Which of the following is the most widely accepted definition of intelligence?

Academic Intelligence

The concept of intelligence goes back to the Latin verb intellegere, meaning the acquirement, processing and storage of information. From this point of view, intelligence is restricted to the cognitive, mental abilities of the human being. Two thousand years later it still seems wise to reserve the term intelligence for what in the scientific literature is frequently called academic intelligence. This is defined as intellectual performance, within a closed system, on academic tasks or on academic problems that have fixed goals, a fixed structure, and known elements, and is distinguished from social, everyday, successful, or practical intelligence. We use the term intelligence here to mean academic intelligence.

Intelligence versus Competencies

The concepts of intelligence and competence are often applied as synonyms (Süß et al., 2005). Some distinctive features commonly accepted in the literature are the context-specificity of competence (Kanning, 2002; McFall, 1982) and the more general meaning of intelligence constructs across situations or contexts (Süß et al., 2005). Competence appears to be more subject to modification and learning (Rose-Krasnor, 1997), whereas intelligence is comparatively stable over time and seen as hereditary to a large extent (see Deary et al., 2006 for an overview). However, intelligence is often a necessary part of the evaluation of competence (Süß et al., 2005).

The Concept of Intelligence

A definition of the concept of intelligence is at once both controversial and complex. To emphasize here the points of disagreement would be self-defeating, for we cannot realistically evaluate the issues at hand if a consensus definition is circumvented. At the same time, some of the complexity must be preserved if we are going to do justice to the term and meaningfully test the limits of the concept of intelligence in the context of aphasia.

Sir Cyril Burt (1955) ascribed the origin of the concept of intelligence to Plato and Aristotle and credits Cicero with the coinage of the term. The use of tests to assess intelligence, as well as the application of statistics to these data, was introduced by an English scientist, Sir Francis Galton. Galton was interested in supporting the theories of his first cousin, Charles Darwin, by demonstrating that the principles of hereditary descent applied to intellectual as well as physical attributes. To this end he published his study Hereditary Genius in 1869 (Galton, 1887). But as Zangwill (1964) pointed out, the real work on the exploration and development of this concept began with the development of intelligence tests for the purpose of addressing socioeducational problems. This work was begun by Alfred Binet, a French lawyer and natural scientist by education, who became a psychologist largely through self-tutoring.

A different conception of the term intelligence is sometimes encountered among the general public, where it is taken to mean a state of above-normal thinking capacity. In scientific psychology, intelligence is conceived as a largely but not exclusively biologic characteristic that is expressed in behavior, which varies from one person to the next and accounts for some individual differences in behavior. Therefore, it is a quantitative concept, as are the concepts of height and weight. At the same time, there appears to be some naturally occurring upper limit to human intelligence, but this limit is not explicitly defined. Unlike height and weight, intelligence cannot be directly observed, touched, or measured in physical terms. It is more well defined and less arbitrary than such concepts as beauty and creativity. Also, the characteristics one looks at to assess intelligence in a subjective fashion are more consistent than, say, the characteristics that might be employed to assess “athleticism” in ping-pong players, football players, gymnasts, and runners.

A distinction is made by most authorities between the application of the concept of intelligence to represent one’s ability versus one’s actual performance. A highly intelligent individual could on some occasions perform poorly on an intelligence test for a variety of reasons, such as anxiety or preoccupation. Clearly one could fake a bad performance on an intelligence test, and obviously such an event would not in any real sense lower that person’s intellectual competence. Thus, this distinction between capacity and performance is crucial and something to be addressed later in this chapter.

Wechsler (1958) described general intellectual ability as the “global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment” (p. 7). Intellectual behavior or functional intelligence, he said, depends on general intellectual ability plus the way in which specific cognitive abilities are combined and such nonintellectual factors as the person’s drive and the incentive offered by the situation in which intelligence is being assessed.

