Raphael Gamaroff, South African Journal of Linguistics, 1997, 15(1):11-18.
See also: Cognition & Language proficiency
Deep language and language proficiency in learning
Academic Failure among Black Learners in South Africa
2. Language of thought and intelligence
3. Intelligence as semiosis
4. Intelligence and fluid intelligence
5. Culture Fair Intelligence Test (CFIT) and the deep semiotic system
6. Deep semiotic system and natural language
7. Basic Interpersonal and Communicative Skills and C ognitive and Academic Language Proficiency
The notions of fluid intelligence and language as a deep semiotic representational system are examined. Many modern educational psychologists regard the concept of fluid intelligence as central to understanding cognitive abilities as manifested in intelligence tests and school performance. The deep semiotic system of the mind incorporates the total life of human beings in all their thoughts, feelings and activities. Oller’s intention is to provide a solid theoretical basis for the hypothesis that intelligence is a kind of semiotic representational capacity. The article deals with the relationship between the semiotic representational capacity, fluid intelligence and language proficiency. The connection between cognitive and academic language proficiency and intelligence is also discussed.
Linguists are thrust into a double abyss of ignorance; the abyss of language, and the abyss of the abyss, which is the study of language. Besides language there is cognition, which is inseparable from language. Linguists often do not have the time or inclination to study in depth the cognitive dimensions of language. The in-depth study of cognition in language is often left to psychologists, philosophers and anthropologists, who in turn may not have the necessary linguistic background to talk adequately about language in cognition. The organising principles of language and cognition as a deep semiotic phenomenon remain elusive, and therefore in the quest for illuminative paradigms there is always the danger of dismembering cognition. In this article the notions of fluid intelligence ‘(Horn & Cattell, 1966) and language as a deep semiotic representational system (Oller, 1991) are examined. Many contemporary psychologists regard the concept of fluid intelligence as central to understanding cognitive abilities as manifested in intelligence tests and school performance. The deep semiotic system of the mind incorporates the total life of human beings: thoughts, feelings and activities. Oller’s intention is to provide a solid theoretical basis for the hypothesis that intelligence is a kind of semiotic representational capacity that shares similarities with but also has differences to language proficiency. This article focuses mainly on the similarities. In academic/scientific discourse this semiotic capacity is manifested in Cognitive and Academic Language Proficiency (CALP) (Cummins, 1980, 1983, 1984). The relationship between the semiotic capacity, fluid intelligence and CALP is examined.
2. Language of thought and intelligence
Bloch (1991) maintains that much of our thinking is done through language, while Fodor, Bever & Garrett (1974), Fodor (1975, 1987) and Oller (1981; 1983; 1989; 1991) maintain that there is a non-verbal ‘language of thought’ or ‘deep language’. According to Pinker (1995:102) ‘language and thought have to be different’ because ‘a particular stretch of language can correspond to two distinct thoughts’.
Oller (1983: 355) defines deep language as a ‘deep propositional reasoning system’. Fodor, Bever & Garrett describe the role of this ‘deep propositional reasoning system’ in the following way:
‘Deciding on an action is, among other things, a computational process. In particular, it presupposes that the agent has access to a system of representation in which the various behavioral options can be formulated and assessed … Deciding upon an action itself involves the use of a language-like system, and this is true whether or not the action up for consideration happens to be a speech act’ (1974: 375).
This ‘deep propositional reasoning system’ (1974: 375) is, according to the above authors, the driving force behind all thought, whether the thought involves high-level reasoning tasks such as looking for causes and effects or low level reasoning tasks such as tying bootstraps. This ‘deep propositional reasoning system’ is not the ‘deep structure’ of Chomsky’s transformational grammar, which pertains to the grammar of a particular language (for example English) and designates a particular stage in the derivation of a sentence.
Pinker who distinguishes between ‘language’ and ‘thought’, also distinguishes between ‘language’ and ‘intelligence’. Pinker suggests that the probable genetic origin of ‘Specific Language Impairment (SLI)’ is a
‘hypothetical gene that does not seem to impair overall intelligence, because those who have the affliction score in the normal range in the nonverbal parts of IQ tests’ Pinker, 1995: 49).
