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School Effectiveness and School Improvement
An International Journal of Research, Policy and Practice
Volume 21, 2010 - Issue 3
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Articles

Do some schools narrow the gap? Differential school effectiveness by ethnicity, gender, poverty, and prior achievement

Pages 289-314 | Received 01 Jul 2009, Accepted 26 Jan 2010, Published online: 23 Aug 2010
 

Abstract

This study analyses the educational progress of an entire national cohort of over 530,000 pupils in England between age 7 in 2000 and age 11 in 2004. The results show that Black Caribbean boys not entitled to free school meals, and particularly the more able pupils, made significantly less progress than their White British peers. There is no evidence that the gap results from Black Caribbean pupils attending less effective schools. There is also no evidence of differential effectiveness in relation to ethnic group; schools that were strong in facilitating the progress of White British pupils were equally strong in facilitating the progress of Black Caribbean pupils. There was some evidence of differential school effectiveness by pupil prior achievement, gender, and poverty, but the absolute sizes of the effects were small. The results suggest the poor progress of Black Caribbean pupils reflects a systemic issue rather than the influence of a small number of “low quality” schools.

Notes

1. England has experienced successive waves of immigration dating back over many centuries. In recent times, the major influxes have been from the Caribbean and the Indian subcontinent in the 1950s. Many Pakistani men brought over their families in the 1960s/1970s, although many Bangladeshi men did not do so until the 1980s. Most recently, the largest waves have been from Africa and from Central and Eastern Europe. For the current proportion of the school age population in each ethnic group, see DfES (Citation2006).

2. The report did not evaluate interactions or the question of school effects as will be described here.

3. Approximately 3.4% of the primary age group in England attend private (independent) schools which are not state-maintained and do not have to complete national tests or provide background data on their pupils. A small proportion of pupils attending state-maintained special schools (1%) were excluded since national tests are not designed to be sensitive enough to pick up the progress made by such pupils.

4. Eligible families are those on Income Support, Income Based Jobseekers Allowance, support under Part VI of the Immigration and Asylum Act 1999, Guarantee element of State Pension Credit, or Child Tax Credit (provided they are not entitled to Working Tax Credit and have an annual income as assessed by the Inland Revenue that does not exceed £13,910).

5. Considering the sample size in this study, statistical significance is not necessarily a good guide to educational significance, since with a very large sample many relatively small differences may be statistically significant (see, e.g., Elliot & Sammons, 2004). However, given the outcome has been normalised, regression coefficients indicated the size of effects in SD units, giving an indication of the magnitude of effects.

6. Effect size is calculated by multiplying the %FSM coefficient by 2 * the SD of %FSM (corresponding to the difference between schools 1 SD above and 1 SD below the grand mean for %FSM) and dividing by the SD of the pupil-level age 11 score (see Elliot & Sammons, 2004).

7. Approximately 40% of primary schools were 100% monoethnic, since all their pupils were White British.

8. This was not the case when the coefficients for other ethnic groups were allowed to vary. For example, the Black African coefficient did vary significantly across schools.

9. The standard deviation (SD) is the square root of the variance.

10. Though this average reflects the fact that Black Caribbean boys entitled to FSM made less progress and Black Caribbean girls entitled to FSM made more progress than their comparable White British peers.

11. This is reflected in the much younger age structure of the Black African population, with 30% aged under 16 compared to 20% among Black Caribbean and White British groups (Office for National Statistics, Citation2001).

12. A binary record of whether English was an Additional Language (EAL) was available for the current sample but has not been included in the regression analysis for two reasons. First, it is effectively co-terminus with ethnicity, for example, 0.2% of White British but 95% of Pakistani and 98% of Bangladeshi pupils were recorded as EAL. Second, the EAL flag gives no information regarding the key question of the pupil's level of fluency in the English language. For example, Strand and Demie (2005) report that 42% of pupils with EAL were fully fluent in English and the achievement of these pupils exceeded that of their monolingual English peers.

13. Black African is itself a heterogeneous group. While Nigerians and Ghanaians form the two largest communities, significant numbers have arrived in recent years, particularly from Somalia, Ethiopia, Congo, Uganda, and Zimbabwe, and there are quite marked differences in achievement between these groups (DfES, 2006).

14. For example, Fryer and Levitt's ECLS-K sample contained an average of only 20 pupils per school (Fryer & Levitt, 2004, p. 449).

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