Thus, intelligence is a construct that implies an underlying reality, but this reality must be inferred from behavioral observations (Wechsler, 1971). The parallel to this is a working definition of intelligence as a complex trait that is measured by intelligence tests (Wechsler, 1971). Because psychology has developed methods to determine whether a particular test is a measure of what we intend to call intelligence, the circularity of the working definition is no longer problematic. These methods derive from our current understanding of the structure of intelligence.

Introduction

In its modern, Western guise the concept of intelligence has seemed inextricably linked to the technology for measuring it, the Intelligence Quotient (IQ) test. Developed in its modern form in 1905 by the French psychologist Alfred Binet (1857–1911) and his collaborator Théodore Simon (1872–1961), the intelligence scale and the practices of measuring intelligence it spawned spread quickly to many parts of the world, including England, Spain, Germany, Latin America, and preeminently the United States. This new technology, however, did not resolve fundamental questions about the nature of intelligence, including a precise definition of what it was, whether it was a product of heredity or environment or both, and whether it was one thing or many. To this day, these issues continue to bedevil psychologists who study intelligence and to haunt many of the public debates about education and merit that rely, either explicitly or implicitly, on particular conceptions of intelligence. In general, one can say that in most current uses of the term, ‘intelligence’ refers to some sort of overall mental capacity, and one that particularly highlights reasoning, problem solving, and abstract thinking. Nonetheless, research across cultures and historical periods has shown that the specific characteristics attached to the notion of overall mental ability can vary greatly, as can the importance assigned to intelligence as an individual or group-level characteristic.

The direct antecedents of the word ‘intelligence’ lie in the Latin intelligentia or intellegentia meaning “the action or faculty of understanding,” itself derived from the Latin intellegere meaning ‘to understand.’ As one of the traditional divisions of the human soul (along with the emotions and the will), intelligence was a concept that had long been of importance to Western philosophers and theologians, especially in their attempts to differentiate human beings from other species in the animal world. Nonetheless, up to the eighteenth century it was not a word that evoked much interest on either side of the Atlantic, particular in its modern sense as a description of a person's overall mental capacity. Intelligence began to attract attention in the West as growing curiosity about the nature of human differences meshed with the turn to scientific methods as a privileged form of explanation. This article will explore some of that history and suggest how the development of the concept was intimately related to the particular cultural circumstances in which it was formulated and used.

Introduction

Das, Kirby, and Jarman (1975, 1979) and, based on that, Das, Naglieri, and Kirby (1994) formulated a theory of cognitive processing that has redefined intelligence in terms of four basic psychological processes: Planning, Attention, Simultaneous, and Successive (PASS) cognitive processes. Based on this theory, Naglieri and Das (1997) developed the Cognitive Assessment System (CAS), which has made a major contribution to diagnostic and clinical practice. Assessing children’s strengths and weaknesses on the basis of the PASS processes helps to explain an individual’s cognitive performance that relates to academic performance. Moreover, such an assessment provides essential information about an individual’s cognitive processes, which equips the teacher with specific knowledge about the (special) educational needs of a student, especially of a student with learning disabilities. Therefore, Das et al. (1994) have significantly contributed to the field of special education because the PASS theory provided the opportunity to focus more on individual differences. The information provided by the CAS may be particularly useful in the diagnostic process, for the identification of special educational needs, for the design of instructional programs, and for the development of specific interventions. Furthermore, the CAS is a valuable alternative for traditional IQ measures (Naglieri & Kaufman, 2001).

