The factor structure and criterion validity of a test for assessment of cognitive abilities. Comparing students in special and regular education

As a consequence of a recent reform of junior secondary education in the Netherlands, instruments for the assessment of cognitive abilities of students who are eligible for special educational support must be designed. In constructing a new test battery contemporary theory on crystallized and fluid intelligence (Gf-Gc theory) was considered. Complete coverage of the factors in Gf-Gc theory was not striven for, because the status of some of these factors in relation to referral to education with special educational support is not entirely clear. The sample in the study consisted of students from regular and special primary as well as secondary education, aged between 11 and 15 years. Approximately two-thirds of the sample was of Dutch origin, whereas the remaining third was of a different ethnic origin. Results show that the factors verbal-crystallized ability, fluid-reasoning ability, spatial-visualization ability and memory capacity can explain the positive correlations between the tests in the battery for the greater part. Students from regular and special education can be distinguished on the basis of their cognitive profiles reasonably accurate, thus supporting the criterion validity of the test battery. Students requiring special educational support are characterized by a significant discrepancy between short-term recall and long-term retention and retrieval.     

A test of theoretical models that account for information processing demands

This study tested four theoretical models in terms of their fit with demands placed on our cognitive system by traditional tests of cognitive ability. We did so by administering seven tests of cognitive ability known to require varying types of processing demands to a large group of college undergraduates (N = 193). We compared the models using confirmatory factor analyses, including those based upon a unitary factor, speed and capacity, crystallized and fluid intelligence, and verbal and spatial ability. The crystallized/fluid model provided the best fit with the data. This finding is consistent with previous research. Implications for education and future research are discussed.     

The Armed Services Vocational Aptitude Battery (ASVAB): Little more than acculturated learning (Gc)!?

The Armed Services Vocational Aptitude Battery (ASVAB) is administered to over 1 million participants in the USA each year, serving either as a screening test for military enlistees or as a guidance counseling device in high schools. In this paper, we examine the factorial composition of the ASVAB in relation to the theory of fluid and crystallized intelligence and Carroll's [1993. Human cognitive abilities: a survey of factor-analytic studies. New York: Cambridge Univ. Press.] three-stratum model. In two studies (N=349, N=6751), participants were administered both the ASVAB and tests designed to measure factors underlying these (largely) analogous models. Exploratory and confirmatory factor analyses (CFA) of correlational data suggested that the ASVAB primarily measures acculturated learning [crystallized intelligence (Gc)]. This evidence does not support the frequent claim that this test measures psychometric g. Our conclusion is that the ASVAB should be revised to incorporate the assessment of additional broad cognitive ability factors, particularly fluid intelligence and learning and memory constructs, if it is to maintain its postulated function.     

Correlates of individual,and age-related,differences in short-term learning

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability.     

Individual differences in speed of mental processing and human cognitive abilities: Toward a taxonomic model

Extensive research within the field of learning and individual differences focuses upon the relationship between general intelligence and process measures derived from elementary cognitive tasks (ECTs). This emphasis has ignored data indicating that cognitive abilities are best described by three levels (or strata). It has also been suggested that mental speed is a unitary construct, although it is more likely to have a complex structure. To address shortcomings evident in this literature, a multivariate investigation (N = 179) was conducted. Factor analysis of 25 psychometric indices gave seven factors postulated under the theory of fluid (G_f) and crystallized (G_c) intelligence. Correlations between cognitive abilities and parameters derived from 11 ECTs indicated that G_f (alone) was related to processing speed. This relationship is seemingly dependent upon experimental manipulations of task complexity. Regarding the factorial structure of mental speed, the results were unequivocal: Broad second-order factors may be derived from both ECTs and psychometric tests. These constructs are independent from abilities defined by accuracy scores and collectively define a general cognitive speed factor. Implications of these findings are discussed. It would appear that mental speed is more intricate than proposed, and that cognitive complexity (reflected in stimulus-response compatibility effects) plays a crucial role in its ontogenesis. In addition, several explanatory models linking intelligence to processing speed are untenable. It is likely that the search for a basic process of intelligence by means of mental speed frameworks (alone) is misguided.Recently, within the field of individual differences, there has been “an explosion of experimental studies into the speed of mental processes” (H.J. Eysenck 1995, p. 225). Various tasks, ranging from those paradigms assessing simple, psychomotor movements and on up through to measures of complex problem solving and psychometric test performance, have been employed (Stankov & Roberts 1997). The present study was designed to explore speed of processing constructs within a structural model of human cognitive abilities. Utilizing the evidence presented in Carroll's (1993) extensive reanalysis of the main data sets collected within the psychometric discipline this century, the structural model of cognitive abilities adopted is that known as the theory of fluid and crystallized intelligence (see Horn & Noll 1994; Stankov et al. 1995). In contrast, the mental speed measures selected for investigation in this study were chosen on the basis of both experimental and psychometric findings that rely on disparate accounts (e.g., information theory). Notably, mental speed constructs are not presently encapsulated within a single unifying model. Another major aim of the present study was to redress this imbalance by establishing a rapprochement between conceptual models of mental speed and human cognitive abilities.     