3. Intelligence as semiosis
A proper study of language learning cannot be done without taking intelligence into account. One is aware of the sensitivity of the topic owing to the fact that IQ tests discriminate not only between individuals but have also discriminated between groups, specifically racial and ethnic groups. (One can discriminate scientifically or ideologically.) Whatever one’s opinion of IQ tests there is no doubt that they reveal real differences in intelligence between people:
To say that older or younger learners are better or worse is not normally considered a breach of egalitarian principles, for most of us have our turn at being young and old. Proposing some other explanations for difference is more questionable, for labeling one learner as inherently less qualified than another runs the risk of establishing or justifying permanent divisions among people. Consider explanations based on intelligence, for example. There is certainly a good deal of evidence that human beings vary considerably in whatever ability or abilities may underlie the construct that is labeled intelligence.
Oller (1991: iv) hypothesises that ‘intelligence itself is a kind of semiotic representational capacity’. This capacity is synonymous with notions such as ‘deep language’, ‘mentalese’, ‘language of thought’ and ‘deep propositional reasoning system’. This ‘theory of semiosis’ (Oller, 1991: 11) integrates linguistic, kinesic (gestural) and sensory motor systems. Oller maintains that
without such an integration it will be impossible to explain the fact that we can talk about what we see, or visualize what someone else talks about’ (1991: 11).
Oller acknowledges the valuable contribution of Charles Sanders Peirce (1897; 1931 ; 1992 ); John Dewey (1938) and Albert Einstein (1941; 1944) to his own thought. Peirce’s theory of signs, ‘semiosis’, incorporates thoughts, feelings and activities. Jackendoff (1983) refers to the essential relatedness between the linguistic, kinesic (gestural) and sensory-motor systems as the ‘cognitive constraint’. (See also Oller above).
There must be levels of mental representation at which information conveyed by language is compatible with information from other peripheral systems such as vision, nonverbal audition, smell, kinesthesia, and so forth. If there were no such levels, it would be impossible to use language to report sensory input. (Jackendoff, 1983:16).
(See also Fodor, 1975; 1987; and Pinker, 1995; for similar views)
These deep levels of mental representation do not only make it possible for us to talk about our sensory input but also to make sense of our sensory input. In order to achieve some understanding of how language works, we need to discover what it has in common with other semiotic systems, or to use the French equivalent term, ‘semiological’ systems (Saussure,  1974; Benveniste, 1969).
Oller suggests that owing to the fact that
language. especially one’s primary or best developed language, represents the most powerful and most general semiotic system for nearly all normal human beings, it follows that primary language abilities will play a central role in all sorts of abstract representational tasks. It is in this refined sense that the hypothesis that intelligence may have a kind of abstract semiotic (even a sort of deep linguistic) basis has, it would seem, its greatest plausibility and theoretical strength (Oller, 1991: iv).
Advances in brain sciences and genetics (e.g. Danesi, 1994; Paradis, 1991; Perecman, 1989; Pribham, 1971; Woese, 1967:4; Young, 1978) provide additional support for the theory that ‘deep language-like representational systems are critical to all aspects of biological organisation and neurological functioning’ (011er, 1991: 4). There may indeed be more to the biblical proposition ‘In the beginning was the word’ than meets the ear. For Vygotsky (1962) ‘in the beginning was the deed’, and ‘the word is the end of development, crowning the deed’ (quoted from Oller, 1991: 35; see his Note 1). It was only a few months after Vygotsky had made the latter remark that he died
never dreaming that his remarks would be tested in scarcely three decades by one of the most remarkable advances in the history of science – the discovery of the genetic code (Oller, 1991: 35).
Vygotsky’s view that ‘in the beginning was the deed’ is less plausible than the view that ‘in the beginning was the word’, the ‘deep’ word, which is the biological and logical predecessor of activity and development.
In the next section I discuss the relationship between intelligence and fluid intelligence, which will link into the subsequent section on nonverbal intelligence tests and the deep semiotic system.
