Handbook of psychology volume 7 educational psychology
Contemporary Theories of Intelligence
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- Contemporary Theories of Intelligence 31
- Explicit Theories A Psychometric Theory
- Cognitive Theories
- Biological Theories
- Early Biological Theories.
- Contemporary Theories of Intelligence 33
- Contemporary Biological Theories.
30 Contemporary Theories of Intelligence Africa views people of higher social class and distinction as speaking less (Irvine, 1978). This difference between the Wolof and Western notions suggests the usefulness of look- ing at African notions of intelligence as a possible contrast to U.S. notions. In fact, studies in Africa provide yet another window on the substantial differences. Ruzgis and Grigorenko (1994) have argued that, in Africa, conceptions of intelligence re- volve largely around skills that help to facilitate and maintain harmonious and stable intergroup relations; intragroup rela- tions are probably equally important and at times more im- portant. For example, Serpell (1974, 1982, 1993) found that Chewa adults in Zambia emphasize social responsibilities, cooperativeness, and obedience as important to intelligence; intelligent children are expected to be respectful of adults. Kenyan parents also emphasize responsible participation in family and social life as important aspects of intelligence (Super, 1983; Super & Harkness, 1982). In Zimbabwe, the word for intelligence, ngware, actually means to be prudent and cautious, particularly in social relationships. Among the Baoule, service to the family and community and politeness toward and respect for elders are seen as key to intelligence (Dasen, 1984). Similar emphasis on social aspects of intelligence has been found as well among two other African groups, the Songhay of Mali and the Samia of Kenya (Putnam & Kilbride, 1980). The Yoruba, another African tribe, empha- size the importance of depth—of listening rather than just talking—to intelligence, and of being able to see all aspects of an issue and of being able to place the issue in its proper overall context (Durojaiye, 1993). The emphasis on the social aspects of intelligence is not limited to African cultures. Notions of intelligence in many Asian cultures also emphasize the social aspect of intelli- gence more than does the conventional Western or IQ-based notion (Azuma & Kashiwagi, 1987; Lutz, 1985; Poole, 1985; White, 1985). It should be noted that neither African nor Asian cultures emphasize exclusively social notions of intelligence. In one village in Kenya (near Kisumu), many and probably most of the children are at least moderately infected with a variety of parasitic infections. As a result, they experience stom- achaches quite frequently. Traditional medicine suggests the usefulness of a large variety (actually, hundreds) of natural herbal medicines that can be used to treat such infections. It appears that at least some of these—although perhaps a small percentage—actually work. More important for our pur- poses, however, children who learn how to self-medicate via these natural herbal medicines are viewed as being at an adaptive advantage over those who do not have this kind of informal knowledge. Clearly, the kind of adaptive advantage that is relevant in this culture would be viewed as totally irrelevant in the West, and vice versa. Grigorenko and her colleagues (2001) have studied con- ceptions of intelligence in this village in some detail. There appear to be four parts to the conception. First, the concept of rieko can be translated as intelligence, smartness, knowledge, ability, skill, competence, and power. Along with the general concept of rieko, the Luo people distinguish among various specialized representations of this concept. Some representations are characterized by the source of rieko: rieko mar sikul (knowledge acquired in school), or rieko mzungu (the White man’s technical powers); others by different domains of action: rieko mar ot (compe- tence in household tasks, including planning skills and re- source management), or rieko mar kite (being versed in traditional customs and rules). Other representations are characterized by specific outcomes, such as rieko mar lupo (fishing skills, including knowledge of magic to provide rich catches), rieko mar yath (knowledge of healing with herbal medicines), and so forth. Luoro is the second main quality of children and people in general. It encompasses a whole field of concepts roughly corresponding to social qualities such as respect and care for others, obedience, diligence, consideration, and readiness to share. Luoro has an unequivocal positive meaning and was always mentioned as a necessity in response to questions such as “What is most important for a good child to have?” and “What should people have to lead a happy life?” When people were asked to compare the relative importance for an individual’s life of rieko and luoro, respondents generally gave preference to luoro. It is interesting that the only two re- spondents ranking rieko higher than luoro were outsiders to the local community who had a tertiary education and con- siderable wealth by village standards. Rieko and luoro are complementary. Rieko is a positive attribute only if luoro is also present. Ideally, the power of pure individual abilities should be kept under control by social rules. Third, paro overlaps with both luoro and rieko and, roughly translated, means thinking. Specifically, paro refers to the thought processes required to identify a problem and its solution and to the thought processes involved in caring for other people. A child with good thinking ( paro maber) could thus, for example, be a child who is able to react rationally in case of another person’s accident or one who is able to collect wood, burn charcoal, and sell it favorably in order to help his old grandmother. The concept of paro stresses the procedural nature of intelligence. In essence, paro occupies an interme- diate position between the potentiality of rieko (its ability as- pects) and the partially moral connotation of an outcome (the deed) done with or without luoro. Paro also reflects the idea of initiative and innovation, for example, in designing a new
Contemporary Theories of Intelligence 31 technical device. Paro encompasses the process of thinking, the ability to think, and the specific kind of thinking that an individual demonstrates. Fourth, winjo, like paro, is linked to both rieko and luoro.