Traditionally, children with learning disabilities have been identified based on a significant discrepancy between intelligence and achievement that cannot be explained by mental age, educational opportunities, or sensory deficits (Sattler, 2002). For example, IQ tests are often used to estimate the assumed potential achievement level of children that is then compared with their actual achievement. A discrepancy between measured IQ score and achievement might indicate the presence of a learning disability. However, the use of general intelligence tests and the IQ-achievement discrepancy has been found to be lacking in validity for identification purposes and has been under attack for some time (e.g., Fletcher, 2012; Siegel, 1988; Vellutino, Scanlon, & Lyon, 2000). One reason for this critique is that tests of general intelligence have been shown to be insensitive to the specific problems experienced by children with learning disabilities (e.g., Naglieri, Salter, & Edwards, 2004; Siegel, 1988; Vellutino et al., 2000). Naglieri (2000), for example, explained that the general intelligence concept is not sensitive to the cognitive difficulties that children with reading disabilities experience. In his opinion, this is due to the fact that the concept does not measure the basic psychological processes related to reading failure (see also Naglieri & Bornstein, 2003; Naglieri et al., 2004). Furthermore, there is no evidence that children with reading disabilities who meet the IQ-achievement discrepancy criteria differ significantly in behavioral, cognitive, or achievement characteristics from children with reading disabilities who do not meet these criteria (Fletcher, 2012). A third reason is that content overlap between IQ tests and achievement tests frequently leads to slightly lower IQ scores in children with specific learning disabilities (Kroesbergen, Van Luit, & Naglieri, 2003).

The PASS theory is a cognitive processing approach to intelligence that regards ability as a multidimensional concept and, therefore, provides more information on specific components and processes compared to a general intelligence test (Das et al., 1994). In addition, the actual CAS test scores have been found to predict academic performance better than traditional measures of IQ (Naglieri, 2000; Naglieri & Das, 1997), a remarkable feat given that the CAS does not contain the verbal and achievement components found in the traditional IQ measures. Naglieri and Das (1997) describe how each of the four PASS processes is associated with specific types of academic achievement. The association between the PASS processes and academic achievement is taken as a starting point for the current review of relations between the PASS processes and specific learning disabilities.

In the past decade, research on cognitive profiles of children with learning disabilities has increased rapidly. In particular, theories about working memory and executive functioning have been used to explain individual differences in reading, mathematics, and other academic areas (e.g., see Berninger, Swanson, & Griffin, this volume; Geary, Hoard, Nugent, & Bailey, 2012; Wang & Gathercole, 2013). Working memory has been described as an active information processor responsible for storage and updating of information for a short period (Baddeley, 1996; see also Swanson in this volume). The concept of executive functions is used as an umbrella term for a number of higher-order cognitive functions such as planning, inhibition, and attentional shifting (e.g., Barry, Lyman, & Klinger, 2002; Miyake et al., 2000). Part of these executive functions can also be found in the CAS, especially in the scales of (1) Planning, defined as the processes to provide cognitive control, utilization of processes and knowledge, intentionality, and self-regulation to achieve a desired goal; (2) Attention, defined as the processes necessary for providing focused, selective cognitive activity over time; and (3) Successive Processing, defined as the processes by which the individual integrates stimuli into a specific serial order that forms a chain-like progression (Kroesbergen et al., 2003).

The different approach of the PASS theory to the concept of intelligence has led researchers to translate and adapt the CAS in different European countries, such as the Netherlands (Kroesbergen et al., 2003), Italy (Taddei, Contena, Caria, Venturini, & Venditti, 2011), and Cyprus (Papadopoulos, 2001; 2013). In this chapter, we provide an overview of several European studies1 that have investigated CAS profiles of children with special educational needs. Specifically, we discuss (1) mathematical learning disabilities, (2) nonverbal learning disabilities, (3) mild mental retardation, (4) giftedness, (5) attention deficits, and (6) the profiles of children from ethnic minorities. Because reading is discussed extensively in other chapters of this book, CAS profiles of children with reading disabilities are only briefly reviewed in the “Discussion” section. Finally, the implications of these studies for the use of the PASS theory are discussed.

Gardner’s Multiple Intelligences (MI)

The Gardner model is a core-curricula approach that employs the multidimensional concept of intelligence (Gardner, 1983). The eight types of intelligence are defined as (1) verbal/linguistic, (2) logical/mathematical, (3) visual/spatial, (4) musical/rhythmic, (5) bodily/kinesthetic, (6) interpersonal, (7) intrapersonal, and (8) naturalistic. The multiple-intelligences curricula model has been used as the base curriculum for the identification of individual differences and multidimensional evaluation.

