimes with fatal consequences, have resulted from poor situation awareness whereby the decision maker fails to recognize important details about the environment (also see Chapter 3 for a discussion of the role cognitive biases play in the interpretation of available information). For a more detailed discussion of the critical importance of situational understanding for decision making in an Army context, see the National Research Council report, Making the Soldier Decisive on Future Battlefields (National Research Council, 2013).

External Validity: Using Spatial Abilities in Predictions of Key Outcomes

Much of the work on spatial abilities by Project A focused on the demands of Army occupations. Campbell and Knapp (2001) documented the incremental validity of AO during Project A for predicting a number of criteria important to the Army; Alderton and colleagues (1997) and Wolfe (1997) described the absolute and incremental validities of several spatial abilities measures across all military services. More recently, Anderson and colleagues (2011) concluded that adding AO to the composite of the ASVAB that is used for selection into the Army would increase the validity of that composite for many criteria.

Other evidence of the validity of constructs for facets of spatial ability in predicting key outcomes was obtained through a longitudinal study of the occupational status of 400,000 high school students from Project Talent (see Humphreys et al., 1993). Using self-report interest questionnaires and ability tests, Austin and Hanisch (1990) predicted occupational groups for a mixed-gender sample of 10th graders included in Project Talent. Prediction accuracy varied across groups “as a function of the a priori selection of the specific occupational groups that formed the criterion categories” (Humphreys et al., 1993, p. 251). Austin and Hanish (1990) extracted and interpreted five discriminant functions; the first function was dominated by verbal and mathematical tests, while the second function was dominated

by mechanical, spatial, and mathematical tests. These first two functions accounted for the major proportion of the variance, while the other three functions, which included dimensions of various vocational interests, accounted for small but significant proportions of the variance.

Humphreys and colleagues (1993) were among the influential researchers on spatial abilities. The spatial composite they used was made up of four tests: (1) the Project Talent 2D spatial abilities test (object rotation and flipping in two dimensions; 24 items); (2) the Project Talent 3D spatial abilities test described above (three-dimensional test of mental folding; 16 items); (3) the Project Talent Mechanical Reasoning test (20 items), which measured deductions based on primitive mechanisms (e.g., gears, pulleys, and springs) and knowledge of the effects of common physical forces (e.g., gravity); and (4) Abstract Reasoning (15 items), which was a nonverbal test of logical relationships in complex figural patterns. The first two tests are relatively pure measures of spatial abilities, whereas the last two are likely to be visual measurements of a broad reasoning (fluid intelligence) skill.

Humphreys and colleagues (1993) reported on what they termed High-Space students (the highest 20 percent of scorers on a spatial-mathematics composite, resulting in an N of 17,647). This group was distinguished from the group they termed High-Intelligence students (the highest 20 percent across both a verbal-mathematics composite and the spatial-mathematics composite, resulting in an N of 54,311). Both males and females in the High-Space group avoided educational and occupational opportunities, relatively speaking, in the social sciences and humanities over the course of 11 years following high school graduation. Both genders in the High-Space group, but especially the males, were working in larger proportion in traditional blue-collar occupations. See Table 4-1 for data that demonstrates a commonality between engineers, artists, and artisans.

The High-Space group also had substantially fewer completed degrees at every educational level beyond high school graduation, compared with the High-Intelligence and High-Verbal groups (see Table 4-2). The authors reported that the predictive validities of the spatial-mathematics and verbal-mathematics ability composites were established by successfully differentiating a variety of educational and occupational groups. By relying solely on scores from conventional mathematical and verbal ability tests, such as those of the Scholastic Aptitude Test and the Graduate Record Examination, physical science and engineering disciplines may be failing to identify and select highly talented individuals.

With respect to the value of a spatial-mathematics composite measure, the authors concluded

TABLE 4-1 Proportions in Four High School Classes of Occupational Categories of Three Select Groups and Students in General

NOTE: These proportions are based on population estimates.
SOURCE: Humphreys et al. (1993, p. 256).

TABLE 4-2 Proportions in Four High School Classes of Amount of Education Completed by the Three Select Groups and Students in General

NOTE: These proportions are based on population estimates. PhD = doctoral degree; it includes degrees in law and medicine. The + next to MA (master’s degree in arts), BA (baccalaureate degree in arts), and HS (high school diploma) = the inclusion of individuals having course work beyond that level but not enough to achieve the next highest credential.
SOURCE: Humphreys et al. (1993, p. 257).