the child’s abilities to comprehend, that is, to process what is said or what is going on. But it also involves the ability to grasp what is appropriate and inappropriate in a situation, that is, to understand and do what you are told by adults or to derive from the situation what is appropriate to do. It shares with the other key terms the feature that its meaning is a func- tion of context. For a teacher in school it means that a child runs an errand as told. In contrast, a grandmother teaching a child about healing might emphasize the aspect of procedural learning combined with attention to another person. A “good child” as well as a “good community member” needs a balanced mixture of all positive qualities, in which the contradictory aspects counterbalance each other. Specifi- cally, the ambiguous powers of individual rieko (which could be either positive or negative) need to be controlled by social values and rules (luoro). These conceptions of intelligence emphasize social skills much more than do conventional U.S. conceptions of intelli- gence, but at the same time they recognize the importance of cognitive aspects of intelligence. It is important to realize, again, that there is no one overall U.S. conception of intelli- gence. Indeed, Okagaki and Sternberg (1993) found that dif- ferent ethnic groups in San Jose, California, had rather different conceptions of what it means to be intelligent. For example, Latino parents of schoolchildren tended to empha- size the importance of social-competence skills in their con- ceptions of intelligence, whereas Asian parents tended rather heavily to emphasize the importance of cognitive skills. Anglo parents also emphasized cognitive skills more. Teach- ers, representing the dominant culture, emphasized cognitive skills more than social-competence skills. The rank order of children of various groups’ performances (including sub- groups within the Latino and Asian groups) could be per- fectly predicted by the extent to which parents shared the teachers’ conceptions of intelligence. In other words, teach- ers tended to reward those children who were socialized into a view of intelligence that happened to correspond to the teachers’ own.
The psychometric approach to intelligence is among the old- est of approaches, dating back to Galton’s (1883) psy- chophysical theory of intelligence in terms of psychophysical abilities (such as strength of hand grip or visual acuity) and later to Binet and Simon’s (1905/1916) theory of intelligence as judgment, involving adaptation to the environment, direc- tion of one’s efforts, and self-criticism. Carroll (1993) has proposed a hierarchical model of intel- ligence, based on a factor analysis of more than 460 data sets obtained between 1927 and 1987. His analysis encompasses more than 130,000 people from diverse walks of life and even countries of origin (although non-English-speaking countries are poorly represented among his data sets). The model Carroll proposed, based on his monumental undertak- ing, is a hierarchy comprising three strata: Stratum I, which includes many narrow, specific abilities (e.g., spelling ability, speed of reasoning); Stratum II, which includes various group-factor abilities (e.g., fluid intelligence, involved in flexible thinking and seeing things in novel ways; and crys- tallized intelligence, the accumulated knowledge base); and Stratum III, which is just a single general intelligence, much like Spearman’s (1904) general intelligence factor. Of these strata, the most interesting is perhaps the middle stratum, which includes (in addition to fluid and crystallized abilities) learning and memory processes, visual perception, auditory perception, facile production of ideas (similar to verbal fluency), and speed (which includes both sheer speed of response and speed of accurate responding). Although Carroll does not break much new ground, in that many of the abilities in his model have been mentioned in other theo- ries, he does masterfully integrate a large and diverse factor- analytic literature, thereby giving great authority to his model. At the same time, his meta-analysis assumes that con- ventional psychometric tests cover the entire domain of intel- ligence that needs to be covered by a theory of intelligence. Some theorists, discussed next, question this assumption.