1.2.3.5 Application layer

Based on the analysis results of the fusion and decision-making layers, the application layer deeply integrates the concept of intelligence into various business areas of the metro. The subsystems not only include the existing electromechanical equipment monitoring system and passenger service system but also incorporate functions of the smart metro station system, such as state perception, automatic operation, intelligent diagnosis, and self-evolution. Overall, it can be divided into three aspects: smart operation, smart maintenance, and smart service.

Smart operation

Smart operation is oriented to passenger transport business and integrates the station equipment production system and operation management system. On the basis of integrated monitoring, the station business data is effectively organized. It includes environmental monitoring, energy management, smart water, smart fire, smart security, and so on.

Smart maintenance

Smart maintenance is oriented to equipment. It establishes an all-life cycle monitoring and management system for equipment perception and fault warning, including four modules: personnel management, equipment management, individual soldiers, and user unification.

Smart service

Smart service is oriented to passengers, which is to improve the passengers’ travel experience from the aspects of information service, intelligent guidance, and advanced customer service. Smart service can grasp the passenger flow situation of entrances and exits, station halls, and platforms in real time through the cellphone sniffing system and timely guide passengers, especially in the case of sudden large passenger flow. Through the real-time display of train congestion, passengers can choose a more spacious compartment actively. At the same time, the smart station will interact with the line network data center, take corresponding passenger flow control measures, and provide solutions that require less transfer and can make travel more comfortable and more timesaving.

Two Kinds of Giftedness

A second issue that must be dealt with is that our present efforts to define giftedness are based on a long history of previous studies dealing with human abilities. Most of these studies focused mainly on the concept of intelligence and are briefly discussed here to establish an important point about the process of defining concepts rather than any attempt to equate intelligence with giftedness. Although a detailed review of these studies is beyond the scope of the present chapter, a few of the general conclusions from earlier research are necessary to set the stage for this analysis.1

The first conclusion is that intelligence is not a unitary concept, but rather there are many kinds of intelligence and therefore single definitions cannot be used to explain this complicated concept. The confusion and inconclusiveness about present theories of intelligence have led Sternberg (1984) and others to develop new models for explaining this complicated concept. Sternberg's ‘triarchic’ theory of human intelligence consists of three subtheories: a contextual subtheory, which relates intelligence to the external world of the individual; a two-facet subtheory, which relates intelligence to both the external and internal worlds of the individual; and a componential subtheory, which relates intelligence to the internal world of the individual. The contextual subtheory defines intelligent behavior in terms of purposive adaptation to, selection of, and shaping of real-world environments relevant to one's life. The two-facet subtheory further constrains this definition by regarding as most relevant to the demonstration of intelligence contextually intelligent behavior that involves adaptation to novelty or automatization of information processing, or both. The componential subtheory specifies the mental mechanisms responsible for the learning, planning, execution, and evaluation of intelligent behavior.

In view of this work and numerous earlier cautions about the dangers of trying to describe intelligence through the use of single scores, it seems safe to conclude that this practice has been and always will be questionable. At the very least, attributes of intelligent behavior must be considered within the context of cultural and situational factors. Indeed, some examinations have concluded that “(t)he concept of intelligence cannot be explicitly defined, not only because of the nature of intelligence but also because of the nature of concepts” (Neisser, 1979, p. 179).

A second conclusion is that there is no ideal way to measure intelligence, and therefore we must avoid the typical practice of believing that if we know a person's IQ score, we also know his or her intelligence. Even Terman warned against total reliance on tests: “We must guard against defining intelligence solely in terms of ability to pass the tests of a given intelligence scale” (1921, p. 131). E. L. Thorndike echoed Terman's concern by stating, “to assume that we have measured some general power which resides in (the person being tested) and determines his ability in every variety of intellectual task in its entirety is to fly directly in the face of all that is known about the organization of the intellect” (Thorndike, 1921 p. 126,).

