Hostname: page-component-76fb5796d-zzh7m Total loading time: 0 Render date: 2024-04-26T08:04:48.078Z Has data issue: false hasContentIssue false

COGNITIVE ABILITY OF PRESCHOOL, PRIMARY AND SECONDARY SCHOOL CHILDREN IN COSTA RICA

Published online by Cambridge University Press:  06 March 2014

HEINER RINDERMANN*
Affiliation:
Department of Psychology, Chemnitz University of Technology, Germany
EVA-MARIA STIEGMAIER
Affiliation:
Clinical and Health Psychologist, Zeltweg, Austria
GERHARD MEISENBERG
Affiliation:
Ross University Medical School, Dominica
*
1Corresponding author. Email: heiner.rindermann@psychologie.tu-chemnitz.de

Summary

Cognitive abilities of children in Costa Rica and Austria were compared using three age groups (N=385/366). Cognitive ability tests (mental speed, culture reduced/fluid intelligence, literacy/crystallized intelligence) were applied that differed in the extent to which they refer to school-related knowledge. Preschool children (kindergarten, 5–6 years old, NCR=80, NAu=51) were assessed with the Coloured Progressive Matrices (CPM), primary school children (4th grade, 9–11 years old, NCR=71, NAu=71) with ZVT (a trail-making test), Standard Progressive Matrices (SPM) and items from PIRLS-Reading and TIMSS-Mathematics, and secondary school students (15–16 years old, NCR=48, NAu=48) with ZVT, Advanced Progressive Matrices (APM) and items from PISA-Reading and PISA-Mathematics. Additionally, parents and pupils were given questionnaires covering family characteristics and instruction. Average cognitive abilities were higher in Austria (Greenwich-IQ MCR=87 and MAu=99, dIQ=12 points) and differences were smaller in preschool than in secondary school (dIQ=7 vs 20 points). Differences in crystallized intelligence were larger than in fluid intelligence (mental speed: dIQ=12, Raven: dIQ=10, student achievement tests: dIQ=17 IQ points). Differences were larger in comparisons at the level of g-factors. Austrian children were also taller (6.80 cm, d=1.07 SD), but had lower body mass index (BMICR=19.35 vs BMIAu=17.59, d=−0.89 SD). Different causal hypotheses explaining these differences are compared.

Type
Articles
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdallah, S., Michaelson, J., Shah, S., Stoll, L. & Marks, N. (2012) Happy Planet Index: 2012 Report. New Economics Foundation (NEF), London.Google Scholar
Arum, R. & Roksa, J. (2011) Academically Adrift: Limited Learning on College Campuses. University of Chicago Press, Chicago.Google Scholar
Barro, R. J. & Lee, J-W. (2009) Barro-Lee Data Set. URL: from www.barrolee.com (accessed 18th December 2012).Google Scholar
Batterjee, A. (2011) Intelligence and education: the Saudi case. Mankind Quarterly 52, 133190.Google Scholar
Bishop, J. H. (1989) Is the test score decline responsible for the productivity growth decline? American Economic Review 79, 178197.Google Scholar
Chen, H-Y., Liao, Y-K., Chen, Y-H., Chen, H-P. & Lynn, R. (2013) Two studies of recent increases of intelligence in Taiwan. Mankind Quarterly LIII, 348357.Google Scholar
Christainsen, G. B. (2013) IQ and the wealth of nations: how much reverse causality? Intelligence 41, 688698.Google Scholar
CINDE (Costa Rican Investment Promotion Agency) (2011) Education Overview. San José. URL: www.cinde.org/attachments/069_028_Education%20Overview%202009.pdf (accessed 4th January 2013).Google Scholar
Colom, R., Flores-Mendoza, C. & Abad, F. J. (2007) Generational changes on the Draw-a-Man Test: a comparison of Brazilian urban and rural children tested in 1930, 2002 and 2004. Journal of Biosocial Science 39, 7989.Google Scholar
Coyle, Th. R. & Rindermann, H. (2013) Spearman's Law of Diminishing Returns and national ability. Personality and Individual Differences 55, 406410.Google Scholar
