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Drivers and barriers to educational success

Drivers and barriers to educational success. Haroon Chowdry, Claire Crawford, Alissa Goodman Institute for Fiscal Studies. Background and Motivation. Why do children from poor backgrounds do worse at school (and in later life) compared to children from better off backgrounds?

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Drivers and barriers to educational success

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  1. Drivers and barriers to educational success Haroon Chowdry, Claire Crawford, Alissa Goodman Institute for Fiscal Studies

  2. Background and Motivation • Why do children from poor backgrounds do worse at school (and in later life) compared to children from better off backgrounds? • Related issue: concern about lack of ‘social mobility’ in UK • Strong correlation between parental ‘socio-economic status’ (SES) as a child, and SES as an adult

  3. Background and Motivation

  4. Background and Motivation • Educational attainment plays key role in transmission of (dis)advantage across generations • 35-40% of correlation between parents’ and sons income (Blanden et al., 2005) • Educational inequalities matter more generally: • Socioeconomic inequality in HE participation • NEETs (especially in current economic climate) • Research has shown that attainment in school plays a crucial role • Improving attainment early on may have compound impact

  5. Background and Motivation • This presentation focus on low achievement in secondary school • ‘Routes’ through which children from poor backgrounds fare badly as teenagers • Complex set of influences throughout childhood • Early years: home learning environments, parenting styles, health-related behaviours • Primary school: lasting influence of early years, maternal aspirations, child’s own ability beliefs • Teenage years: young person’s own attitudes and behaviours; lasting influence of parents; material resources in the home • Important caveat: none of this is a causal analysis • Does not tell us if we increased resources/social position, whether outcomes would change • Cannot make specific policy recommendations

  6. The teenage “attainment gap”

  7. Attainment gap: intuitive examples

  8. Methodology • Define a set of possible pathways (“transmission mechanisms”) between “family background” and attainment • Family background • Socioeconomic position (SEP) • Parental education • Demographics, family structure, etc. • Possible transmission mechanisms • Schools (quality and composition) • Neighbourhoods (composition) • Material resources on educational items • Parental ‘attitudes and behaviours’ • Child ‘attitudes and behaviours’

  9. CHANGES IN TRANSMISSION MECHANISMS FAMILY BACKGROUND OUTCOMES @14 TRANSMISSION MECHANISMS OUTCOMES @ 16 Parental socio-economic status Key Stage 3 results Key Stage 4 results Changes in family background 1. Schools 5. Young people’s attitudes, and behaviours (“As and Bs”) 2. Neighbourhoods Parental education 3. Material resources diverted to education 5. Changes in YP attitudes, and behaviours 4. Parental attitudes and behaviours (“As and Bs”) Other family background and demographics Unobservables Model of attainment at secondary school

  10. Empirical analysis • Estimate series of simple equations, starting with • Yt = α + βSEP + ε(‘levels’) • Yt = α+ γYt–1 + βSEP + ε(‘value-added’) • These give the SEP gradient we are trying to explain • Add in our ‘transmission mechanisms’ and observe size of SEP gradient with inclusion of each one: • Yt = α + βSEP + δPED + ηFAM + ε • Yt = α + βSEP + δPED + ηFAM + λSCH + μNBD + ρMATRES + κMPABS +σ YPABS + ε • These suggest how much the SEP gradient (β) can be explained by controlling for differences in each of these sets of factors • But this is NOT a causal analysis (reverse causation/unobservables)

  11. Data • Longitudinal Study of Young People in England (LSYPE) • Single academic year cohort born in 1989/90 • Study started in Year 9 (age 13), we have data up to Year 11 • Detailed questions from young person and parents • Linked to administrative attainment records at age 11, 14, and 16 • Our sample: with complete administrative records (state school only), approximately 15,770

  12. Variables derived from LSYPE • SEP • Income (averaged across waves) • Occupation of both parents • Housing tenure • Financial difficulties • Take principal component to derive SEP index, divide into quintiles • Parental education • Matched information from administrative school data • School quality and composition • Neighbourhood composition

  13. Variables derived from LSYPE • Material resources devoted to education • Private lessons • Computer access • Internet access • Parental attitudes and beliefs • Education values (‘getting a good education is important’) • Aspirations for age 16 • Expectations for HE • Education interactions (help with homework, talking about reports) • Family interactions (sharing meals, arguing) • Involvement in school activities (parents’ evenings etc.)

  14. Variables derived from LSYPE • Young person attitudes and behaviours • Ability beliefs (‘I get good marks’) • Locus of control (In control of destiny) • Likes school (‘I like school’) • School valuable (‘School is a waste of time’ ) • Aspirations for age 16 (Wants to stay on in FTE) • Expectations for HE (Likely to apply to HE) • Job/career values (‘Having a job that leads somewhere is important’) • Experiences of bullying • Anti-social behaviour (fighting, trouble with police, shoplifting) • Truancy, suspension, exclusion • Substance use (smoking, drinking, cannabis) • Teacher child relations (I like my teachers) • Positive activities (sport, reading etc.)

  15. Descriptives: parents

  16. Descriptives: young people

  17. Results • How important are these transmission mechanisms for understanding the inequalities in school attainment? • Answer in two stages: • Do transmission mechanisms have an impact upon attainment? • Do transmission mechanisms help to explain the socioeconomic gap in attainment?

  18. 1) Impact of TMs on KS4 scores (std. devs.)

  19. 1) Impact of TMs on KS4 scores (std. devs.)

  20. 1) Impact of TMs on KS4 scores (std. devs.)

  21. 2) How much of KS4 gap can be explained by TMs

  22. 2) How much of KS4 gap can be explained by TMs

  23. 2) How much of KS4 gap can be explained by TMs

  24. 2) How much of KS4 gap can be explained by TMs

  25. 2) How much of KS4 gap can be explained by TMs

  26. 2) How much of KS4 gap can be explained by TMs

  27. 2) How much of KS4 gap can be explained by TMs

  28. 2) How much of KS4 gap can be explained by TMs

  29. Conclusions • Large SEP gap in education outcomes • Correlations of particular note: • Maternal education (causal analysis supports this too) • Parents’ and young people’s educational aspirations • Family child interactions • Computer and internet access in the home • Changing attitudes and aspirations – the answer? • Aspirations are high across the board at age 14 and still to an extent at age 16: just raising them may not be enough • Ability beliefs: kids from poor backgrounds more likely to think that they are good at school than young people from better off backgrounds after taking Key Stage 2 into account: no evidence of systematic under-estimation here • This analysis identifies some key areas • ...but not policy answers!

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