gender and student achievement in english schools

357Oxford Review of Economic Policy vol. 21 no. 3 2005© The Authors (2005). Published by Oxford University Press. All rights reserved.

GENDER AND STUDENT ACHIEVEMENTIN ENGLISH SCHOOLS

OXFORD REVIEW OF ECONOMIC POLICY, VOL. 21, NO. 3DOI: 10.1093/oxrep/gri021

STEPHEN MACHINUniversity College London and London School of EconomicsSANDRA McNALLYLondon School of Economics1

The widening gap between the average educational achievement of boys and girls has been the subject of muchdiscussion. This gap is especially controversial for students taking national exams at the end of their compulsoryeducation. However, the gender gap is also apparent at earlier and at later stages of education. In this paper, weanalyse changes over time in the gender achievement gap at the different stages of compulsory education in Englishschools. We first use a combination of data sources to paint a picture of how gender gaps have evolved over time and inwhat context they are most marked. Then we consider possible explanations for the observed gender gaps. We look at therelevance of school inputs, teaching practice, and the examination system for explaining the gender gap. We also discussthe potential influence of wider social and economic changes as reflected, for example, in the much higher educa-tion levels of mothers relative to those of previous generations. Analysis of this issue is important in the context ofresearch on the gender wage gap. However, it is also raises policy-relevant issues in relation to whether changesin the school system can effect a change in the gender gap in educational achievement.

I. INTRODUCTION

Major controversy surrounds examination perform-ance in recent times. The lower educational achieve-

ment of boys relative to girls in English schools hasreceived a great deal of publicity, in particularfollowing publication of results from General Cer-tificate of Secondary Education (GCSE) examina-

1 E-mail addresses: [email protected], [email protected] are very grateful to the British Academy for financial support. We would like to thank Panu Pelkonen, for excellent research

assistance; Matthew Young at the Department for Education and Skills (DfES) for making available the codes for identifying schoolsthat took part in the National Literacy Project and National Numeracy Project; Mike Treadaway of the Fischer Trust and DfESfor providing administrative pupil data sets; and the ESRC for giving permission to use the NCDS, BCS, and the GHS. We thankthe Director of the National Literacy Project, John Stannard, for a very useful discussion and much information, and participantsfrom conferences at ZEW in Mannheim and a CEPR/IZA conference in Ammersee. In particular, we thank Bruno Van der Lindenfor helpful comments. We also thank Margaret Stevens, an anonymous referee, and participants at the Oxford Review’s seminarfor detailed comments on an earlier draft.

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OXFORD REVIEW OF ECONOMIC POLICY, VOL. 21, NO. 3

tions that children take at the end of their years ofcompulsory education. There is currently a sizeable‘gender gap’ of 10.2 percentage points betweengirls and boys who achieve five or more GCSEs atgrades A*–C. This has been deemed ‘unaccept-able’ by the government and some commentatorshave suggested that the government’s performancetargets will not be met if solutions are not found.

The gender gap in educational achievement is nei-ther a new problem nor one confined to achieve-ment at GCSE. There is evidence that, in mostsubjects, the average performance of girls nowexceeds that of boys at all levels of education.International studies such as the Programme forInternational Student Assessment (PISA) suggestthat a ‘gender gap’ in attainment is also an issue inother countries (OECD, 2004)2 and in the USAwomen have been consistently more educated thanmen since the mid-1970s (Charles and Luoh, 2003;Freeman, 2004). As is shown later in this paper,some indicators suggest that this problem has be-come worse over time in the UK (although this is in thecontext of an overall improvement in achievement forboys and girls). An important caveat in this debate isthat GCSE (or indeed any other measure of achieve-ment) does not fully measure the ‘gap’ in humancapital between boys and girls, but rather a gap atthe age at which compulsory schooling ends whichis also coupled with those aspects of achievement thatare deemed important by the education and exami-nation system (which can also change over time).

Many explanations have been put forward for theexistence of a gender gap in achievement. In thenational press, explanations for the comparativelylow performance of boys include ‘too much timewatching football’, an ‘anti-learning laddish culture’,and the ‘teachers in the classroom, the school, and theorganization’.3 There is a large educational literatureabout the role of school characteristics (such aswhether the school is single-sex) and modes of

assessment.4 There are several papers in the econom-ics literature, most of which deal with gender differ-ences in post-compulsory educational outcomes.5 Asnoted by Gorard et al. (2001), few studies deal withthe evolution of the gender gap over time.