4. Intelligence and fluid intelligence
Spearman (1904) attributed a dominant role to the ‘g’ factor namely ‘general intelligence’. The ‘g’ factor in intelligence is analogous to the notion of global/overall/general language proficiency, also known as the ‘unitary competence hypothesis’ (UCH) (Oller, 1976; 1979; 1983; Oller & Kahn, 1981). The UCH posits that a holistic language ability is manifested through the four language modes of listening, speaking, reading and writing and that, accordingly, it was possible to predict UCH from the output of any one of these modes. For example, a high level of proficiency in writing would indicate a high level of proficiency in all the other language skills. Spolsky expresses the overall proficiency claim in the following ‘necessary’ condition:
As a result of its systematicity, the existence of redundancy, and the overlap in the usefulness of structural items, knowledge of a language may be characterized as a general proficiency and measured (1989: 72).
In contrast to the UCH, the ‘divisible competence hypothesis’ posits that language proficiency does not consist of a unitary factor. A middle position holds that language proficiency consists of a hierarchy of a unitary factor and divisible factors. (See Oller, 1983a for a survey of the issues.)
As with theories of language proficiency, theories of intelligence also differ, and are analogous to the different theories of language proficiency. As mentioned, Spearman attributed a dominant role to the ‘g’ factor. Subsequent researchers regarded intelligence as hierarchical in nature, where the ‘g’ factor stands at the top of the hierarchy, and two major group factors stand on the stratum below. These two major group factors are (1) a verbal-numerical-educational factor and (2) a practical-mechanical-spatial-physical factor; other minor group factors occupy lower levels (Horn & Cattell, 1966).
Thurstone (1938) originally claimed that the ‘g’ factor could be accounted for by a number of primary factors, but later conceded that a ‘g’ factor could also be identified. Guilford (1959; 1966; 1967) rejected the notion of general intelligence and claimed to have identified 120 narrow factors that are generated by the three-way classification of the ‘Structure of Intellect’, namely, Content, Operation and Product. Cattell (1957; 1963; 1971), Horn (1965) and Horn & Cattell 1966) rejected the Thurstone model and took Spearman’s hierarchical concept of intelligence further. The Horn-Cattell model (1966) consists of Fluid Intelligence (Gf, Crystallized intelligence (Gc), General Speediness (Gs), General Visualization (Gv) and General Fluency (F). (Some authors use ‘g’ but others use ‘G’: they refer to the same concept.) For Horn and Cattell, the two main dimensions of intelligence are Gf and Gc, where Gf refers to a general innate attribute:
The fluid-crystallized theory argues that the primary abilities, which can be said to involve intelligence to any considerable degree, are organized at a general level into two principal classes or dimensions. One of these referred to as fluid intelligence ( abbreviated to Gf) is said to be the major measurable outcome of the influence of biological factors on intellectual development, that is, heredity, injury to the central nervous system (CNS) [Gf might be affected by brain damage or a smoking mother; Vernon, 1979: 48, R.G.] or to the basic sensory structures, etc. The other broad dimension, designated crystallized intelligence (abbreviated Gc), is said to be the principal manifestation of a unitariness in the influence of experimental-educative-acculturation influences. Each dimension is, according to theory, so pervasive relative to other ability structures and so obviously of an intellectual nature that each deserves the name of intelligence (1966: 253-254).
(See also Cattell, 1973: 58, and Horn, 1965,1985,1988.)
Pascuale-Leone & Goodman’s (1979: 352) M (mental power/energy) ‘can be regarded as an explication of Cattell’s “Gf’, which has a ‘heavy biogenetic basis’.
Contrary to Horn & Cattell, Carroll (1993: 639) argues for a distinction between I. G (as a third-order factor) and 2. Gf and Gc as second-order factors. (Carroll’s Chapters 5 to 15 are interpretations of factor-analytic studies in terms of a three-stratum theory of cognitive abilities’ (Carroll, 1993: 633). The following diagram, which is an abridgement of Carroll’s 1993: 626) outline of the structure of cognitive abilities, shows the relationship between general intelligence (G), fluid intelligence (F) and crystallized intelligence (C). I have omitted the following from Carroll’s original outline: broad visual perception, broad auditory perception, broad retrieval ability, broad cognitive speediness and processing speed. (Figure 1 below).
What is noticeable is that the ‘level factors’ in Gf (induction) are more abstract than those in Gc, where the factors in Gc are concerned with language abilities. Gf is closer than Gc to General Intelligence (stratum 3). Carroll indicates this by the distance of the boxes in stratum 2 from the General Intelligence box of stratum 3.
