Refinement and test of the theory of fluid and crystallized general intelligences.

Horn, John L.; Cattell, Raymond B.

doi:10.1037/h0023816

Cited by 1,350 publications

(835 citation statements)

References 22 publications

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“…The Importanc. of this common source of individual differences to psychometric theory is shown by the fact that the concept of t has played a prominent part in several major psychometric theories of intelligence (e.g., Burt, 1940;Horn ~ Cattell, 1966;Huaphreys, 1962;Spearman, 1927;Vernon, 1971), and by the fact that the problems of inducing Structure are such good measures of g that they are found on an overwhelming majority of psychometric intelligence tests.…”

Section: Unities In Inductive Reasoningmentioning

confidence: 99%

Unities in inductive reasoning.

Sternberg¹,

Gardner²

1983

Journal of Experimental Psychology: General

224

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Three experiments sought to discover sources of communalities in performance on three inductive reasoning tasks: analogies, series completions, and classifications. In Experiment 1, 30 subjects completed an untuned pencil-and-paper test in Which they were asked to solve 90 induction items with names of mammals as content. Items were equally divided among the three kinds of induction tasks noted above. The subjects' task was to rank order four response options in terms of their goodness of fit as completions for each particular item. Data sets for the three tasks were highly intercorrelated, and a single exponential model of response choice provided a good fit to each data set. In Experiment 2,36 subjects completed a timed test in which they, too, were asked to solve 90 mammal-name induction items. Items were again equally divided among the three kinds of induction tasks noted above. The subjects' task was to choose the better of two response options as a completion for each particular item. Data sets for the three tasks were again highly intercorrelated, and a single linear model of response times provided a good fit to each data set. In Experiment 3, 18 subjects were timed while solving 1,440 induction items with schematic picture, verbal, and geometric content. Items were apprpximately equally divided among the three kinds of induction tasks noted above. Both analysis of stimulus and of subject variance supported the notion of highly related performance algorithms on the three tasks. It was concluded that a common or highly similar model of response choice and of information processing can account for at least some of the previously observed relationships in performance across induction tasks. The implications of these findings for psychometric and information-processing accounts of induction and intelligence are discussed.

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Section: Unities In Inductive Reasoningmentioning

confidence: 99%

Unities in inductive reasoning.

Sternberg¹,

Gardner²

1983

Journal of Experimental Psychology: General

224

View full text Add to dashboard Cite

show abstract

“…Following a well-established tradition of cognitive achievement being hierarchically organized in broad and narrow factors (see, e.g., Carroll, 1993;Gustafsson, 1988aGustafsson, , 1988bHorn & Cattell, 1966), a general factor as well as intermediate and more specific dimensions were hypothesized for the test of graphicacy as well as for the grades from the leaving certificate, and nested factor (NF) modeling was used. In an NF model, less general and narrower factors are nested under broader and more general ones (Gustafsson & Balke, 1993;Gustafsson & Undheim, 1996).…”

Section: Strategies For Analysesmentioning

confidence: 99%

What lies behind graphicacy? Relating students' results on a test of graphically represented quantitative information to formal academic achievement

Åberg‐Bengtsson

Ottosson

2005

J Res Sci Teach

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Based on studies carried out on qualitative data an instrument was constructed for investigating how larger numbers of students handle graphics. This test, consisting of 18 pages, each with its own graphic display(s) and a set of tasks, was distributed to 363 students, 15-16 years of age, from five different schools. The format of the questions varied, as did the format of the graphics. As students' performance was expected to be multidimensional, confirmatory factor analysis was carried out with a structural equation modeling technique. In addition to the identification of a general graphicacy-test factor (Gen) and an end-of-test effect (End 0 ), a narrative dimension (Narr 0 ) was vaguely indicated. This model was then related to a six-factor model of students' formal academic achievement measured by their leaving certificates from compulsory education. The strongest correlation obtained was between the general graphicacy-test dimension (Gen) and a mathematic/science factor (MathSc 0 ) in the grades model. In addition, substantial relationships were detected between the Gen factor and both an overall school achievement factor (SchAch) and a language factor (Lang 0 ) in the grades model. ß 2005 Wiley Periodicals, Inc. J Res Sci Teach 43: [43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62] 2006 Graphs, charts, cartograms, thematic maps, etc., are common tools for handling and communicating quantitative information in contemporary society. Successively, through their years of schooling, students encounter increasingly more advanced forms of graphic displays, both in direct educational situations and as illustrations and/or complementary facts on other subject matters. Students' access to modern computers equipped with graphic application software makes possible not only an abundance of graphics (sometimes unnecessarily elaborate) in magazines, newspapers, television, and electronic media-encountered in their everyday life both in and out of school-but also allows them to create these images. Thus, being ''graphicate''