Additional research shows that spatially talented youth are an important pool of human capital in science, technology, engineering, and mathematics fields, and “the influence of this intellectual pattern extends beyond learning and work settings and into domains of creative production” (Kell et al., 2013, p. 1,835). Furthermore, the correlation between spatial ability and career choice, and performance and persistence in that career, is demonstrated even in the top one percent of adolescents in cognitive ability (Robertson et al., 2010). This suggests that even those recruits scoring in the highest tiers of the AFQT would benefit from job assignments made in consideration of their talents in spatial abilities.

Sex Differences

The adoption of tests of spatial abilities for the purposes of assessment and placement has been hampered by contradictory and sometimes confusing results regarding sex differences. Males score higher, on average, than females in many spatial abilities tests, but this is not true across all facets of spatial ability. In fact, the current AO test in the ASVAB reduces adverse impact and score barriers for both women and ethnic/racial minority groups (Held and Carretta, 2013). Other research indicates that men and women do not, as subgroups, show the same score distributions on many tests of facets of spatial ability (Jones and Anuza, 1982), and long-standing questions remain in dispute about the magnitude of the differences, as well

as the facets of spatial ability in which sex differences in score distribution are apparent and the age at which those differences appear (Linn and Petersen, 1985).

Humphreys and Yao (2002) used Project Talent data from 57 cognitive tests to analyze college-major selection preferences. Based on what they termed their Descriptive Discriminant Analysis, they concluded, “Large sex differences in the incidence of various choices do not affect appreciably patterns of scores on cognitive and self-report tests” (Humphreys and Yao, 2002, p. 8). While it appears that men score higher then women on this kind of test, Humphreys and Yao found that, for both sexes, science majors are identifiable from those in the humanities and social sciences through a combination of mechanical, spatial, and mathematical tests.

Voyer and colleagues (1995) conducted a meta-analysis of 286 effect sizes from studies employing a variety of spatial ability measures. They found significant sex differences in several tests, and they found that differences from test to test still exist. Military research also shows variability in sex differences across spatial ability measures. Russell and Peterson (2001) reported a male-female d = 0.06 for AO, but d values greater than .30 for three other spatial tests.³ Voyer and colleagues (1995) also found some support for the belief that sex differences on spatial ability measures have decreased recently. Finally, it was found that the age of emergence of sex differences varied by the type of test administered. The data from this meta-analysis leads the committee to believe further research is necessary to better understand sex differences in spatial ability.

Interestingly, the relationship between spatial ability and verbal ability has been found in some studies to differ between men and women. For example, in a test of fluid intelligence using letters (Primary Mental Abilities Battery), females outperformed males. However, in a similar test using figures rather than letters (Advanced Progressive Matrices Test), males outperformed females (Colom and García-López, 2002).

The debate surrounding possible differences in experience and processing of spatial information between men and women has been heightened by research on the impact of video games on spatial abilities test scores. Feng and colleagues (2007, p. 850) noted that “boys have always played different games than girls, and early recreational activities have often been cited as a major cause of gender differences in adult spatial cognition.” While it is important to note that spatial abilities do appear to be amenable to training (Feng et al., 2007; we note that this study makes use of a very small sample size and should be viewed as merely suggestive), a key question is whether training on one task generalizes to other tasks. Sims and Mayer (2002)

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³ “d is the standardized mean difference between group means” (Russell and Peterson, 2001, p. 275).

found that experience with the computer game Tetris aided performance on a Tetris-like task, but not on other spatial tasks, leading them to conclude that spatial training effects were task-specific. Terlecki and colleagues (2008) also found evidence of transfer from Tetris training to performance on mental rotation tasks. The committee’s interpretation of this body of research is that spatial ability training is usually domain specific and does not generalize to other dissimilar domains (e.g., training spatial ability in chemistry students for detecting the chirality of molecules does not increase ability to identify and recall the spatial locations of truck engine parts).

