High Ability and Learner Characteristics

Abstract

The outstandingly able learner has been conceptualised, in terms of test and examination performance, as the learner showing superior academic performance which is markedly better than that of peers and in ways regarded as of value by wider society. In Kuwait, such superior examination performance leads to a classification regarded as being ‘gifted’. This study looks at the inter-correlations between performance in various subjects in examinations and then considers how examination performance correlates with measures of working memory capacity, extent of field dependency, extent of divergency and visual-spatial abilities. A very large sample of grade 7 Kuwaiti students (aged ~13) was involved, the sample being selected in such a way that it contained a high proportion of those regarded as ‘gifted’ under the procedures used in Kuwait. While specific learner characteristics have been related to examination performance, this study brings four different characteristics together to gain a picture of the way these characteristics may be seen in those who perform extremely well in examinations. Principal components analysis using varimax rotation, was used to look at the examination data and one factor accounted for 87% of the variance. A consideration of the examination papers led to the conclusion that the national examinations tested only recall-recognition. It was also found that those who performed best in all six subjects tended to be those who are highly divergent and strongly visual-spatial as well as those tending to have higher working memory capacities and being more field independent. The inter-correlations between the various learner characteristics are explained in terms of the way the brain is known to process information. The implications of the findings for assessment and for the way high ability is considered are discussed

Keywords

• Giftedness, High Academic Ability, Learner Characteristics, Learning, Kuwait

High Ability and Learner Characteristics

Abstract

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Keywords

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