DESA (UN Department of Economic and Social Affairs) (2010) World Population Prospects: The 2010 Revision. URL: http://esa.un.org/unpd/wpp/index.htm (accessed 6th May 2011).Google Scholar
Flores-Mendoza, C., Gallegos, M., Mansur-Alves, M., Rosas, R., Ardila, R., Gómez-Maqueo, M. E. L.et al. (2007) Study of Latin American Intelligence (SLATINT). URL: www.fafich.ufmg.br/ladi/en/node/103 (accessed 23rd July 2012).Google Scholar
Flores-Mendoza, C., Widaman, K. F., Rindermann, H., Primi, R., Mansur-Alves, M. & Couto Pena, C. (2013) Cognitive sex differences in reasoning tasks: evidence from Brazilian samples. Intelligence 41, 7084.Google Scholar
Flynn, J. R. (2009) Requiem for nutrition as the cause of IQ gains: Raven's gains in Britain 1938–2008. Economics and Human Biology 7, 1827.Google Scholar
Flynn, J. R. (2012) Are We Getting Smarter? Rising IQ in the Twenty-First Century. Cambridge University Press, Cambridge.Google Scholar
Gottfredson, L. (2004) Intelligence: is it the epidemiologists' elusive ‘fundamental cause’ of social class inequalities in health? Journal of Personality and Social Psychology 86, 174199.Google Scholar
Gudjonsson, G. H. (1995) The Standard Progressive Matrices: methodological problems associated with the administration of the 1992 adult standardisation sample. Personality and Individual Differences 18, 441442.Google Scholar
Hart, B. & Risley, T. R. (1995) Meaningful Differences in the Everyday Experience of Young American Children. Paul Brookes, Baltimore.Google Scholar
Haworth, C. M. A., Wright, M. J., Luciano, M., Martin, N. G.de Geus, E. J. C.et al. (2010) The heritability of general cognitive ability increases linearly from childhood to young adulthood. Molecular Psychiatry 15, 11121120.Google Scholar
Hunt, E. (2012) What makes nations intelligent? Perspectives on Psychological Science 7, 284306.Google Scholar
Jensen, A. R. (1977) Cumulative deficit in IQ of Blacks in the rural South. Developmental Psychology 13, 184191.Google Scholar
Jensen, A. R. (1998) The g factor. The Science of Mental Ability. Praeger, Westport.Google Scholar
Johnson, W. (2010) Understanding the genetics of intelligence: can height help? Can corn oil? Current Directions in Psychological Science 19, 177182.Google Scholar
Jones, G. (2012) Cognitive skill and technology diffusion: an empirical test. Economic Systems 36, 444460.Google Scholar
Khaleefa, O., Lynn, R., Abulgasim, A., Dosa, M. & Abdulradi, F. (2010) Norms for the Standard Progressive Matrices for 9–18 year olds for Darfur. Mankind Quarterly 50, 311317.Google Scholar
Komlos, J. & Kriwy, P. (2003) The biological standard of living in the two Germanies. German Economic Review 4, 493507.Google Scholar
Kratzmeier, H. & Horn, R. (1980) Raven-Matrizen Test. Advanced Progressive Matrices (APM). Beltz, Weinheim.Google Scholar
Levine, R. (1997) A Geography of Time. Basic Books, New York.Google Scholar
LLECE (Laboratorio Latinoamericano de Evaluación de la Calidad de la Educación) (2000) Primer estudio internacional comparativo sobre lenguaje, matemática y factores asociados, para alumnos del tercer y cuarto grado de la educación básica. []. UNESCO/Andros, Santiago, Chile.Google Scholar
LLECE (Latin American Laboratory for Assessment of the Quality of Education) (2008) Student Achievement in Latin America and the Caribbean. Results of the Second Regional Comparative and Explanatory Study (SERCE). Regional Bureau for Education in Latin America Latina and the Caribbean, Santiago, Chile.Google Scholar
Lynn, R. (1990) The role of nutrition in secular increases in intelligence. Personality and Individual Differences 11, 273285.Google Scholar
