Socioeconomic environment effect on inferential reasoning of Latin American students

Carmen Flores-Mendoza, Renan Benigno Saraiva, Gislene Clemente Vilela Câmara, Wilma M. Guimarães Lopes, Ana P. Carvalho Pereira Passos, Ana Maria Valladão Pires Gama, Viviane de Oliveira Baumgartl, Larissa Assunção Rodrigues, Ruben Ardila, Ricardo Rosas, Miguel Gallegos, Norma Reategui

DOI: https://doi.org/10.17711/SM.0185-3325.2017.024

Abstract


Introduction. Inferential reasoning (IR) is a major component of intelligence, which comprises many different cognitive processes such as perception, memory, and logic. Many studies have proposed that socioeconomic status (SES) has a negligible association with IR, but more recent findings suggest that they may have a higher association when evaluating group instead of individual SES.

Objective. The aim of this study is to test the effects of both individual (students) and group (schools) socioeconomic status on IR, comparing different countries of Latin America.

Method. The sample was composed of 2 358 students aged 14 and 15 years from 52 different schools (44% public) of five Latin American countries (Argentina, Brazil, Chile, Colombia, and Peru). Participants took part in an inferential reasoning test and answered a socioeconomic questionnaire.

Results. SES student showed a small positive correlation with IR (r = .10, p < .001), while SES school had a more pronounced effect on IR (F [2, 1944] = 74.68, p < .001, ηp2 = .07), with higher IR at schools with higher SES. A significant difference of IR between countries (F [4, 1976] = 20.68, p < .001, ηp2 = .04), was also found with Peru showing the highest mean. Peru was the country with the higher percentage of private schools in the present study. A multilevel model was fitted using individual and group SES as predictors.

Discussion and conclusion. Our findings showed that group SES have a higher predictive value of IR when compared to individual SES. This result suggests that individuals with low SES can benefit from studying on higher SES schools. Future research and the importance of public policies are discussed.


Keywords


Inferential reasoning; intelligence; socioeconomic factors; Latin American; schoolchildren

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References


Beddington J, Cooper CL, Field J, Goswami U, Huppert FA, Jenkins R, et al. The mental wealth of nations. Nature. 2008 Oct; 455(7216):1057-1060.

Future of skills and lifelong learning [Internet]. [Place unknown];2016, Jun 23). Available from: https://www.gov.uk/government/collections/future-of-skills-and-lifelong-learning.

Jensen A. The g Factor: The Science of Mental Ability. Westport: Praeger; 1998.

Sisto FF. Teste de Raciocínio Inferencial. São Paulo: Vetor Editora Psicopedagó; 2006.

Gottfredson LS. Where and why g matters: Not a mystery. Human Performance. 2002 Jun; 15(1/2):25-46.

Kuncel NR, Hezlett SA, Ones DS. Academic performance, career potential, creativity, and job performance: Can one construct predict them all? Journal of personality and social psychology. 2004 Jan; 86(1):148-161.

Neisser U, Boodoo G, Bouchard Jr TJ, Boykin AW, Brody N, Ceci, SJ et al. Intelligence: knowns and unknowns. American psychologist. 1996 Feb; 51(2):77-101.

Gottfredson LS. g, jobs and life. In H. Nyborg (Hrsg.), The scientific study of general intelligence (S. 293-342). Oxford: Pergamon; 2003.

Gottfredson LS. Consequências Sociais das Diferenças de Grupo na Capacidade Cognitiva. In C. Flores-Mendoza e R. Colom (comps), Introdução à Psicologia das Diferenças Individuais (433-456). Porto Alegre: Artmed; 2006.

Beier ME, Ackerman PL. Current-events knowledge in adults: an investigation of age, intelligence, and nonability determinants. Psychology and aging. 2001 Dec; 16(4):615-628.

Beier ME, Ackerman PL. Determinants of health knowledge: An investigation of age, gender, abilities, personality, and interests. Journal of Personality and Social Psychology. 2003 Feb; 84(2):439-448.

Beier ME, Ackerman PL. Age, Ability, and the Role of Prior Knowledge on the Acquisition of New Domain Knowledge: Promising Results in a Real-World Learning Environment. Psychology and Aging. 2005 Jun; 20(2):341-355.

Gottfredson LS, Deary IJ. Intelligence predicts health and longevity, but why? Current Directions in Psychological Science. 2005 Feb; 13(1):1-4.

Walker NP, McConville PM, Hunter D, Deary IJ, Whalley LJ. Childhood mental ability and lifetime psychiatric contact: A 66-year follow-up study of the 1932 Scottish Mental Ability Survey. Intelligence. 2002 May; 30(3):233-245.

Der G, Batty GD, Deary I. The association between IQ in adolescence and a range of health outcomes at 40 in the 1979 US National Longitudinal Study of Youth. Intelligence. 2009 Nov; 37(6):573-580.

Ciarrochi J, Heaven PCL, Skinner T. Cognitive ability and health-related behaviors during adolescence: A prospective study across five years. Intelligence. 2002 July; 40(4):317-324.

Ashby-Mitchell K, Jagger C, Fouweather T, Anstey KJ. Life Expectancy with and without Cognitive Impairment in Seven Latin American and Caribbean Countries. PLoS ONE. 2015 Mar; 10(3).

Guàrdia-Olmosa J, Peró-Cebollero M, Rivera D, Arango-Lasprilla JC. Methodology for the development of normative data for ten Spanish-language neuropsychological tests in eleven Latin American countries. NeuroRehabilitation. 2015 Nov; 37(4):493–499.

Flynn JR, Rossi Casé, L. IQ gains in Argentina between 1964 and 1998. Intelligence. 2012 Jan; 40(2):145-150.

Flores-Mendoza C, Mansur-Alves M, Ardila R, Rosas RD, Guerrero-Leiva MK, Maqueo MELG et al. Fluid intelligence and school performance and its relationship with social variables in Latin American samples. Intelligence. 2015 Mar; 49:66-83.

Strenze T. Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence. 2007 Sep; 35:401–426.

Colom R, Flores-Mendoza C. Intelligence predicts scholastic achievement irrespective of SES factors: Evidence from Brazil. Intelligence. 2007 May; 35(3):243-251.

Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage; 2002.

R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org. 2016.

Hox JJ, Moerbeek M, van de Schoot R. Multilevel analysis: Techniques and applications. Routledge; 2010

Voyer D, Voyer S, Bryden M. Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin. 1995 Mar; 117(2):250-270.

Miller DI, Halpern DF. The new science of cognitive sex differences. Trends in Cognitive Sciences. 2014 Jan; 1:37-45.

Duarte J, Bos MS, Moreno M. Inequity in School Achievement in Latin America: Multilevel Analysis of SERCE results according to the socioeconomic status of students. R Inter-American Development Bank. 2010 May.

Jargowsky PA, El Komi M. Before or After the Bell? School Context and Neighborhood Effects on Student Achievement. In: Susan Wachter, Eugénie L. Birch, and Harriet Newberger (Eds.), How Place Matters. Philadelphia: University of Pennsylvania Press; 2009.