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The Dynamics of School Attainment of England s Ethnic Minorities Deborah Wilson, Simon Burgess, Adam Briggs February 2006.

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Presentation on theme: "The Dynamics of School Attainment of England s Ethnic Minorities Deborah Wilson, Simon Burgess, Adam Briggs February 2006."— Presentation transcript:

1 The Dynamics of School Attainment of England s Ethnic Minorities Deborah Wilson, Simon Burgess, Adam Briggs February 2006

2 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO2 Introduction Accumulation of human capital is a key to economic success for individuals and communities. Relative achievement of minority ethnic learners is an on-going cause for concern among policy-makers in the UK. A lot of evidence for US, rather less for UK.

3 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO3 In this paper: –We exploit a universe dataset of state school students in England –We document the evolution of attainment for different ethnic groups through school –We explore some factors lying behind relative achievement –Results:

4 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO4 We confirm some well-known facts for the high stakes exams taken at age 16: –pupils from some ethnic groups achieve considerably lower scores than white pupils on average – pupils with Black Caribbean heritage, other Black heritage or Pakistani ethnicity. –Students with Indian or Chinese ethnicity score much higher than their white peers

5 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO5 We provide some striking new findings: –All ethnic minority groups make greater progress on average than white students between ages 11 and 16. –Much of this improvement is in the high-stakes exams at the end of compulsory schooling. –For most ethnic groups, this gain relative to white students is pervasive, happening in almost all schools.

6 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO6 Our analysis addresses some of the usual factors invoked to explain attainment gaps, although these are typically about levels rather than growth in attainment We consider the roles of poverty, language, school quality, and teacher influence We analyse attainment gaps at the lower end of the distribution.

7 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO7 Plan Literature Data Modelling Framework Results I Results II Conclusions

8 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO8 English School System Age PrimarySecondary University, job, … Tests KS1KS2KS3KS4 = GCSEs A levels This paper End of compulsory schooling

9 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO9 Data PLASC/NPD: administrative data from the DfES. All pupils in English state schools; approx 0.5 million in each cohort. Key Stage (KS) tests: –Cohort 1: KS1 (age 7) in 1998; KS2 (age 11) in –Cohort 2: KS2 in 1997; KS3 (age 14) in 2000; KS4 = GCSE (age 16) in As yet, no single cohort going all the way through

10 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO10 Data II PLASC/NPD gives individual characteristics: –Ethnicity –English as an additional language (EAL) –Eligibility for free school meals (FSM) –Gender, age within year –Special educational needs status (SEN) –Home postcode –School attended Attainment data at each Key Stage All but attainment data is for 2001/02 only.

11 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO11 Data III Pupil home postcode enables us to match in local area data: –Index of multiple deprivation (IMD) Ward level; 6 components (income; employment; health; education; housing; access to services) –MOSAIC Postcode level dataset. Categorises each postcode into one of 61 types.

12 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO12 Data IV Analysis sample: –study the cohorts as balanced panels – proportion of students with full record is high –track the same group through school without worrying about changing sample composition –Unrepresentative of all students taking tests? No, apart from Black African heritage students Sample sizes:

13 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO13

14 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO14 Table 2: Summary statistics of Key-stage scores for both cohorts

15 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO15 Measuring test score gaps Different distribution of marks at each KS. At KS4 – SD here four times bigger than at KS2. Just using marks – hard to interpret gaps. We do three things: –We use z scores – normalise each KS# mark separately by its mean and SD (all ethnic groups together). So units are in SDs. –Use ranks –Discretise KS4 marks as alternative to treating KS2 marks as continuous

16 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO16 Plan Literature Data Modelling Framework Results I Results II Conclusions

17 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO17 Modelling Framework Adopt a human capital approach – test score depends on human capital h it = t + j jt X ij + l lt Z il + m mt im The final term is the myriad influences on human capital cant measure. These may be correlated with a pupils ethnicity. So the coefficient on an ethnic group dummy summarises the correlation of membership of that ethnic group with these variables, weighted by their impact on human capital.

18 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO18 Role of schools In most tables, we dont focus on schools: –A straightforward interpretation of such variables would require the assumption that pupils are randomly allocated to schools –Interpretation of ethnicity is that it includes both the direct impact of that characteristic on test score, plus the indirect effect on school quality times the impact of that quality on test score.

19 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO19 Estimation We estimate: y it = g gt I(ethnic group) i + b 1t.gender i + b 2t.age i + b 3t.FSM i + b 4t.SEN i + n b 5nt.I(nhood) i We also look at a pupils progress over the Key Stages, referred to as value-added: –An individual pupils value added from KS2 to KS4 is the difference between her own grade and that average for those with the same KS2 score.