Cronbach (1957) called for a merging of the two disciplines of scientific psychology: the differential and experimental approaches. The idea is that the study of individual differ- ences (differential psychology) and of cross-individual com- monalities (experimental psychology) need not be separate disciplines. They can be merged. Serious responses to Cronbach came in the 1970s, with cognitive approaches to intelligence attempting this merger. Two of the responses were the cognitive-correlates approach to intelligence and the cognitive-correlates approach. Hunt, Frost, and Lunneborg (1973; see also Hunt, Lunneborg, & Lewis, 1975) introduced the cognitive- correlates approach, whereby scores on laboratory cognitive tests were correlated with scores on psychometric intelli- gence tests. The theory underlying this work was that fairly 32 Contemporary Theories of Intelligence simple components of information processing studied in the laboratory—such as the time to retrieve lexical information from long-term memory—could serve as a basis for under- standing human intelligence. Intelligence tests, on this view, present complex problems whose solution nevertheless relies on fairly simple information processing. Thus, a participant in a cognitive study might be asked whether two letters, A and a, are identical in identity (answer: yes) or identical in case (answer: no). The tasks were directly out of the literature of experimental psychology, including the letter-comparison task, which is based on work by Posner and Mitchell (1967). Sternberg (1977; see also Sternberg, 1983) introduced the cognitive-components approach, whereby performance on complex psychometric tasks was decomposed into ele- mentary information-processing components. The underlying theory was that intelligence comprises a series of component information processes. In contrast to the cognitive-correlates approach, however, the underlying components were seen as complex rather than as simple. For example, solving an anal- ogy of the form A : B :: C : ? involves components such as encoding the terms, inferring the relation between A and B, applying this relation from C to ?, and so forth (see review by Lohman, 2000). The cognitive approaches of Hunt and Sternberg are now primarily of historical interest. Both authors have expanded their conceptualizations of intelligence since this work. They were forced to do so. Neither approach yielded consistently high correlations between the tasks and task components and psychometric tests of intelligence used as criteria. Moreover, sometimes the components showing the highest correlations were the ones least expected to show them. Sternberg and Gardner (1983), for example, consistently found the regression-constant component to have the highest correlations with psychometric test scores, leading them to wonder whether they had rediscovered through information- processing analysis the general factor that had been discovered through psychometric analysis. In the 1990s cognitive and biological approaches (dis- cussed next) began to merge (Vernon, Wickett, Bazana, & Stelmack, 2000). A prototypical example is the inspection- time task (Nettlebeck, 1982; see reviews by Deary, 2000; Deary & Stough, 1996). In this task, two adjacent vertical lines are presented tachistoscopically or by computer, fol- lowed by a visual mask (to destroy the image in visual iconic memory). The two lines differ in length, as do the lengths of time for which the two lines are presented. The participant’s task is to say which line is longer. But instead of using raw re- sponse time as the dependent variable, investigators typically use measures derived from a psychophysical function esti- mated after many trials. For example, the measure might be the duration of a single inspection trial at which 50% accu- racy is achieved. Correlations between this task and measures of IQ appear to be about .4, a bit higher than is typical in psy- chometric tasks. Much of this correlation may be mediated by the visual ability component of intelligence (Gv). There are differing theories as to why such correlations are ob- tained. All such theories generally attempt to relate the cog- nitive function of visual inspection time to some kind of biological function, such as speed of neuronal conduction. Let us consider, then, some of the biological functions that may underlie intelligence. Biological Theories An important approach to studying intelligence is to under- stand it in terms of the functioning of the brain, in particular, and of the nervous system, in general. Earlier theories relat- ing the brain to intelligence tended to be global in nature, al- though they were not necessarily backed by strong empirical evidence. Because these earlier theories are still used in con- temporary writings and, in the case of Halstead and Luria, form the bases for test batteries still in contemporary use, they are described here briefly. Early Biological Theories. Halstead (1951) suggested that there are four biologically based abilities, which he called (a) the integrative field factor, (b) the abstraction factor, (c) the power factor, and (d) the directional factor. Halstead attributed all four of these abilities primarily to the functioning of the cortex of the frontal lobes. More influential than Halstead has been Hebb (1949), who distinguished between two basic types of intelligence: Intelli- gence A and Intelligence B. Hebb’s distinction is still used by some theorists. According to Hebb, Intelligence A is innate potential, and Intelligence B is the functioning of the brain as a result of the actual development that has occurred. These two basic types of intelligence should be distinguished from Intelligence C, or intelligence as measured by conventional psychometric tests of intelligence. Hebb also suggested that learning, an important basis of intelligence, is built up through cell assemblies, by which successively more and more complex connections among neurons are constructed as learning takes place. A third biologically based theory is that of Luria (1973, 1980), which has had a major impact on tests of intelligence (Kaufman & Kaufman, 1983; Naglieri & Das, 1997). Ac- cording to Luria, the brain comprises three main units with respect to intelligence: (a) a unit of arousal in the brain stem and midbrain structures; (b) a sensory-input unit in the tem- poral, parietal, and occipital lobes; and (c) an organization