Reciprocal effects between fluid and crystallized intelligence and their dependence on parents' socioeconomic status and education

The investment theory of Cattell supposes an influence of fluid on crystallized intelligence. The development of fluid intelligence largely depends on biological factors, of crystallized intelligence on fluid intelligence and environmental stimulation. To test this theory two contrasting samples representing a broad ability range were chosen, a Brazilian sample (ages 7 to 15, N = 833, mean IQ 92) and a sample with a higher ability level in Germany (ages 11 to 19, N = 722, IQ 118). Analyses of cross-lagged effects across two year intervals show similar effects of fluid intelligence on crystallized and vice versa (around β = .17). Parental socioeconomic status and parental education have in both samples a slightly stronger effect on crystallized than on fluid intelligence. The first result refutes Cattell's theory, the second gives some support. The development of fluid intelligence also seems to be influenced by non-biological environmental factors resulting in a concept of intelligence as a malleable ability.     

COGNITIVE,MOTIVATIONAL AND TEMPERAMENTAL INDICANTS OF CREATIVITY AND INTELLIGENCE1

Relationships between measures of creativity and measures of intelligence were analysed to show that even when the intercorrelations among the former are not appreciably larger than correlations between creativity and intelligence measures, dimensions of creativity are found to be psychometrically and conceptually distinct from dimensions of intelligence. One hundred eighty-eight art and engineering college students were administered objective tests and questionnaires designed to tap a number of ability and nonability indicants of creativity and intelligence. Some of these measures were of a kind that some investigators would regard as “criterion” measures of creativity and intelligence. Data were analysed by means of correlational and factor analytic procedures. Eight major influences were indicated by independent factors rotated to approximate simple structure. The influences represented by these factors were identified as: fluid intelligence, crystallized intelligence, memory, fluency, rule-orientation versus intuitive thinking, and self-sufficient-calculated-risk-taking. The fourth, seventh, and eighth factors were discussed as representing distinct cognitive, motivational, and temperamental aspects of creativity. At the level of test intercorrelations discriminant validity did not obtain–measures of creativity did not intercorrelate more highly among themselves than they correlated with measures of intelligence. The putative factors of creativity did correlate more highly with creativity criteria, however, than did the factors identified as representing intelligence. Moreover, the intelligence factors were more highly related to intelligence criteria than to creativity criteria. Thus the evidence of this study suggests that it is useful to think of creativity and intelligence as the outgrowths of distinct (although overlapping) sets of influences, even when this is not well indicated by discriminant-convergent validation analyses carried out with respect to tests (in contrast to factors).     

Children's agency beliefs, cognitive performance, and conceptions of effort and ability: individual and developmental differences

In order to understand how children's beliefs and cognitive performance vary according to development in their conceptions of effort and ability, 120 fourth and sixth graders were given the following assessments: (a) a measure of agency beliefs, defined as the extent to which persons believe they have access to certain classes of potential means, including effort, ability, powerful others, and luck; (b) a battery of intelligence test scales, including figural patterns, letter series, arithmetic, and spelling; (c) an interview designed to assess developmental levels in conceptions of effort and ability. Correlations between intelligence scores and agency beliefs for effort decreased with increasing levels of reasoning about effort and ability, but correlations between intelligence scores and agency beliefs for ability increased with increasing levels of reasoning. No such trends were found in correlations between performance and agency beliefs for luck or for unknown causes. The results are discussed in terms of the interaction between individual differences and developmental change.     

Explorations of crystallized intelligence: Completion tests,cloze tests,and knowledge

An attempt is made to reconcile two historically important tools for the assessment of intelligence and the prediction of academic achievement with extant theories of verbal–crystallized–knowledge aspects of adult abilities. A study of 167 adults ranging in age from 18 to 69 reasserts the importance of individual differences in completion test and cloze test performance in accounting for both measures of crystallized intelligence (Gc) and four scales of knowledge (biology, U.S. history, U.S. literature, and technology). The completion tests were found to account for all of the variance in Gc and knowledge that the cloze tests accounted for, and resulted in incremental predictive validity for both domains. In addition, completion and cloze tests were found to have a suppressor effect on the relationship between Gc and Age. We note that C. Spearman's [The nature of “Intelligence” and the principles of cognition. New York: MacMillan (1927).] assertion, namely that the completion test had higher correlations with intelligence than any other measure. Our results suggest that abstract reasoning may be far less useful in predicting learning and performance than the completion test is.     