Lynn, R. (2008) The Global Bell Curve. Race, IQ, and Inequality Worldwide. Washington Summit, Augusta.Google Scholar
Lynn, R. (2009) Fluid intelligence but not vocabulary has increased in Britain, 1979–2008. Intelligence 37, 249255.Google Scholar
Lynn, R. & Vanhanen, T. (2006) IQ and Global Inequality. Washington Summit, Athens.Google Scholar
Lynn, R. & Vanhanen, T. (2012) Intelligence. A Unifying Construct for the Social Sciences. Ulster Institute for Social Research, London.Google Scholar
Martin, M. O., Mullis, I. V. S., Foy, P. & Stanco, G. M. (2012) TIMSS 2011 International Results in Science. TIMSS & PIRLS International Study Center, Boston, MA.Google Scholar
Meisenberg, G. (2009) Intellectual growth during late adolescence: effects of sex and race. Mankind Quarterly 50, 138155.Google Scholar
Meisenberg, G. (2012) National IQ and economic outcomes. Personality and Individual Differences 53, 103107.Google Scholar
Meisenberg, G. & Lynn, R. (2011) Intelligence: a measure of human capital in nations. Journal of Social, Political and Economic Studies 36, 421454.Google Scholar
Meisenberg, G., Lawless, E., Lambert, E. & Newton, A. (2006) Determinants of mental ability on a Caribbean island, and the mystery of the Flynn effect. Mankind Quarterly 46, 273312.Google Scholar
Meisenberg, G. & Woodley, M. A. (2013) Are cognitive differences between countries diminishing? Evidence from TIMSS and PISA. Intelligence 40, 808816.Google Scholar
Mullis, I., Martin, M. O., Kennedy, A. M. & Foy, P. (2007) PIRLS 2006 International Report. IEA/TIMSS & PIRLS International Study Center, Chestnut Hill, MA.Google Scholar
Mullis, I. V. S., Martin, M. O. & Foy, P. (with Olson, J. F., Preuschoff, C., Erberber, E., Arora, A. & Galia, J.) (2008) TIMSS 2007 International Mathematics Report. TIMSS & PIRLS Study Center, Chestnut Hill, MA.Google Scholar
Mullis, I. V. S., Martin, M. O., Foy, P. & Arora, A. (2012) TIMSS 2011 International Results in Mathematics. TIMSS & PIRLS International Study Center, Boston, MA.Google Scholar
Neubauer, A. & Benischke, Ch. (2002) A cross-cultural comparison of the relationship between intelligence and speed of information processing in Austria vs. Guatemala. Psychologische Beiträge 44, 521534.Google Scholar
OECD (2006) Assessing Scientific, Reading and Mathematical Literacy. A Framework for PISA 2006. OECD, Paris.Google Scholar
Oswald, W. D. & Roth, E. (1978) Der Zahlenverbindungstest (ZVT) [Number trail test.] Hogrefe, Göttingen.Google Scholar
Pianta, R. C., Barnett, W. S., Burchinal, M. & Thornburg, K. R. (2009) The effects of preschool education. Psychological Science in the Public Interest 10, 4988.Google Scholar
Pieber, E-M. (2009) Kognitive fähigkeiten bei kindern im kindergarten- und schulalter [.] Master's Thesis, Graz.Google Scholar
Pietschnig, J., Voracek, M. & Formann, A. K. (2010) Pervasiveness of the IQ rise: a cross-temporal meta-analysis. PLoS One 5(12), 16.Google Scholar
Protzko, J., Aronson, J. & Blair, C. (2013) How to make a young child smarter: evidence from the database of raising intelligence. Perspectives on Psychological Science 8, 2540.Google Scholar
Putterman, L. & Weil, D. (2010) Post-1500 population flows and the long run determinants of economic growth and inequality. Quarterly Journal of Economics 125, 16271682.Google Scholar
Raven, J. C. (1976/1943) Advanced Progressive Matrices (APM). Oxford Psychologists Press, Oxford.Google Scholar
Raven, J. (1981) Manual for Raven's Progressive Matrices and Vocabulary Scales. Oxford Psychologists Press, Oxford.Google Scholar
Raven, J. C. (2003/1958) Coloured Progressive Matrices (Raven's CPM Kit). Pearson, Upper Saddle River.Google Scholar
