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The Theory of Successful Intelligence as a Basis for Gifted Education

Sternberg, Robert J., Grigorenko, Elena L.·2002·Gifted Child Quarterly
DOI 10.1177/001698620204600403
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Abstract

A number of models are available for use in gifted education. The theory of successful intelligence, one such model, provides a basis for identification, intervention, and evaluation in gifted programs. This article describes the model, allowing practitioners and other interested parties to apply the model in a gifted education environment. The article contains four main parts. The first part presents the theory of successful intelligence and data in support of it. The second part shows how to implement the model in schools and presents data in support of the success of its school implementation. The third part relates the theory of successful intelligence to other models of gifted education. The fourth part briefly draws some conclusions.

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Crossref · 10.1177/001698620204600403

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  • Validation results of the CANAL-F test did not significantly outperform the MLAT in predictive validity.

    “validation results of the CANAL-F test, as obtained in their empirical studies, did not significantly outperform the MLAT in predictive validity (Sternberg & Grigorenko 2002).”

    From Foreign language aptitude theory: Yesterday, today and tomorrow (2017) · cites this paper as Sternberg & Grigorenko 2002

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 45

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  15. Renzulli, J. S., 1984, Conceptions of giftedness, 53
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  39. Sternberg, R. J., 2001, Educational Leadership, 58, 48
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Metadata

Authors
Sternberg, R. J., & Grigorenko, E. L.
Affiliations
  • Yale University
  • Yale University and Moscow State University
Venue
Gifted Child Quarterly
Publisher
SAGE Publications
Published
2002-10
Volume
46
Issue
4
Pages
265-277
ISSN
  • 0016-9862
  • 1934-9041
DOI
10.1177/001698620204600403
Cited by
55
References
0
Language
en
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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