Self estimates of general,crystallized, and fluid intelligences in an ethnically diverse population

Self-estimated intelligence is a quick way to assess people's conceptions of their own abilities. Furnham (2001) and colleagues have used this technique to make comparisons across culture and gender and different approaches to intelligence (such as g or Multiple Intelligences). This study seeks to build on past work in two ways. First, a large, diverse sample (N = 2309) enables the study of self-estimated intelligence across ethnicity. Second, one of the most prominent accepted intelligence theories is the Cattell–Horn–Carroll (CHC) theory. Can laypeople distinguish between general, fluid, and crystallized intelligence? This study finds evidence for a “modesty bias” in Hispanic Americans. In addition, fluid and crystallized intelligences may simply be seen as general intelligence (particularly by Caucasians and males).     

Age versus schooling effects on intelligence development

The effect of formal education, as opposed to chronological age, on intelligence development has suffered from inadequate empirical investigation. Most studies of this issue have relied on natural variation in exposure to school among children of the same age, thus confounding differences in schooling with differences in other intelligence-related variables. This difficulty can be overcome by a quasi-experimental paradigm involving comparison between children who differ in both chronological age and schooling. The present study applies this paradigm to the estimation of the independent effects of age and schooling in grades 5 and 6 on raw scores obtained on a variety of general ability tests. The sample included all students in Jerusalem's Hebrew-language, state-controlled elementary schools. The results unambiguously point to schooling as the major factor underlying the increase of intelligence test scores as a function of age and to the larger effect schooling has on verbal than nonverbal tests. These results contribute to our understanding of the causal model underlying intelligence development and call for reconsideration of the conceptual basis underlying the definition of deviation-IQ scores. Some implications of these results concerning the distinction between intelligence and scholastic achievement, the causal model underlying the development of "crystallized" and "fluid" abilities, and the notion of "culture-fair" tests are discussed.     

The Comprehensive Assessment of Rational Thinking

The Nobel Prize in Economics was awarded in 2002 for work on judgment and decision-making tasks that are the operational measures of rational thought in cognitive science. Because assessments of intelligence (and similar tests of cognitive ability) are taken to be the quintessence of good thinking, it might be thought that such measures would serve as proxies for the assessment of rational thought. It is important to understand why such an assumption would be misplaced. It is often not recognized that rationality and intelligence (as traditionally defined) are two different things conceptually and empirically. Distinguishing between rationality and intelligence helps explain how people can be, at the same time, intelligent and irrational. Thus, individual differences in the cognitive skills that underlie rational thinking must be studied in their own right because intelligence tests do not explicitly assess rational thinking. In this article, I describe how my research group has worked to develop the first prototype of a comprehensive test of rational thought (the Comprehensive Assessment of Rational Thinking).     

Fluid/spatial and crystallized intelligence in relation to domain-specific working memory: A latent-variable approach

Fluid/spatial intelligence, crystallized intelligence and their relationships to verbal and visuospatial working memory (WM) were studied. A total of 120 Finnish Air Force recruits participated in this study. Fluid/spatial intelligence was assessed using four different tasks, while crystallized intelligence was defined with the help of test scores of Finnish upper secondary school National Matriculation Tests in three different academic subjects and one additional Verbal Relations task. Complex WM span tasks were used to measure visuospatial and verbal WM capacities. Structural equation modeling indicated that verbal WM was related to crystallized intelligence when both WM tasks were included in the model, whereas performance on the visuospatial WM task was related to fluid/spatial intelligence, but not to crystallized intelligence. Verbal WM was not related to fluid intelligence when used as a single WM predictor. The results indicate that verbal WM might be related to verbal ability and learning at school, while visuospatial WM is relatively strongly related to nonverbal reasoning and spatial visualization. The current results further suggest that WM capacity is not a unitary system.     

Plasticity in fluid intelligence of older adults: An individual latent growth curve modeling application

This article is concerned with modeling the individual latent growth curves of older adults on measures of fluid intelligence in a 2‐group cognitive intervention study (Baltes, Dittmann‐Kohli, & Kliegl, 1986). Second‐order polynomial growth curves reflecting initial test performance improvement followed by relative stability/drop are fitted to the recorded scores of each participant. Experimental subjects are found to exhibit mean ability growth outperforming that shown by untrained subjects. Both the control and experimental groups, however, demonstrate the same pattern of interrelationships among the individual ability intercepts, linear slopes, and quadratic bend parameters of the growth curves. The results suggest substantial amount of plasticity in fluid intelligence of older adults, and that elders may be capable of considerably improving their performance on repeatedly presented fluid measures by capitalizing on interrelationships between fluid intelligence subabilities.     