Thus Gf is more abstract than Gc, because it is closer to the General Intelligence box.
A high correlation exists between ‘fluid intelligence’ – which is responsible for ‘new’ conceptual learning – and crystallized intelligence’ which is manifested in education and experience; in language learning for example (Horn & Cattell, 1966; Jensen, 1972; Demetriou et al., 1992). A crucial point is that the quality of Gc is dependent on the quality of Gf because ‘the acquisition of knowledge and skills in the first place depends on fluid intelligence’ (Jensen, 1972: 80).
Many modern educational psychologists regard Gf as central to understanding cognitive abilities as manifested in intelligence tests and cognitive and academic language proficiency. For example, the neo-Piagetians Demetriou, Gustafsson, Eflides & Platsidou (1992: 90) use educational tasks that are shown to be directly related to fluid intelligence.
5. Culture Fair Intelligence Test (CFIT) and the deep semiotic system
A variety of nonverbal instruments have been used to measure fluid intelligence. In the Kaufman Adolescent and Adult Test (KAIT), where the major theory ‘underlying the KAIT is the Horn and Cattell view (1966) that intelligence can be separated into fluid intelligence and crystallized components (Brown, 1994), rebus1 learning and block designs are used, while Raven’s (1965) Progressive Matrices Test and Cattell’s (1973) Culture Fair Intelligence Test (CFIT) use figural shapes. There are various theoretical accounts of the processing in nonverbal tests, for example Carpenter, Just & Shell’s (1990) account of the processing in the Raven Progressive Matrices Test and Oller’s (1981; 1991) account of the processing in Cattell’s CFIT, which has many similarities with Raven’s Progressive Matrices (Oller, 1991:51 and 102). Oller’s account of the processing in the CFIT is dealt with here. Oller refers to the CFIT as a test of ‘g’ (general intelligence – Carroll’s stratum 3), while Cattell describes his CFIT as a test of Cf (fluid intelligence – Carroll’s stratum 2). Oller regards his ‘g’ as equivalent to Cattell’s Gf (fluid intelligence) because the processes Oller describes as belonging to ‘g’, Cattell describes as belonging to Gf. Oller’s description of the processing in the CFIT serves to illustrate what he means by the deep semiotic system. The point of Oller’s ‘logical analysis of intelligence test items’ (Oller, 1991:11) – Cattell’s CFIT – is to show that the processing involved in the CFIT (which Cattell claims tests Gf) is a test of what he regards as ‘g’ and also what he regards as (logical) evidence for the deep semiotic system. Thus, in the description of the CFIT, I shall equate Cattell’s Gf with Oller’s ‘g’ and with his deep semiotic system.
Cattell (1973: 5) claims that the CFIT is ‘designed to reduce as much as possible the influence of verbal fluency, cultural climate, and educational level’.
Cattell’s CFIT (1973: 7; see also Oller, 1981: 484) consists of three scales (that is, levels):
Scale 1. Four to eight years of age.
Scale 2. Eight to 14 years and adults of average intelligence.
Scale 3. Adults of high intelligence.
The rationale for different scales is the existence of stages in mental development. Pascuale-Leone & Goodman state that the ‘developmental growth curve of M measures in normal children … is very similar to the curves Cattell and his followers (e.g. Cattell, 1971) have reported for their measures of fluid intelligence or Gf, reaching asymptotic levels at late adolescence’ (original italics) (1979: 352).
Cattell’s Scale 3 (Adults) refers to people over the age of fourteen years. It is at about this age that one reaches, according to Pascuale-Leone & Cattell, one’s full mental potential.
Each scale consists of four subtests, which are composed of visual symbols that involve the perception of relationships:
I. Progressive series completion;
3. Matrices; and
Sample items of Scale 2 are provided in Figure 2. These subtests tap the following four operations:
Figure 2. Cattell’s CFIT Scale
Subtest 1: Progressive series completion
In the example above, the bar becomes progressively longer
The correct answer is choice 1.
Subtest 2: Classification
Five figures are presented where the aim is to select the one different from the others. The correct answer is choice 4.
