The Great Debate: General Ability and Specific Abilities in the Prediction of Important Outcomes
There are many different theories of intelligence. Although these theories differ in their nuances, nearly all agree that there are multiple cognitive abilities and that they differ in the breadth of content they are typically associated with. There is much less agreement about the relative importan...
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Format: | Electronic Book Chapter |
Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2019
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Lang, Jonas |4 auth | |
700 | 1 | |a Kell, Harrison J. |4 auth | |
245 | 1 | 0 | |a The Great Debate: General Ability and Specific Abilities in the Prediction of Important Outcomes |
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520 | |a There are many different theories of intelligence. Although these theories differ in their nuances, nearly all agree that there are multiple cognitive abilities and that they differ in the breadth of content they are typically associated with. There is much less agreement about the relative importance of cognitive abilities of differing generality for predicting important real-world outcomes, such as educational achievement, career success, job performance, and health. Some investigators believe that narrower abilities hold little predictive power once general abilities have been accounted for. Other investigators contend that specific abilities are often as-or even more-effective in forecasting many practical variables as general abilities. These disagreements often turn on differences of theory and methodology that are both subtle and complex. The five cutting-edge contributions in this volume, both empirical and theoretical, advance the conversation in this vigorous, and highly important, scientific debate. | ||
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650 | 7 | |a Psychology |2 bicssc | |
653 | |a general cognitive ability | ||
653 | |a second stratum abilities | ||
653 | |a narrow abilities | ||
653 | |a cognitive abilities | ||
653 | |a ability tilt | ||
653 | |a identification | ||
653 | |a occupational attainment | ||
653 | |a scholastic performance | ||
653 | |a longevity | ||
653 | |a non-g residuals | ||
653 | |a specific abilities | ||
653 | |a higher-order factor model | ||
653 | |a bifactor model | ||
653 | |a intelligence | ||
653 | |a general intelligence (g) | ||
653 | |a specific factors | ||
653 | |a academic achievement | ||
653 | |a hierarchical factor model | ||
653 | |a educational attainment | ||
653 | |a nested-factor models | ||
653 | |a ability differentiation | ||
653 | |a general abilities | ||
653 | |a relative importance | ||
653 | |a relative importance analysis | ||
653 | |a bifactor(S-1) model | ||
653 | |a subscores | ||
653 | |a g-factor | ||
653 | |a school grades | ||
653 | |a non-g factors | ||
653 | |a nested-factors model | ||
653 | |a general mental ability | ||
653 | |a cognitive tests | ||
653 | |a specific cognitive abilities | ||
653 | |a curvilinear relations | ||
653 | |a specific ability | ||
653 | |a situational specificity | ||
653 | |a predictor-criterion bandwidth alignment | ||
653 | |a job performance | ||
653 | |a health | ||
653 | |a machine learning | ||
653 | |a academic performance | ||
653 | |a general factor | ||
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856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/48877 |7 0 |z DOAB: description of the publication |