The reason I have cited these concerns about the historical difficulty of defining and measuring intelligence is to highlight the even larger problem of isolating a unitary definition of giftedness. At the very least we will always have several conceptions (and therefore definitions) of giftedness; but it will help in this analysis to begin by examining two broad categories that have been dealt with in the research literature. I will refer to the first category as ‘school-house giftedness’ and to the second as ‘innovative giftedness’. Before going on to describe each type, I want to emphasize that:

Both types are important.

There is usually an interaction between the two types.

Special programs should make appropriate provisions for encouraging both types of giftedness as well as the numerous occasions when the two types interact with each other.

Thinking Processes

The decisive event in modern psychological analyses of creativity was the acceptance speech in 1949 of the – at that time new – President of the American Psychological Association, J. P. Guilford. In a nutshell, he complained that existing concepts of intelligence visualized it as the finding of single correct answers to circumscribed problems. By contrast, he argued that intellectual power could also be applied to the finding of substantial numbers of new, original and unexpected answers, quite possibly to loosely defined problems. He referred to this process as a special kind of thinking, which he labeled ‘divergent.’ Guilford's original paper had the title ‘creativity,’ and the equating of creativity with divergent thinking quickly established itself, especially after the Sputnik shock already mentioned. Other researchers have also concentrated on thinking processes as the basis for creativity. A well-known popular scientific approach emphasized ‘lateral’ thinking. Other concepts are ‘janusian’ thinking (named after the Roman god Janus, who could look backwards and forwards at the same time), ‘homospatial’ thinking (ideas from different domains are brought together into the same space), ‘biphasic’ thinking (in the first phase uninhibited combinations of ideas, which are then organized and sorted out in the second phase, for instance according to social acceptability), and ‘tertiary’ thinking (in the psychoanalytic sense, primary process and secondary process thinking are combined).

Associational theories emphasize the process of linking ideas. The theory of ‘remote associates’ is based on the observation that, in the course of their experiences, people learn a number of responses to a particular stimulus. Some of the stimulus-response associations occur frequently, others seldom. As a result, people learn a hierarchy of associations. Pairings that occurred frequently in the past stand high in the hierarchy, and have a higher probability of being chosen when the stimulus occurs again than associations which occurred infrequently in the past. These less likely associations are ‘remote’ and the person who makes them produces unusual or unexpected ideas. A similar approach is seen in the theory of ‘bisociation,’ which assumes that ideas occur in ‘matrices’ or fields. Normally, ideas from the same field are combined in a process of association. However, some people combine ideas from separate matrices in a process of bisociation which, by virtue of the fact that the ideas are not normally found together, means that the combination is surprising.

Consequences

In retrospect, it seems clear that Thurstone's approach was actually a step backward compared to that of Spearman. One reason why Thurstone, Cattell, Eysenck, Guilford, and numerous other psychometricians gave widely differing answers to Spearman's question—what do we mean when we say we “measure intelligence”?—was that they could not even agree on the number of intelligence factors. Yet, whatever the phrase meant, both Spearman and elementary logic tell us that it cannot possibly refer to a multidimensional concept of intelligence. Only unidimensional variables can be “measured” in the sense that exactly one real number is assigned to each subject so that, at a minimum, the empirical order relations (implied by statements of the type “A is more intelligent than B”) are preserved. If there were two different intelligences, then all such statements would have to be qualified with a reference to the particular intelligence that is being measured.

In hindsight, it is not surprising that the Thurstone era of exploratory factor analysis, imposing as it seemed at the time, left few empirical imprints still remembered today. Where Spearman had set himself a clearly defined substantive problem, Thurstone promised a research technique uncommitted to any particular subject area, a technique that, moreover, could never fail. No correlation matrix can ever falsify what amounted to a tautological claim that a given number of observed variables can be reasonably well approximated by a smaller number of common factors. Statistical tests of the simple structure hypothesis, although available, were carefully avoided.

Although Thurstone's empirical results are virtually forgotten today, his gospel of a research automaton capable of dispensing scientific progress without requiring any ingenuity, technical skill, or even familiarity with a substantive area proved hugely popular and subsequently resurfaced in various statistical disguises.