Raven, J., Raven, J. C. & Court, J. H. (1998/1938) Manual for Raven's Progressive Matrices and Vocabulary Scales. Oxford Psychologists Press, Oxford.Google Scholar
Raven, J. C., Raven, J., Court, J. H., Bulheller, S. & Häcker, H. (2006/1956) Coloured Progressive Matrices (CPM). Harcourt, Frankfurt.Google Scholar
Rindermann, H. (1999) Sexual relationships between tourists and locals in Cuba: forms and experiences in the perspective of Cubans. Zeitschrift für Sexualforschung 12, 159177.Google Scholar
Rindermann, H. (2011) Results in the International Mathematical Olympiad (IMO) as indicators of the intellectual classes' cognitive-ability level. In Ziegler, A. & Perleth, Ch. (eds) Excellence. Essays in Honour of Kurt. A. Heller: Lit, Münster, pp. 303321.Google Scholar
Rindermann, H. (2012) Intellectual classes, technological progress and economic development: the rise of cognitive capitalism. Personality and Individual Differences 53, 108113.Google Scholar
Rindermann, H. (2013) African cognitive ability: research, results, divergences and recommendations. Personality and Individual Differences 55, 229233.Google Scholar
Rindermann, H. & Baumeister, A. E. E. (2012) Differences between Montessori and traditional kindergartens concerning quality and their effects on child development. Psychologie in Erziehung und Unterricht 59, 217226.Google Scholar
Rindermann, H., Baumeister, A. E. E. & Gröper, A. (2014) Cognitive abilities of Emirati and German engineering university students. Journal of Biosocial Science 46, 207221.Google Scholar
Rindermann, H., Michou, Ch. D. & Thompson, J. (2011) Children's writing ability: effects of parent's education, mental speed and intelligence. Learning and Individual Differences 21, 562568.Google Scholar
Rindermann, H. & Neubauer, A. (2000) Speed of information processing and success at school: do basal measures of intelligence have predictive validity? Diagnostica 46, 817.Google Scholar
Rindermann, H., Sailer, M. & Thompson, J. (2009) The impact of smart fractions. Talent Development and Excellence 1, 325.Google Scholar
Rindermann, H. & te Nijenhuis, J. (2012) Intelligence in Bali – a case study on estimating mean IQ for a population using various corrections based on theory and empirical findings. Intelligence 40, 395400.Google Scholar
Rindermann, H. & Thompson, J. (2013) Ability rise in NAEP and narrowing ethnic gaps? Intelligence 41, 821881.Google Scholar
Rindermann, H., Woodley, M. A. & Stratford, J. (2012) Haplogroups as evolutionary markers of cognitive ability. Intelligence 40, 362375.Google Scholar
Silverman, I. W. (2010) Simple reaction time: it is not what it used to be. American Journal of Psychology 123, 3950.Google Scholar
Spearman, Ch. (1932) The Abilities of Man: Their Nature and Measurement. AMS Press, New York, NY.Google Scholar
UNDP (2010) Human Development Report 2010. United Nations, New York.Google Scholar
Van de Vijver, F. J. R. & Brouwers, S. A. (2009) Schooling and basic aspects of intelligence: a natural quasi-experiment in Malawi. Journal of Applied Developmental Psychology 30, 6774.Google Scholar
Walker, M. (2011) PISA 2009 Plus Results. Performance of 15-year-olds in Reading, Mathematics and Science for 10 Additional Participants. ACER, Camberwell.Google Scholar
Winship, Ch. & Korenman, S. (1997) Does staying in school make you smarter? The effect of education on IQ in The Bell Curve. In Devlin, B., Fienberg, S. E., Resnick, D. P. & Roeder, K. (eds) Intelligence, Genes and Success. Springer, New York, pp. 215234.Google Scholar
Woodley, M. A., te Nijenhuis, J. & Murphy, R. (2013) Were the Victorians cleverer than us? Intelligence URL: http://dx.di.org/10.1016/j.intell.2013.04.006Google Scholar