20 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO20 Plan Literature Data Modelling Framework Results I Results II Conclusions

21 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO21 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

22 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO22 Graphical approach:

23 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO23 KS Scores by ethnicity

24 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO24 Using ranks

25 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO25 Discretising KS4:

26 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO26 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

27 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO27 Table 5: Regressions of standardised Key-stage 4 scores for cohort 2

28 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO28 Table 6: Regressions of standardised key-stage scores

29 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO29 Figure 5: Group-White conditional gaps

30 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO30 Heterogeneity – matching analysis

31 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO31 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

32 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO32 Table 7: Regressions of Key-stage 2 to 4 Value added for cohort 2

33 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO33 Table 8: Regressions of value-added

34 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO34 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

35 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO35 Z-scores: male, FSM, bottom 20% KS2 and IMD

36 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO36 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

37 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO37 Table 10: Predicted Vs actual GCSE attainment by ethnicity

38 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO38 Results I –Raw attainment gaps –Conditional attainment gaps –Value Added gaps –Attainment Gaps at Lower Quantiles –Quantifying the gap Results II –Non-school factors –Systemic schooling factors –Between-school factors –Within-school factors

39 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO39 Statistical factors Regression to the mean –Split pupils from each ethnic group into gender*FSM*KS2 cells –Designate equivalent white pupils in each sub- cell; track these over subsequent KSs. –Figure 8

40 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO40 Figure 8: Performance of equivalent Group-White pupils

41 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO41 Non-school factors Individual characteristics affect progress? Language –PLASC records whether English is a pupils mother tongue, the language spoken at home. –Only two groups with some variation: Black Africans and Indian ethnicity students –Accounts for about a third of the gain for these two groups (Table 12) –Separate analysis of maths, english and science

42 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO42 Systemic Schooling Factors Differences in assessment? –No: consistent assessment across KS2 – KS4. Teacher expectations or bias? –Yes: greater divergence between mark and teacher assessment for some groups (Table 13) Role of Special Educational Needs (SEN) indicator? –Not conditioning on SEN, same results on progress.

43 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO43 Between-school factors School quality –the quality of the teachers, the ethos and leadership of the school, and peer groups –Non-random allocation of pupils to schools –Comparing fixed effects and OLS means comparing average variation within a school, to variation both within and across schools. –Look at London only

44 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO44 Table 14: School fixed effects vs OLS

45 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO45 Within-school factors Differences in school practices? –For each school and for each ethnic group, we ask whether that group has higher mean value added than white students. –Table 15 presents the percentage of schools for which that group improves relative to whites.

46 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO46 Table 15: Proportion of schools/LEAs where ethnic group progress relative to White pupils is positive

47 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO47 Hot off the press … Black Caribbean Indian Black African Pakistani Conditional score gaps

48 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO48 Plan Literature Data Modelling Framework Results I Results II Conclusions

49 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO49 Conclusions Minority ethnic groups make better average progress through secondary school than do white students. These gains are substantial for some groups, only marginal for students of Black Caribbean heritage. These gains are pervasive for most of the groups. The gains are particularly marked in the final exams that are crucial for further progress in education or jobs.

50 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO50 Findings suggest systemic factors: the importance of aspirations and values? –Modood (2005): Asian trajectory … social mobility by education, self-employment and progression into the professions –Winder (2004): familiar immigrant paradigm: the children of immigrants, lacking financial capital of their own, devote themselves to the acquisition of knowledge

51 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO51 Appendices

52 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO52 Table 11: Regressions of standardised values of cohort 2 key-stage 4 score

53 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO53 Table 12: Regressions of key-stage 2 to 4 value added for cohort 2

54 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO54 Table 13: Test score vs Teacher assessment

55 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO55 KS scores by ethnicity and FSM status: FSM Pupils

56 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO56 KS scores by ethnicity and FSM status: non-FSM Pupils

57 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO57 KS scores by ethnicity and gender: Female Pupils

58 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO58 KS scores by ethnicity and gender: Male Pupils

59 PLUG, March 2006www.bristol.ac.uk/Depts/CMPO59 Understanding ethnicity Ethnicity here refers to membership of a group defined by descent; and ethnic difference has 5 dimensions (Modood 2005): –Cultural distinctiveness –Disproportionality –Strategy –Creativity –Identity These 5 dimensions relate to educational attainment.


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