Literature DB >> 30631464

Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them.

Emily Smith-Woolley1, Jean-Baptiste Pingault1,2, Saskia Selzam1, Kaili Rimfeld1, Eva Krapohl1, Sophie von Stumm3, Kathryn Asbury4, Philip S Dale5, Toby Young6, Rebecca Allen7, Yulia Kovas8,9, Robert Plomin1.   

Abstract

On average, students attending selective schools outperform their non-selective counterparts in national exams. These differences are often attributed to value added by the school, as well as factors schools use to select pupils, including ability, achievement and, in cases where schools charge tuition fees or are located in affluent areas, socioeconomic status. However, the possible role of DNA differences between students of different schools types has not yet been considered. We used a UK-representative sample of 4814 genotyped students to investigate exam performance at age 16 and genetic differences between students in three school types: state-funded, non-selective schools ('non-selective'), state-funded, selective schools ('grammar') and private schools, which are selective ('private'). We created a genome-wide polygenic score (GPS) derived from a genome-wide association study of years of education (EduYears). We found substantial mean genetic differences between students of different school types: students in non-selective schools had lower EduYears GPS compared to those in grammar (d = 0.41) and private schools (d = 0.37). Three times as many students in the top EduYears GPS decile went to a selective school compared to the bottom decile. These results were mirrored in the exam differences between school types. However, once we controlled for factors involved in pupil selection, there were no significant genetic differences between school types, and the variance in exam scores at age 16 explained by school type dropped from 7% to <1%. These results show that genetic and exam differences between school types are primarily due to the heritable characteristics involved in pupil admission.

Entities:  

Year:  2018        PMID: 30631464      PMCID: PMC6220309          DOI: 10.1038/s41539-018-0019-8

Source DB:  PubMed          Journal:  NPJ Sci Learn        ISSN: 2056-7936


  22 in total

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Authors:  Yulia Kovas; Claire M A Haworth; Philip S Dale; Robert Plomin
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  11 in total

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4.  School quality ratings are weak predictors of students' achievement and well-being.

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Review 6.  Bench Research Informed by GWAS Results.

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8.  The moderating role of SES on genetic differences in educational achievement in the Netherlands.

Authors:  Eveline L de Zeeuw; Kees-Jan Kan; Catharina E M van Beijsterveldt; Hamdi Mbarek; Jouke-Jan Hottenga; Gareth E Davies; Michael C Neale; Conor V Dolan; Dorret I Boomsma
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10.  From Genome-Wide to Environment-Wide: Capturing the Environome.

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