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“…J. P. Guilford (1967) hypothesised three broad intelligence factors (i.e., operations, content, and products) defined by some 120 or more specific factors, each requiring a specific test. The seminal contributions of John Horn and R. B. Cattell (1966) describing crystallized (Gc) and fluid (Gf) intelligence were seen by some as paralleling the Verbal (VIQ) and Performance IQ (PIQ) scores of the Wechsler tests. More recently, multifaceted descriptions of intelligence include Sternberg's (1997) triarchic theory, Gardner's (1983, see also Gardner & Karnbaber & Wike, 1996 multiple intelligences, and the Naglieri-Das (Naglieri, 2009) PASS model (i.e., planning, attention, simultaneous, and successive/ sequential processing).…”

Section: Concurrent Development Of Theories Of Intelligence and Intelmentioning

confidence: 99%

Intelligence: Foundations and issues in assessment.

Gottfredson

Saklofske

2009

Canadian Psychology / Psychologie canadienne

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There is no more central topic in psychology than intelligence and intelligence testing. With a history as long as psychology itself, intelligence is the most studied and likely the best understood construct in psychology, albeit still with many "unknowns." The psychometric sophistication employed in creating intelligence tests is at the highest level. The authors provide an overview of the history, theory, and assessment of intelligence. Five questions are proposed and discussed that focus on key areas of confusion or misunderstanding associated with the measurement and assessment of intelligence. Keywords: intelligence, intelligence testing, intelligence testsTo understand how we are like all others, some others, and no others, to paraphrase Kluckhohn and Murray (1948), has led to the search for those key individual differences factors that can be operationally defined and measured. Individual differences characteristics attributed as the causes or underlying basis of human behaviour include intelligence, personality, and conative factors. Here, the view is that school achievement, job success, or longevity is, in turn, related to these latent traits. Thusly, school success is causally related to, or at least correlated, for example, with fluid intelligence, memory, and processing speed, on the one hand, and personality factors such openness to experience and conative factors such as motivation, on the other (Hilgard, 1980). And, if we know how these factors are distributed in the population, following, say, normal curve expectations, then future behaviours may be predicted using reliable and valid measures of these latent traits and, of course, the criterion measure as well. A Historical Note on Intelligence TestsDefining and measuring intelligence predates scientific psychology founded in the mid-19th century. Psychology provided the needed forum for the study of intelligence as a key individual differences factor. Although the elementary "brass instruments" tests created and used by Galton and James McKeen Cattell raised interest in the measurement of intelligence, it was the practical success of the Binet-Simon tests in France at the beginning of the 20th century and their adoption in the United States that propelled the study and measurement of intelligence into its current central position in both the discipline and practise of psychology (see Boake, 2002;Tulsky et al., 2003). Whipple stated in the preface to his 1914 book Manual of Mental and Physical Tests, One need not be a close observer to perceive how markedly the interest in mental tests has developed during the past few years. Not very long ago attention to tests was largely restricted to a few laboratory psychologists; now tests have become objects of the attention for many workers whose primary interest is in education, social service, medicine, industrial management and many other fields in which applied psychology promises valuable returns. (Whipple, 1914, p. v) The Army Alpha and Beta tests used extensively for screening U.S. military rec...

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Refinement and test of the theory of fluid and crystallized general intelligences.

Cited by 1,350 publications

References 22 publications

Unities in inductive reasoning.

Unities in inductive reasoning.

What lies behind graphicacy? Relating students' results on a test of graphically represented quantitative information to formal academic achievement

Intelligence: Foundations and issues in assessment.

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