In this paper, we analyse changes over time in thegender achievement gap for school-age children inEngland at different stages of compulsory educa-tion, particularly at the end of primary school (age11) and at the end of compulsory education (age 16).We consider the importance of some possible expla-nations for the gender gap—in particular, factorsthat may explain the observed changes over time.Analysis of this issue is important in the context ofresearch on the gender wage gap. However, it isalso raises policy-relevant issues in relation towhether changes in the school system can effect achange in the gender gap in educational achieve-ment. The implication of a gender gap during com-pulsory education is that it may persist to later stagesof education and subsequently into the labour mar-ket. In fact, in the last few years female participationin higher education has risen (and from a higherbase) in comparison with male participation.6

The structure of the paper is as follows. We firstdiscuss the most recent statistics for England, show-ing the gender gap at each stage in the educationsystem (section II). We then describe how thegender gap has evolved over time in primary andsecondary schools using two birth-cohort studiesand more recent administrative data (section III).We also examine (in ‘value-added’ models) whetherthe gender gap has changed at the end of secondaryschool conditional on achievement at the end ofprimary school. Then we provide some empiricalevidence for the role of factors that influence thegender gap: school inputs, teaching practice, and theexamination system (section IV). We then discussthe role of non-school-based factors (section V) anddraw together conclusions (section VI).

2 The OECD study shows that girls had ‘significantly higher average performance’ in reading in all but one of the 40 countriesincluded in the analysis. However, in most countries, boys out-perform girls in maths.

3 BBC News Online, 22 August 2002, ‘Addressing the Gender Gap’.4 There are a number of good reviews, such as Gipps and Murphy (1994); Powney (1996); Arnot et al. (1998).5 In the UK, examples are McNabb et al. (2002) and Smith and Naylor (2001). Burgess et al. (2004) and Gorard et al. (2001)

consider gender differences in educational achievement at school in England and Wales, respectively. See Jacob (2002) and Charlesand Luoh (2003) for the USA.

6 The ‘higher education initial participation rate’ for English-domiciled first-time entrants (full and part time) in higher educationcourses in 1999/2000 was 38 per cent for men and 43 per cent for women. In 2003/4, the statistics were 38 per cent for men and47 per cent for women. http://www.dfes.gov.uk/rsgateway/DB/SFR/s000572/index.shtml

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S. Machin and S. McNally

II. THE GENDER ACHIEVEMENTGAP AT SCHOOL: THE CURRENTSITUATION

National statistics for 2004 reveal the extent of thegender gap in student achievement through theeducation system. The 11 years of compulsoryeducation in England are divided into four ‘KeyStages’ (KS) for different age categories: age 5–7;age 7–11 (the end of primary school); age 11–14;and age 14–16. After each KS, there is a nationalexamination, which is externally set and marked.The government has targets associated with thepercentage of children expected to meet a requiredstandard (as set out in the National Curriculum).

In Table 1, we show the percentage of childrenachieving the government target at the end of KS 1(age 7), KS 2 (age 11), and KS 4 (the GCSEexamination at age 16). The gender gap is shownoverall and also for disadvantaged pupils (i.e. pupilseligible for free school meals) and for pupils whospeak English as a second language. This is basedon administrative data for all school children inEngland.

Table 1 shows the gender achievement gap to beevident throughout the school years, particularly inreading and writing from the age of 7 onwards. It is

also visible in maths, though the differential is muchlower. At GCSE, headline statistics relate to thepercentage of pupils attaining five or more GCSEsat grades A*–C. As discussed above, the genderdifferential is substantial, at 10 percentage points.There is also a gender gap at the lower end of thedistribution—the percentage of children leavingschool without any qualifications at all. Thisapplies to 5 per cent of 16-year-old boys and 3 percent of 16-year-old girls, a gap of 2 percentagepoints.