Subtest 3: Matrices
The aim is to complete the matrix presented in the bottom right-hand corner. The correct answer is choice 1.
Subtest 4: Conditions
The aim here is to select from the five items the one where the dot would lie outside the box but inside the circle. Only choice 3 meets these conditions.
With regard to Cattell’s subtests 1 and 4, Oller argues that the mental processes required in subtest 1 to internally represent the dashes function
‘like a series of potential subjects which may be associated with predicates in a propositional manner. For instance, a logical predicate for the second dash in the series is that it is longer than the first’ (198 it 483).
In subtest 4 there are: firstly, the potential subjects ‘dot’, ‘circle’, ‘square’; secondly, a set of implicit predicates ‘inside’, ‘outside’; and thirdly, a set of superordinate operators ‘not’ and ‘and’. One has to discover the logical proposition ‘dot inside circle and outside square’ (Oller 1981: 483). This mental operation involves the testing of hypotheses that results in a mapping of the deep (abstract) propositional form into the visual elements. Oller’s (1981: 487) point is that it seems impossible to explain the mental processes revealed in the CFIT in non-propositional terms, that is, these mental processes cannot be explained without the ‘deep propositional reasoning system’ (the deep semiotic system; see also Oller, 1991: 49-55).
6. Deep semiotic system and natural language
What goes for nonverbal reasoning also goes for verbal reasoning, revealed in verbal intelligence tests and language proficiency tests. The relationship between intelligence and language proficiency has been the occasion of much controversy (Oller & Perkins, 1978; Boyle, 1987; Oller 1991). Oller (1978:14) states that the name of a test does not necessarily reveal what the test is in fact measuring, and that therefore an ‘intelligence’ test or an ‘achievement’ test may in actual fact be a language test more than anything else (see Gunnarson, 1978 for the same opinion). Oller’s meaning is not that intelligence tests and achievement tests are in fact nothing but language tests, but that it is difficult to know exactly what intelligence tests or achievement tests are measuring, owing to the fact that (natural) language pervades all verbal intelligence tests. What verbal and nonverbal tests have in common is that both presuppose what Fodor (1975) calls an ‘internal language’ or the ‘language of thought’. Fodor’s position is the following
1. There is no internal representation without an internal language. This applies to both human (including preverbal children) and infrahuman organisms (Fodor, 1975: 55);
2. We do not have any notion of how a language can be learnt other than by hypothesis formation and confirmation:
‘(L)earning a first language involves constructing grammars consonant with some innately specified system of language universals and testing those grammars against a corpus of observed utterances in some order fixed by an innate simplicity metric. And, of course, there must be a language in which the universals, the candidate grammars, and the observed utterances are represented. And, of course, this language cannot be a natural language since, by hypothesis, it is his first language that the child is learning’ (Fodor, 1975: 58).
In other words, we cannot learn a language, or anything, without hypothesising and unless we already possess an internal language. This internal language is the same notion as Oller’s deep semiotic (representational) system.
The kind of hypothesizing revealed in the CFIT (which involves the rejection of some and the acceptance of other hypotheses) plays an important role in language comprehension and production. It is this kind of hypothesising that is the basis of Oller’s (1979: 34) ‘pragmatic expectancy grammar’, which is the psychological source of ‘pragmatic language ‘hat is, language in use).
Consider the following list of pragmatic language demands required to understand a simple story (Schank, 1982:15), all of which involve hypothesizing:
Access and utilise raw facts.
Recognize stereotyped situations.
Make simple inferences.
Establish causal connections.
Track people’s goals.
Predict and generate plans.
Recognize thematic relationships between individuals and society.
Employ beliefs about the world.
For 0ller, it is the deep semiotic system that undergirds the abilities required to fulfil these demands listed above. Oller provides several examples to show that
in important ways “verbal items” have some common semiotic ground with “nonverbal” ones in the propositional operations that they require. For another, it should also be possible to examine the extent to which such items are distinct from so called “language proficiency” items’ (1991:55).
