Differences in Intelligence and Socio-Economic Outcomes across the Twenty Seven States of Brazil

Lynn, Richard; Antonelli-Ponti, Mayra; Mazzei, Rodrigo Focosi; Silva, José Aparecido da; Meisenberg, Gerhard

doi:10.46469/mq.2017.57.4.3

Cited by 7 publications

(16 citation statements)

References 32 publications

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“…The strongest impact of HOMEPOS on performance in mathematics (β = 0.47), reading (β = 0.38) and science (β = 0.49), (Figures 1a,1b and 1c,respectively) corroborates the arguments that socioeconomic status explains part of the academic achievement (Lynn et al, 2017). Although the choice of this variable was made in an attempt to remove other variables related to income, it is noted in its description, that several items, even those considered educational resources, are easier to obtain with a higher income (such as computers and access to the internet).…”

Section: Discussionsupporting

confidence: 75%

“…It is influenced by social mechanisms in levels of complex and diverse relations, and must be taken into account in the elaboration of public policies in the area of education. Any improvement that leads to personal fulfillment will have an impact on school success and on the future of young people and their community (Curi & Menezes-Filho, 2014;Lynn et al, 2017). Having housing and being matriculated in school is not enough for the learning context to be efficient.…”

Section: Discussionmentioning

confidence: 99%

“…Among the international assessments, the Programme for International Student Assessment (PISA) stands out, applied in different countries and which, with each edition, improves the ways of accessing the performance of students as well as their personal, family and school profiles. The results of the analysis of the PISA databases are published through reports and publications in several areas and themes (Fernández, Rios & Marques, 2016;Lynn et al, 2017;Pizarro & Junior, 2017). As the PISA provides a standardized measurement of variables and a good representative sample of the national context, it is constituted as an opportunity to deepen the understanding of the relationship between variables related to the student, school and family (SSF) on school performance.…”

Section: Introductionmentioning

confidence: 99%

“…Educational achievement measures are widely used as predictors of future success (Curi & Menezes-Filho, 2014;Lynn, Antonelli-Ponti, Mazzei, Da Silva & Meisenberg, 2017). Multiple factors can influence school performance, among them stand factors related to the student itself, their school context and their family environment (SSF).…”

Section: Introductionmentioning

confidence: 99%

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Academic achievement and the effects of the student’s learning context: a study on PISA data

et al. 2021

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School achievement is under a multiple factorial context related to student, school and family (SSF). Based on 23.141 Brazilians self-reports, obtained from PISA 2015, representative SSF measures were selected, and their impacts measured on school performance scores in mathematics, reading and science. The feeling of belonging to the school (BELONG) and parents’ emotional support (EMOSUPS) were strongly correlated with the three investigated performances. EMOSUPS affected how the student feels at school and when being assessed. And the educational and cultural resources of the home affected EEC three dimensions, increasing EMOSUPS, BELONG and school performance, and decreasing anxiety during assessments. Thus, the importance of the school and family environments on students’ performance is reiterated and calls for public policies in education that considers the three dimensions.

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Academic achievement and the effects of the student’s learning context: a study on PISA data

et al. 2021

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“…O que parece de fato importar é a semelhança entre os instrumentos e os conjuntos de respostas, bem como a argumentação sobre a semelhança dos dados e a aceitação do uso dos conceitos pela comunidade científica. Exemplo disso são os trabalhos que embora adotem um mesmo instrumento ou base de dados, como o programa de avaliação escolar Programme International for Student Assessment (PISA), interpretam os dados como demonstrações de habilidades cognitivas ou de inteligência (Lynn, Antonelli-Ponti, Mazzei, Da Silva & Meisenberg, 2017;León & Antonelli-Ponti, 2018).…”

Section: Concepções Sobre Comportamentos Humanosunclassified

Concepções sobre a origem do comportamento humano e percepções sobre práticas docentes: potencialidades da formação continuada com base na psicobiologia