试论多元智力理论对素质教育的启示

多元智力理论认为,智力是在某种社会或文化环境标准下,个体用以解决自己遇到的真正难题或生产及创造出有效产品的能力.智力具有多元性、差异性、开放性、文化性、实践性以及创造性.多元智力理论对素质教育理论依据的发现、对素质教育模式的界定、对素质教育文化的创生等方面都有重要的启示作用.     

The Use of Biological Measures to Estimate Behavioral Intelligence

Little attention has been paid to biological or physiological correlates of mental ability in the development of theories or tests of intelligence. A number of such biological correlates exist, however; some showing a pronounced relationship with performance on standard intelligence tests. Given the magnitude of the correlations that exist between behavioral intelligence and such measures as averaged evoked potentials, nerve conduction velocity, and cerebral glucose metabolic rate, it is proposed that an appropriately weighted combination of these and other physiological processes could provide a reliable, culture-fair estimate of intelligence that could be administered in the same manner to persons of almost any age or level of ability. Biological approaches to the measurement of intelligence may not replace traditional assessments, but the information that they can provide deserves greater attention than typically has been the case.     

Prediction of reading by Ga and Gc specific cognitive abilities for low‐SES white and hispanic English‐speaking children

Based on previous findings (McGrew, Flanagan, Keith, & Vanderwood, 1997) that auditory processing (Ga) predicts reading decoding, and crystallized intelligence (Gc) predicts reading comprehension beyond the prediction of reading by g(broad general intelligence), this study examined the cross‐ethnic predictive validity of Ga and Gc for reading achievement among low‐SES English‐speaking White and Hispanic students. Subtests of the Woodcock‐Johnson Psycho‐Educational Battery‐Revised (WJ‐R) cognitive subtests were used to measure Ga and Gc, and the WJ‐R achievement subtests were used to measure basic reading skills and reading comprehension. Results indicated that there are no differences between ethnic groups in the prediction of reading ability, and that phonetic coding and crystallized intelligence together are strong predictors of reading achievement. © 2000 John Wiley & Sons, Inc.     

Modeling complexity and difficulty in measures of fluid intelligence

This article applies structural equation modeling to the simultaneous study of task complexity and difficulty in measures of fluid intelligence. The interrelation between 3 tests of fluid intelligence, 2 experimental tasks, and age is examined. Each experimental task is decomposed into 4 subtasks, with the most intellectually demanding ones being measures of fluid intelligence, and the remaining 3 levels constructed to be gradually simpler. The findings suggest that the experimental manipulations produced systematic changes in 3 sets of parameters. These are: (a) the mean intercept parameters of the structural equation model—interpreted as “pure test difficulties” reflecting task‐specific demands placed on elementary cognitive processes of the “same kind” (b) factor loadings on 2 subtask‐specific narrow factors (SWAPS and TRIPLETS) that reflect demands placed on processes of “similar kinds,” that is, processes common to variations within the same experimental task; and (c) factor loadings on a fluid intelligence factor (Gf) that reflect demands placed on processes of “diverse kinds,” which are common to measures of a broad range of different cognitive tasks. The results indicate that as task requirements become more demanding, cognitive processes of the same kind, which are involved in solving the easier subtasks, are no longer critical to performance, but the demand on processes of similar and diverse kinds is increased. It is suggested that for human subjects, increase in task complexity may be associated with lapses of attention in the course of carrying out a series of interconnected steps.     

The Genetic‐Environmental Influences on Individual Cognitive Functioning or IQ

While some researchers place greater emphasis on heredity causes of individual differences in cognitive functioning, others place greater emphasis on cultural and environmental factors (broadly defined). Still others place greater stress on the dynamic interrelationship between the genetic components and the environmental components in accounting for individual cognitive functioning. The paper examines these views and concludes that intelligence is far more complex than hereditarians would admit and that although we may go along with the view that heredity could set the limit to cognitive development, it is not possible to tell what this limit is, if we define intelligence as a multifaCEDSd, multicausal phenomenon, which is partially malleable and capable of expression in many diverse ways.     

Individual differences in working memory, nonverbal IQ, and mathematics achievement and brain mechanisms associated with symbolic and nonsymbolic number processing

Individual differences in mathematics performance may stem from domain-general factors like working memory and intelligence. Parietal and frontal brain areas have been implicated in number processing, but the influence of such cognitive factors on brain activity during mathematics processing is not known. The relationship between brain mechanisms during symbolic and nonsymbolic number comparison and individual differences in working memory, nonverbal IQ, and mathematics achievement were investigated to determine possible associations with behavior and brain function. A number of brain areas showed correlations with working memory and number processing. For symbolic digits, working memory showed a positive relationship with brain activity in a network of bilateral parietal, temporal, and right frontal regions. For nonsymbolic dot arrays, working memory showed a negative relationship with several parietal and frontal brain areas. This relationship indicates differences between behavioral and brain function measures and points to the importance of working memory and basic number processing.