Why are cognitive abilities of children so different across countries? The link between major socioeconomic factors and PISA test scores

Burhan, Nik Ahmad Sufian; Yunus, Melor Md; Tovar, María Elena Labastida; Burhan, Nik Mohd Ghazi

doi:10.1016/j.paid.2016.09.043

Cited by 20 publications

(13 citation statements)

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“…Paternal and maternal schooling levels were the socio-economic and socio-cultural family variables which more accurately predict 2009 SIMCE outcomes as well as the results of intelligence testing in 2010 5ESG and 1HSG, respectively. This reflects the widely acknowledged opinion that intelligence is the best predictor of SA, as shown in this study, since brighter parents attain higher levels of education, occupy better-paying jobs and form families with higher incomes [7,11–14,17,20]. It has been described that children from less advantaged families were up to twice as likely to be in the lowest quintile of mathematics and literacy scores.…”

Section: Discussionsupporting

confidence: 82%

“…Educational inequalities result from the extent to which students with different socio-cultural origins have unequal probabilities of attaining satisfactory SA levels; as a consequence, cognitive abilities of children are very different across countries [17–19]. Other authors have proposed that variables related to the family’s socio-economic status (SES) such as paternal schooling, and in particular maternal schooling, are consistent in explaining child SA, intelligence, and nutritional status, probably because mothers are the main source of intellectual stimulation and enrichment in the psycho-social environment and the health-related behaviour of the family [4,5,7,11,12,20–24].…”

Section: Introductionmentioning

confidence: 99%

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A multifactorial approach of nutritional, intellectual, brain development, cardiovascular risk, socio-economic, demographic and educational variables affecting the scholastic achievement in Chilean students: An eight- year follow-up study

et al. 2019

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The aim of this study was to quantitate the relative impact of nutritional, intellectual, brain development, cardiovascular risk, socio-economic, demographic and educational variables on the results of the 2009 Quality Education Measurement System (SIMCE) tests of language and mathematics for scholastic achievement (SA) applying a multifactorial approach, in school-age children of the 2010 5 th elementary school grade (5ESG) and of the 1 st grade of high school (1HSG). The purposes were: i) to test the hypothesis that intellectual ability, the level of SA of the educational establishments in the 2009 SIMCE tests, sex, parental schooling levels, and head circumference-for-age Z-score are the most relevant parameters associated with 2009 SIMCE outcomes; ii) to determine the predictive ability of the 2009 SIMCE results in determining the 2013 SIMCE outcomes for the 2010 5ESG cohort (when they graduated from elementary school, 8 th grade) and for determining the 2013 University Selection Test (PSU) outcomes for the 2010 1HSG group (for university admission, when they graduated from high school, 4 th grade); iii) to determine the association between the 2009 SIMCE results with the 2017 PSU outcomes for the 2010 5ESG group (for university admission, when they graduated from high school, 4 th grade). A representative, proportional and stratified sample of 33 schools of the Metropolitan Region of Chile was randomly chosen. In these schools, 1,353 school-age children of both sexes, of the 2010 5ESG (n = 682; mean age = 10.8 years, SD = 0.6) and of the 2010 1HSG (n = 671; mean age = 14.8 years, SD = 0.6) participated. In both grades and tests, the findings confirm the hypotheses formulated. 2009 SIMCE outcomes were positively and significantly associated with 2013 SIMCE and with 2017 PSU and, with 2013 PSU outcomes in school-age children from 2010 5ESG and 1HSG, respectively. These findings may be useful for educational and health planning in Chile and countries in a comparable stage of development.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

A multifactorial approach of nutritional, intellectual, brain development, cardiovascular risk, socio-economic, demographic and educational variables affecting the scholastic achievement in Chilean students: An eight- year follow-up study

et al. 2019

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“…However, we did not find that maternal employment status to be significantly associated with the children’s VMI performance. Although employment status, together with educational status and household income are contributors to the well-being and development of young children [ 58 ], the effects of maternal employment on child outcomes are inconclusive, as employment does not necessarily cause reduced mother-child time and not all types of parental time directly benefit child development [ 59 ]. In addition, all of the children involved in this study had fathers who were formally employed.…”