Contemporary Theories of Intelligence 33 and planning unit in the frontal cortex. The more modern form of this theory is PASS theory (Das, Kirby, & Jarman, 1979; Naglieri & Das, 1990, 2002), which distinguishes among planning, attentional, successive processing, and si- multaneous processing abilities. These latter two abilities are subsets of the sensory-input abilities referred to by Luria. The early biological theories continue to have an influence on theories of intelligence. Oddly, their influence on contem- porary psychometric work is substantially greater than their influence on contemporary biological work, which largely (although not wholly) has left these theories behind. Contemporary Biological Theories. More recent theo- ries have dealt with more specific aspects of brain or neural functioning. One contemporary biological theory is based on speed of neuronal conduction. For example, one theory has suggested that individual differences in nerve-conduction ve- locity are a basis for individual differences in intelligence (e.g., Reed & Jensen, 1992; Vernon & Mori, 1992). Two pro- cedures have been used to measure conduction velocity, ei- ther centrally (in the brain) or peripherally (e.g., in the arm). Reed and Jensen (1992) tested brain-nerve conduction ve- locities via two medium-latency potentials, N70 and P100, which were evoked by pattern-reversal stimulation. Subjects saw a black-and-white checkerboard pattern in which the black squares would change to white and the white squares to black. Over many trials, responses to these changes were an- alyzed via electrodes attached to the scalp in four places. Cor- relations of derived latency measures with IQ were small (generally in the .1 to .2 range of absolute value), but were significant in some cases, suggesting at least a modest rela- tion between the two kinds of measures. Vernon and Mori (1992) reported on two studies investi- gating the relation between nerve-conduction velocity in the arm and IQ. In both studies nerve-conduction velocity was measured in the median nerve of the arm by attaching elec- trodes to the arm. In the second study, conduction velocity from the wrist to the tip of the finger was also measured. Vernon and Mori found significant correlations with IQ in the .4 range, as well as somewhat smaller correlations (around .2) with response-time measures. They interpreted their results as supporting the hypothesis of a relation between speed of information transmission in the peripheral nerves and intelli- gence. However, these results must be interpreted cautiously, as Wickett and Vernon (1994) later tried unsuccessfully to replicate these earlier results. Other work has emphasized P300 as a measure of intelli- gence. Higher amplitudes of P300 are suggestive of higher levels of extraction of information from stimuli (Johnson, 1986, 1988) and also more rapid adjustment to novelty in stimuli (Donchin, Ritter, & McCallum, 1979). However, at- tempts to relate P300 and other measures of amplitudes of evoked potentials to scores on tests of intelligence have led to inconclusive results (Vernon et al., 2000). Indeed, the field has gotten a mixed reputation because so many successful attempts have later been met with failures to replicate. There could be a number of reasons for these failures. One is almost certainly that there are just so many possible sites, potentials to measure, and ways of quantifying the data that the huge number of possible correlations creates a greater likelihood of Type I errors than would be the case for more typical cases of test-related measurements. Investigators using such methods therefore have to take special care to guard against Type II errors. Another approach has been to study glucose metabolism. The underlying theory is that when a person processes infor- mation, there is more activity in a certain part of the brain. The better the person is at the behavioral activity, the less is the effort required by the brain. Some of the most interesting recent studies of glucose metabolism have been done by Richard Haier and his colleagues. For example, Haier et al. (1988) showed that cortical glucose metabolic rates as re- vealed by PET scan analysis of subjects solving Raven Progressive Matrices problems were lower for more intelli- gent than for less intelligent subjects. These results suggest that the more intelligent participants needed to expend less effort than the less intelligent ones in order to solve the rea- soning problems. A later study (Haier, Siegel, Tang, Abel, & Buchsbaum, 1992) showed a similar result for more versus less practiced performers playing the computer game of Tetris. In other words, smart people or intellectually expert people do not have to work as hard as less smart or intellec- tually expert people at a given problem. What remains to be shown, however, is the causal direction of this finding. One could sensibly argue that the smart people expend less glucose (as a proxy for effort) because they are smart, rather than that people are smart because they expend less glucose. Or both high IQ and low glucose metabolism may be related to a third causal variable. In other words, we cannot always assume that the biological event is a cause (in the reductionist sense). It may be, instead, an effect. Another approach considers brain size. The theory is sim- ply that larger brains are able to hold more neurons and, more important, more complex intersynaptic connections between neurons. Willerman, Schultz, Rutledge, and Bigler (1991) correlated brain size with Wechsler Adult Intelligence Scale–Revised (WAIS-R) IQs, controlling for body size. They found that IQ correlated .65 in men and .35 in women, with a correlation of .51 for both sexes combined. A follow-up analy- sis of the same 40 subjects suggested that, in men, a relatively
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