Oller uses a typical item from the original Binet tests to illustrate how verbal intelligence tests tap the deep semiotic system. The test-taker is required to point out the mistake in be following statement: The judge told the prisoner: ‘You are to be hanged at dawn. Let this he a warning to you’. On the surface there does not seem to be anything as profound as a deep semiotic system involved. One merely laughs at the joke. What’s so complicated about that? But, on deeper analysis, one discovers a network of categories of propositions, which involves a complex web of inferencing and hypothesising. To understand the joke (and to tell it) one has to have a large store of knowledge (for example semantic, syntactic, pragmatic knowledge, etc.) that involves not only facts but also all sorts of principled connections, that is relationships (between the facts). (See Oller, 1991: 56-60 for a detailed account.)
In the next section, I deal with an important distinction in language proficiency, and how it relates to intelligence.
7. BICS and CALP
Cummins (1980; 1983; 1984) divides language proficiency into the two categories of Basic Interpersonal and Communicative Skills (BICS) and Cognitive and Academic Language Proficiency (CALP).
Although BICS is the foundation of CALP and all healthy human beings automatically ‘acquire’ BICS in their mother tongue, it does not follow that all human beings are capable of ‘learning’ the level of CALP that is required for academic study. BICS and CALP are communicative as well as cognitive, but BICS is not academic language. In both BICS and CALP, language is used to think about language, but CALP does this in a far more cognitively demanding way, which makes a CALP task more like an academic task, and a BICS task more like a non-academic task.
Significant differences in intelligence do not have a significant effect on the acquisition of BICS, but they do play a significant role in the effective development of CALP. At the core of CALP is fluid intelligence, what I understand to be Chomsky’s (1967: 4) ‘intelligence’ or his ‘intellectual capacities’ (Chomsky, 1988:198):
We find that over a very broad range, at least, there is no difference in the ability to acquire and make effective use of human language at some level of detail, although there may be differences in facility of use. I see no reason for dogmatism on this score. So little is known concerning other cognitive capacities that we can hardly even speculate. Experience does seem to support the belief that people do vary’ in their intellectual capacities and their specialization. It would hardly come as a surprise if this were so, assuming that we are dealing with biological structures, however intricate and remarkable, of known sorts (Chomsky, 1988:198; my emphasis).
I equate Chomsky’s ‘ability to acquire and make effective use of human language at some level of detail’ with BICS. BICS is basic language and thus does not differ among individuals. There is no doubt that ‘there may be differences in facility of use’ (Chomsky, 1988:198) in less basic interpersonal and communicative skills, which goes beyond BICS and which involves ‘other cognitive capacities’ (Chomsky. 1988: 198). These ‘other cognitive capacities’, however, come more to the fore in CALP than in advanced interpersonal and communicative skills, owing to the fact that CALP (spoken and written) is more cognitively demanding than interpersonal skills.
Although healthy human beings have the same ‘amount’ of lower order intelligence to ‘acquire’ BICS in their mother tongue, not all human beings (a scurrilous notion?) have the same amount of higher order intelligence to ‘learn’ (a high level of) CALP. IQ tests are the best predictors of academic achievement (Locurto, 1991: 160; Itzkoff, 1991; Pearson, 1991: 111), where academic achievement is understandably often closely related to CALP (Cummins & Swain, 1986: 50).
One of the major problems of many learners who enter higher primary and lower secondary school, where a second language is the medium of instruction, is that they have gained neither the necessary knowledge nor developed the necessary skills through their mother tongue to succeed academically. Second language CALP cannot be separated from first language CALP, nor can either of these be separated from proficiency in the ‘content’ subjects. For Jensen (1972), Cummins & Swain (1986), Spolsky (1989), Chomsky (1988) ~d Cattell (1973), the river that runs through all academic ability is intelligence, specifically, as Jensen (1972) and Cattell (1973) maintain, ‘fluid’ intelligence.
Besides intelligence there is another important issue: To attain CALP in a first language, one must first know BICS in the first language. One of the causes of cognitive stagnation is the lack or proper use of BICS in the home and school. However, if a learner wants to develop CALP in a second language, for example ENGLISH (ESL – English as a second language), it is not necessary to develop BICS in English, owing to the fact that the attainment of a reasonable standard off BICS in ESL often only occurs after the attainment of a reasonable standard of CALP in ESL. In these circumstances, CALP in a second language is developed mostly through the modes of reading and writing. A crucial point is that a high level of BICS in a particular language (whether the mother tongue or another language) does not necessarily lead ~) a high level of CALP in the same language.