Section: Discussionmentioning

confidence: 99%

Association between reduced visual-motor integration performance and socioeconomic factors among preschool children in Malaysia: A cross-sectional study

et al. 2021

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Visual-motor integration (VMI) is related to children’s academic performance and school readiness. VMI scores measured using the Beery-Bucktenicka Developmental Test of Visual-Motor Integration (Beery-VMI) can differ due to differences in cultural and socioeconomic backgrounds. This study compared the VMI scores of Malaysian preschoolers with the corresponding US norms and determined the association between their VMI scores and socioeconomic factors. A cross-sectional study was conducted among 435 preschoolers (mean age: 5.95±0.47 years; age range: 5.08–6.83 years) from randomly selected public and private preschools. VMI scores were measured using Beery-VMI in the preschools’ classrooms. Information on the socioeconomic characteristics of the preschoolers was obtained using a parent-report questionnaire. One sample t-test was used to compare their VMI scores with the corresponding US norms. Multivariate logistic regression models were used to explore the influence of socioeconomic factors on the preschoolers’ VMI scores. Overall, Malaysian preschoolers’ VMI performance was similar to the US standardized norms (p>0.05). Children from low-income families were twice likely to obtain lower than average VMI scores than those from higher-income families (OR = 2.47, 95%CI 1.05, 5.86). Children enrolled at public preschools were more likely to obtain a lower than average VMI score than those who enrolled at private preschools (OR = 2.60, 95%CI 1.12, 6.06). Children who started preschool at the age of six were more likely to obtain lower than average VMI scores than those who started at an earlier age (OR = 4.66, 95%CI 1.97, 11.04). Low maternal education level was also associated with lower than average VMI score (OR = 2.60, 95%CI 1.12, 6.06). Malaysian preschoolers’ Beery-VMI performance compared well to their US counterparts. Some socioeconomic factors were associated with reduced VMI scores. Those from disadvantaged socioeconomic backgrounds are more likely to have reduced VMI performance, potentially adversely affecting their school readiness, cognitive performance, and future academic achievements.

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“…Rindermann ( 2006 , 2007 , p. 687) concludes there is a strong ‘ g ’-factor, that is the general intelligence factor, in international student assessments, including PISA. Burhan et al’s ( 2017 ) measure of adolescents’ cognitive ability was their PISA test scores. Direct evidence at the individual student level is from the German PISA 2000 study in which students undertaking PISA also sat German cognitive ability tests.…”

Section: Methodsmentioning

confidence: 99%

Do the labour market returns to university degrees differ between high and low achieving youth? Evidence from Australia

Marks

2018

J Labour Market Res

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In almost all developed countries there has been substantial growth in university education over the last half-century. This growth has raised concerns that the benefits of university education are declining and that university education is not appropriate for students who, without the expansion, would not have been admitted. For such students, vocational education or direct entry to the labour market may be more appropriate. The purpose of this study is to examine the effects of university and vocational qualifications, net of other influences on a variety of labour market outcomes for Australian youths up to age 25; and if the benefits of university degrees differ across the achievement continuum. Achievement is measured by test scores in the OECD’s PISA assessments. The six labour market outcomes investigated are: occupational status, hourly and weekly earnings, employment, unemployment and full-time work. The study finds that university degrees provide substantially superior labour market outcomes which are not confined to high and average achievers, at least for this cohort in their formative years in the labour market.

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Why are cognitive abilities of children so different across countries? The link between major socioeconomic factors and PISA test scores

Cited by 20 publications

References 135 publications

A multifactorial approach of nutritional, intellectual, brain development, cardiovascular risk, socio-economic, demographic and educational variables affecting the scholastic achievement in Chilean students: An eight- year follow-up study

A multifactorial approach of nutritional, intellectual, brain development, cardiovascular risk, socio-economic, demographic and educational variables affecting the scholastic achievement in Chilean students: An eight- year follow-up study

Association between reduced visual-motor integration performance and socioeconomic factors among preschool children in Malaysia: A cross-sectional study

Do the labour market returns to university degrees differ between high and low achieving youth? Evidence from Australia

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