Antonelli-Ponti¹

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Com reconhecimento pleno e profundo da importância de todas as colaborações para a tese e para a minha vida, agradeço sincera e afetuosamente: À família maravilhosa que tenho. Minha mãe, Clara, ter me apoiado de diversas maneiras desde sempre e, durante o doutorado, por estar presente contagiando com positividade e simpatia tantos destes momentos. Meu filho, Pedro, por querer aprender comigo e junto comigo, por estar sempre disposto a me ajudar, por ser tão compreensivo e amoroso. Meu irmão, Moacir, pelas incontáveis conversas sobre minha vida e carreira, pelo carinho com que valoriza meu trabalho e acredita nele. Meu irmão, Maurício, por ter tido paciência e se empolgado comigo nas descobertas científicas.Minha avó, Judith por permitir e apoiar minha formação profissional. Meu companheiro, Ricardo, por se preocupar, me alertar pra que eu me cuide, por abraçar minhas causas, por me deixar acreditar e me fazer acreditar mais. Aos professores e professoras. Professor José Aparecido da Silva, por se manter presente e por cada orientação sobre a vida acadêmica. Professora Patrícia Ferreira Monticelli, por ter me encorajado a continuar estudando um tema que eu acredito, por me incentivar a buscar as oportunidades, por me ensinar com tanta qualidade e ternura. Professora Fabiana Maris Versuti, por me incluir em tantas e ricas oportunidades e experiências. Professora Rosana Suemi Tokumaru, pela hospitalidade com que me recebeu, e pela assertividade criativa que organizou meus pensamentos no início deste projeto. Professor José Dutra de Oliveira Neto, pelas orientações sobre EAD e pela oportunidade de trabalhar junto com o NPT. Professor Cesar Alexis Galera e Professora Elaine Pazello pelo auxílio do início do doutorado até a qualificação. Professora Teresa Vilaça, pela recepção e acompanhamento em Braga, pela ajuda em encontrar soluções, pelas recomendações acadêmicas sinceras sobre minha escrita, pelos ensinamentos sobre método e conselhos sobre a continuidade do trabalho. Professor José Egídio Barbosa Oliveira, pela disponibilidade em ensinar e pela destreza com que ensina. Professora Cristina Costa-Lobo, pelas oportunidades concedidas em Portugal e compartilhadas no Brasil. Professor Daniel Santos, por considerar minhas habilidades, além do meu currículo, e por ampliar minha visão e perspectivas sobre a sociedade humana. Às amizades. Lívia, por saber ouvir tão atentamente, pela parceria competente e comprometida, por compartilhar as dores dos obstáculos e a satisfação das esperanças. Alessandra, por saber colaborar da maneira mais real e prática que alguém pode imaginar. Palavras-chave: Interação social; genética do comportamento; ambiente educacional; aprendizagem social; formação continuada do professor; estereótipos.

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What matters for student learning outcomes? A systematic review of studies exploring system‐level factors of educational effectiveness

Mejía‐Rodríguez

Kyriakidēs

2022

Review of Education

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Meta‐analysis comprises a powerful tool for synthesising prior research and empirically validating theoretical frameworks. Using this tool and two recent multilevel models of educational effectiveness as guiding frameworks, this paper synthesises the results of 195 studies investigating the association between system‐level characteristics and student learning outcomes. Results show a broad range of system‐level factors studied in the international literature, which could be grouped into the three categories used in the integrated multilevel model of education: antecedents determined by the larger societal context, including factors such as level of development, inequality and societal values; system ecology and structural reform, covering factors such as decentralisation, accountability and stratification; and direct educational policies, including financial resources, time resources and variables related to teacher training and qualifications. Results highlight the importance of the larger context in which educational systems operate, as well as the need for further research looking at actual educational policies. Further analyses provide support for a generic effect of system‐level factors, regardless of the educational level or subject domain assessed. However, results show variation in terms of methodological choices, such as the number of levels used in the analysis. Based on these results, implications for theory, research, and policy are drawn.

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Differences in Intelligence and Socio-Economic Outcomes across the Twenty Seven States of Brazil

Cited by 7 publications

References 32 publications

Academic achievement and the effects of the student’s learning context: a study on PISA data

Academic achievement and the effects of the student’s learning context: a study on PISA data

Concepções sobre a origem do comportamento humano e percepções sobre práticas docentes: potencialidades da formação continuada com base na psicobiologia

What matters for student learning outcomes? A systematic review of studies exploring system‐level factors of educational effectiveness

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