Getting through grade 2: Predicting children's early school achievement in rural South African schools

C Liddell, J Lycett, Gordon Rae

    Research output: Contribution to journalArticle

    6 Citations (Scopus)

    Abstract

    Children in the second-grade classrooms of three rural schools (n = 150) completed a variety of psychometric and curriculum-based tests, and were rated by their teachers and parents on dimensions of their everyday behaviour; demographic data (e.g. socioeconomic status, presence of mother in the home) and biographical information (e.g. gender, age, birth order) were also collected for each child. Some of these data (e.g. child's age and gender) were more cost-efficient to collect than others (e.g. parent ratings). Measures were evaluated in terms of their salience for constructing a multivariate model that would predict subsequent grade 2 outcome, with the most cost-effective variables being inserted first. In this way, both the cost-efficiency and predictive power of independent variables (IVs) were taken into consideration when attempting to build a predictive model. A model containing three IVs (scores on curriculum-based tests, teacher ratings of children's attention span, and teacher ratings of helpfulness) ultimately predicted 51% of the variance in grade 2 outcome. These results demonstrate, first, that it is possible to build a relatively strong predictive model of grade 2 outcome, although not based on variables that are cheap and quick to measure. Second, that doing well in grade 2 is not so much a matter of having well-developed, broad-ranging psychometric abilities, but more a matter of mastering elements of the curriculum and behaving in ways that permit adaptation to the requirements of crowded and under-resourced African classrooms.
    LanguageEnglish
    Pages331-348
    JournalInternational Journal of Behavioral Development
    Volume21
    Issue number2
    Publication statusPublished - Jun 1997

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    school grade
    teacher rating
    predictive model
    curriculum
    psychometrics
    school
    parents
    costs
    classroom
    birth order
    rural school
    gender
    social status
    rating
    efficiency
    ability
    teacher

    Cite this

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    abstract = "Children in the second-grade classrooms of three rural schools (n = 150) completed a variety of psychometric and curriculum-based tests, and were rated by their teachers and parents on dimensions of their everyday behaviour; demographic data (e.g. socioeconomic status, presence of mother in the home) and biographical information (e.g. gender, age, birth order) were also collected for each child. Some of these data (e.g. child's age and gender) were more cost-efficient to collect than others (e.g. parent ratings). Measures were evaluated in terms of their salience for constructing a multivariate model that would predict subsequent grade 2 outcome, with the most cost-effective variables being inserted first. In this way, both the cost-efficiency and predictive power of independent variables (IVs) were taken into consideration when attempting to build a predictive model. A model containing three IVs (scores on curriculum-based tests, teacher ratings of children's attention span, and teacher ratings of helpfulness) ultimately predicted 51{\%} of the variance in grade 2 outcome. These results demonstrate, first, that it is possible to build a relatively strong predictive model of grade 2 outcome, although not based on variables that are cheap and quick to measure. Second, that doing well in grade 2 is not so much a matter of having well-developed, broad-ranging psychometric abilities, but more a matter of mastering elements of the curriculum and behaving in ways that permit adaptation to the requirements of crowded and under-resourced African classrooms.",
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    Getting through grade 2: Predicting children's early school achievement in rural South African schools. / Liddell, C; Lycett, J; Rae, Gordon.

    In: International Journal of Behavioral Development, Vol. 21, No. 2, 06.1997, p. 331-348.

    Research output: Contribution to journalArticle

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