In South Africa many non-mother-tongue speakers of English are obliged to develop BICS in English in order to gain a foothold in CALP in English, because they haven’t developed sufficiently in the CALP of their mother tongue to move relatively smoothly into CALP in English. Thus, one of the major problems in South African education is that disadvantaged learners have not developed sufficient CALP in their mother tongue, which is dependent on the development of BICS in the mother tongue. Consequently they are obliged to learn CALP in English. To add to their plight, they have to develop BICS in English and CALP in English both at the same time.
With regard to cultural factors, ‘Western’ culture emphasises the kind of knowledge and skills involved in both Gf and Gc. According to Kaplan (1966) academic thinking is culture-bound, which supports McDonough’s (1986: 20) view that Western academic concept formation is foreign to a non-Western mind where ‘students from a different “concept world” may be under more pressure than is realised’. In contrast, protagonists of English as an International Language claim that many scientific fields such as biology, medicine, physics, psychology, and linguistics transcend particular cultures.
The deep semiotic system of the mind incorporates the total life of human beings in all their thoughts, feelings and activities. Many modern psychologists regard the concept of fluid intelligence, which is closely related to this deep semiotic system, as central to understanding cognitive abilities as manifested in intelligence tests and school performance.
The cardinal issue is not trying to prove the notion that all people have the same potential for higher order processing but finding out the cognitive constraints of fluid intelligence, deep language and natural language, where individual differences are to be expected. In the academic domain one would be specifically interested to know how intelligence (fluid and crystallized) and the deep semiotic system relate to CALP. I conclude with the realization that
‘we still do not understand very well how cognitive structures interact with each other and how their formation is affected by the structure of knowledge as it exists in our present educational and broader cultural environment … we also know that mental and school-specific knowledge structures are constrained by both internal and social constraint systems … we have already gathered firm knowledge about the developmental and cognitive preconditions under which learning may occur. However, we still need to learn a lot more about how learning situations work in the mind and/or the brain to alter its present state into a more advanced one’ (Demetriou et al., 1992; 6).
1. ‘The examinee is taught a series of rebus symbols (drawings) that are then combined into sentences that the examinee must translate. The subtest [unlike Cattell’s CFIT, R.G.] includes an extensive teaching process which precedes the actual testing phases’ (Brown, 1994: 89).
2. Some psychologists and educationists reject the CFIT (and intelligence tests in general) for the following reasons:
– The moral revulsion at the racial tensions that such measurements have occasioned.
– Political pressure from egalitarian circles such as Marxism and other pseudo-democratic movements that discourages investigations into the relationship between intelligence and heredity (Pearson, 1991). Nowadays, the tendency in these circles is to attribute learning problems solely to causes such as the clash of cultures or political/educational oppression (for example Bantu Education in South Africa) or economic exploitation (e.g. capitalism). There has been strong opposition to IQ tests in various parts of the world at different times (e.g. the Soviet era, America for many decades, and still on the increase, and in South Africa more and more so. In South Africa entrance tests to schools are now unconstitutional. At an ‘Academic Development Workshop’ held at Port Hare (22 August. 1995), Dr Carson Carr, Associate Dean of Academic Affairs, State University of New York, stated that in America, not only do they no longer speak about ‘intelligence’ and IQ, there is also a move to get rid of the A in SAT (Scholastic Aptitude Testing).
– The opposition of many psychologists to the purportedly simplistic (yet statistically complex) measurements of intelligence represented by an intelligence quotient (IQ).
– Some authors such as Wober (1975: 58) maintain that there are cultures that have difficulty with the general recognition of shapes. If Wober is right then these visual symbols (as they appear in Cattell’s tests) might not be culture-fair, and accordingly, an intelligence test such as Cattell’s CFIT should not be considered as a universal test of IQ. However, according to Jensen (1973:188), the shapes used in Cattell’s CFIT are universally applicable and the concepts tested are common to all societies. Oller (1981: 483) maintains that although the CFIT is a visual test, it may nevertheless be argued that the mental processes required to do the CFIT are universal. Thus 0ller agrees with Jensen and Cattell on the validity of the CFIT.
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