Wherefore Art Thou, Multiple Intelligences? Alternative Assessments for Identifying Talent in Ethnically Diverse and Low Income Students

Plucker, Jonathan A.; Callahan, Carolyn M.; Tomchin, Ellen M.

doi:10.1177/001698629604000205

Cited by 57 publications

(74 citation statements)

References 33 publications

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“…There is some evidence to suggest, however, that they are of acceptable reliability (Plucker, Callahan, & Tomchin, 1996). Without demonstrably valid tests, however, it is difficult to evaluate the success of interventions.…”

Section: Second Wave: Domain-specific Modelsmentioning

confidence: 99%

Conceptions of Giftedness

Kaufman¹,

Sternberg²

2008

Handbook of Giftedness in Children

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Johnny, a 9-year-old elementary school student, has an IQ of 140, which would qualify him as "gifted" by virtually any IQ-based definition of giftedness anyone might use. Johnny has few friends, in large part because he has very poor social skills. Johnny has no hobbies to speak of, and is unengaged in significant extracurricular activities outside of school. And despite his IQ, Johnny is a good, but not great, student.Davy is also 9 and is in the same school as Johnny. He has an IQ of 120, which would quality him as "gifted" by some, but not other IQ-based definitions of giftedness. Davy is very active in sports and is the best soccer player of any age in his school. He also is a highly talented trombonist, and is first trombone in the elementary-school orchestra. His teacher believes he has the potential for a career in musical performance, should he wish to follow that path. Davy is very popular and is one of the top three academic performers in his class.Who is gifted? Johnny? Davy? Both? Or neither? In answering this question, four things must be kept in mind.First, "giftedness" is a label-nothing more. We are frequently asked whether such-and-such or so-and-so child is gifted. The answer depends on the criteria one sets. But there is no one absolute or "correct" set of criteria. Criteria for such labeling are a matter of opinion, nothing more, and there are many disagreements as to how the label should be applied.Second, the label can be applied in either a more general or a more specific way. The more general way implies that giftedness is relatively general across many domains-that is, someone is either gifted or not. On this view, someone who is gifted is gifted very broadly. The more specific way implies that giftedness is something that is potentially limited to one or several narrow domains-for example, verbal skills; or within the verbal domain, writing skills; or within the writing domain, fiction-writing skills. Indeed, relatively few successful fiction writers are also successful nonfiction writers, and vice versa.

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Section: Second Wave: Domain-specific Modelsmentioning

confidence: 99%

Conceptions of Giftedness

Kaufman¹,

Sternberg²

2008

Handbook of Giftedness in Children

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“…Even though assessments exist to test Gardner's various intelligences (e.g., Gardner et al 1998), these assessments have not been associated with high levels of psychometric validity, and the evidence regarding reliability of these and similar measures is mixed (e.g., Plucker 2000;Plucker et al 1996;Visser et al 2006). (p. 814) It is interesting to compare the treatment Jensen and Gardner received from the scientific establishment for their respective work.…”

Section: A Double Standard Applied To Researchers Who Defend Hypothesmentioning

confidence: 99%

Science Is Not Always “Self-Correcting”

Cofnas

2015

Found Sci

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Some prominent scientists and philosophers have stated openly that moral and political considerations should influence whether we accept or promulgate scientific theories. This widespread view has significantly influenced the development, and public perception, of intelligence research. Theories related to group differences in intelligence are often rejected a priori on explicitly moral grounds. Thus the idea, frequently expressed by commentators on science, that science is "self-correcting"-that hypotheses are simply abandoned when they are undermined by empirical evidence-may not be correct in all contexts. In this paper, documentation spanning from the early 1970s to the present is collected, which reveals the influence of scientists' moral and political commitments on the study of intelligence. It is suggested that misrepresenting findings in science to achieve desirable social goals will ultimately harm both science and society.

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“…The aim of these studies was to confirm the presence of different types of intelligence in a battery of activities derived from Project Spectrum. Plucker, Callahan, and Tomchin (1996) performed exploratory factor analysis in order to test the existence of four types of intelligence -spatial, logical/mathematical, linguistic and interpersonal -in a sample of 1813 children in kindergarten and first grade, using the Multiple Intelligences Assessment Technique, which is based upon the assessment activities used in Project Spectrum (Gardner et al, 1998). The technique consisted of 13 performance-based activities, teacher ratings, and observational checklists corresponding to the four intelligences.…”

mentioning

confidence: 99%

“…Although these factor analysis results appear to provide some support for the theory of multiple intelligences, they are limited by the fact that they were obtained using exploratory factor analysis, rather than CFA, a much better procedure to study this issue. Pyryt (2000) reanalyzed the correlation matrix of Plucker et al (1996) to illustrate how higher-order exploratory factor analysis using more adequate procedures -maximum likelihood and direct oblimin -might be used to explain the constructs found in the initial factor analysis. Consistent with Carroll's (1993) factor analysis study of mental abilities, results indicated that the g factor underlies correlations between first-order factors.…”

mentioning

confidence: 99%

“…Consistent with Carroll's (1993) factor analysis study of mental abilities, results indicated that the g factor underlies correlations between first-order factors. Gridley (2002) reanalyzed data from Plucker et al (1996) to illustrate how the use of CFA might help to determine the factorial structure that fits these empirical data. The findings obtained by Gridley (2002) showed that a model with several correlated factors fitted the data from Plucker et al (1996) better than did a hierarchical model with g at the top.…”

mentioning

confidence: 99%

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