Regarding training effects on gender differences, the classic meta-analysis by Baenninger and Newcombe (1989) reported that training produces comparable changes in performance for males and females, and hence produces no reduction in the mean difference. A number of more recent studies have reported differing findings, with gender differences reduced or even eliminated. For example, Stieff and colleagues (2014) focused on strategy training in problem solving and reported that specific training on mental imagery with additional training in analytic strategies eliminated sex differences in achievement. However, a meta-analysis by Uttal and colleagues (2013, p. 367) of the trainability of spatial abilities concluded that, “Both men and women responded substantially to training; however, the gender gap in spatial skills did not shrink due to training.” The committee gives these meta-analytic findings much greater weight than the findings of small-scale individual studies. Given the varieties of spatial abilities and the range of possible training interventions, we view the issues as not yet fully resolved.

The focus of this section on sex differences in spatial abilities reflects the considerable attention such differences have received in the recent research literature. In particular, the committee’s interest in sex differences is based on findings that male-female differences on some spatial ability measures are substantially greater, in proportional terms, than are sex differences on the currently used AFQT composite. For instance, Sackett and colleagues (2009) report a male-female AFQT d of 0.08 for a nationally representative sample of 18-22 year old youth, which is similar to the 0.06 reported in the Russell and Peterson Project A data for AO, but quite different from the d’s greater than 0.30 that Russell and Peterson (2001) reported for three other spatial tests (maze, orientation, and map). However, the committee notes that racial/ethnic mean differences are also generally found on spatial ability measures. For example, Russell and Peterson (2001) reported white-black d’s ranging from 0.69 to 1.08 for six spatial ability measures in Army Project A data. These are substantially larger differences than those Russell and Peterson reported for male-female differences (see above). The focus above on sex differences does not imply that racial/ethnic

group differences are not present or are not important for the Army’s accession and selection purposes.

New Technologies

The rate of advance in modern technologies has implications for two major aspects of the Army’s selection and assignment process: (1) the duties and tasks of many technical fields for which recruits will be assigned, and (2) the available methods of testing recruits for spatial abilities. The Army’s primary work on spatial abilities was conducted through Project A, which assessed the spatial abilities relevant to Army occupations at that time. Modifications of jobs and occupations, especially during the past 30 years, warrant a new look at the fundamental importance of spatial abilities to Army occupations, including those aspects of spatial ability that require proficiency in human-computer systems, virtual interfaces, graphical data representations, and other digital-age technologies. The intrinsic capabilities of many of these everyday work duty technologies also provide opportunities for new methods of assessing spatial ability (see Section 5, Methods and Methodology, for further discussion). With the decrease of pencil-and-paper ASVAB testing in favor of the computer adaptive CAT-ASVAB, it is now feasible to consider test formats that were previously not easily implemented, when only the paper-and-pencil format was available. More important, inevitable advances in hardware and software capabilities will make it possible to consider tests dependent upon such three-dimensional features as precise measurement of speed, introduction of eye-tracking visual search, and real-time three-dimensional spatial manipulation of virtual objects.

A PATH FORWARD

Research indicates that spatial abilities are distinct from general intelligence. Furthermore, these abilities are separable and specific; some facets of spatial ability can be measured now, while others should be measurable in the near future. Nonetheless, there are numerous open questions about spatial abilities. Uttal and colleagues (2013, p. 370) observe, “ . . . much of the focus of research on spatial cognition and its development has been on the biological underpinnings of these skills. . . . Perhaps as a result, relatively little research has focused on the environmental factors that influence spatial thinking and its improvement.” As noted by a previous National Research Council committee, “Through the support of federal funding agencies . . . there should be a systematic research program into the nature, characteristics, and operations of spatial thinking” (National Research Council, 2006, p. 7).

Ultimately, the Army would benefit from learning the utility of spatial abilities in determining the (a) initial selection of recruits, (b) their preferred choices for occupations, (c) their actual classification into occupations, (d) their long-term retention in those occupations (and in the Army), and (e) their performance in those occupations. The path to addressing those important questions first requires answers to more basic questions about spatial abilities in general, how they can be developed (or trained), and how they can be most appropriately measured.

RESEARCH RECOMMENDATION

1. Identify or develop measures of various facets of spatial ability, with particular attention to the role of technology to overcome prior limitations in test-item formats.
2. Examine the interrelationships among various facets of spatial ability, including but not limited to spatial relations, spatial orientation, and spatial visualization.
3. Examine sex differences on the various facets of spatial ability, as well as the degree to which sex differences are mitigated or accentuated by various forms of training on the facets of spatial ability.
4. Develop measures reflecting various work outcomes that can be used as criterion measures in evaluating the validity of various measures of spatial ability.

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