For children who speak English as an additionallanguage, the percentage of children reaching gov-ernment targets at each stage is lower. However,this is equally true for boys and girls as the gendergap for these pupils does not diverge from theaverage. Poverty (as indicated by free school meals)appears to be a greater source of disadvantage thanlanguage difficulties in terms of whether childrenachieve government targets at each stage of educa-tion. Furthermore, in most cases, the gender differ-ential widens: in terms of educational achievement,there is a greater penalty for being a boy if he is partof a low-income household. It is very notable thatdespite substantial investment in education and ef-forts to help pupils in disadvantaged areas, as manyas 10.2 per cent of boys from low income house-holds still leave school without any qualifications

Table 1Gender Differences in Achievement: National Data, 2004

All pupils Pupils who speak Pupils eligible English as an for free

additional language school meals

Boys Girls Gap Boys Girls Gap Boys Girls Gap

KS 1 (age 7)% achieving target in reading 81 89 –8 75 82 –7 64 76 –12% achieving target in writing 76 87 –11 70 81 –11 58 74 –16% achieving target in maths 89 91 –2 84 87 –3 78 82 –4

KS 2(age 11)% achieving target in English 72 83 –11 65 76 –11 51 66 –15% achieving target in maths 74 73 +1 68 67 +1 55 55 0

GCSE (age 16)Five or more at grades A*–C 47 57 –10 45 57 –12 22 30 –8No qualifications 5 3 +2 5 3 +2 10 7 +3

Source: Department for Education and Skills.

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whatsoever. This applies to 7.3 per cent of girls. Thegender gap of 2.9 percentage points is double thenational average.7

III. EVOLUTION OF THE GENDERACHIEVEMENT GAP OVER TIME

(i) Data on Achievement Over Time

We now consider the evolution of the gender gapover time at the end of primary school (age 11) andat the end of compulsory education (age 16). Weuse a range of measures so as to enable analysisover a long period, focusing on the average gendergap in each case. For earlier periods, we use datafrom the two best-known birth-cohort studies: theNational Child Development Study (NCDS) and theBritish Cohort Study (BCS), longitudinal data sets ofall people born in a particular week of March 1958(NCDS) and April 1970 (BCS).8 With regard tomore recent years, we use administrative data setsfor all pupils in the country (the National PupilDatabase, NPD). In all data sets, there are tests inreading and maths at a similar age (10 or 11). Weconvert marks to a percentile score and consider theraw gender differential and how this has changedover time. We then show the evolution of the gendergap in public examinations at age 16 using these datasets. We examine whether controlling for priorachievement can help to close the gender gapobserved at age 16.

It is important to note that the nature of educationand assessment has changed over time—in particu-lar, following the change in public examinations in1988 (which is discussed in section IV(iii) in somedetail). Therefore, it is difficult to make fully precisestatements about trends over time. However, aclear picture emerges from analysis of this range ofmeasures: girls outperform boys (especially in Eng-lish). There has been no tendency for these differ-ences to disappear over time—if anything, the gapsseem to be widening.

(ii) Primary Schools

In Table 2, we show the gender differential at theend of primary school over time using the data setsdescribed above. We report the average genderdifferential for maths and reading for this age groupin 1969, 1980, 1996, and 2003. With regard to maths,traditionally there has been a small gender gap infavour of boys. The magnitude has fluctuated be-tween 0.79 and 2.71 percentile points on averageover the four time periods. The gender gap is farmore pronounced for reading—and this favoursgirls. On average, there was an increase over thefirst three time periods, moving from a differential of0.44 percentile points (and not statistically signifi-cant) to 4.06 in 1980 and 8.96 in 1996. In the mostrecent time period (2003), the gap has reduced to6.79 percentile points.

(iii) Secondary Schools

In Table 3, we show how the gender gap hasevolved at age 16 using the following indicators:whether the student obtained five or more A*–Cgrades in public examinations at age 16 and whetherhe/she obtained an A*–C grade in maths and Eng-lish. It should be borne in mind that there have beenincreases over time in all these indicators of achieve-ment for both boys and girls. This is shown inAppendix Table 2. Figure 1 (discussed in sectionIV(iii)) shows the percentage of boys and girls whohave obtained five or more A*–C grades in eachyear since 1975. There was a change in the exami-nation system in 1988, which has important implica-tions for the interpretation of the gender gap (seesection IV(iii)).

Across all three indicators, there have been markedchanges over time which favour girls. The overallmeasure of performance (five or more A*–C grades)was small in 1969 (two percentage points), negligi-ble in 1980, and highly pronounced in 1998 and 2003,where it was 9.7 percentage points (favouring girls)in both periods.

7 This compares to a gender gap among students not entitled to free school meals of 1.1 percentage point (favouring girls). Thenumber of boys on free school meals is 41,756 (14 per cent of the total number of boys in maintained schools in England).

8 Both the NCDS and the BCS are nationally representative in terms of results attained in public examinations. We show somerelevant statistics in Appendix Table 1. However, there is a problem with the BCS in that there was a teacher’s strike at the timeof the age 16 survey. Hence the analysis relying on the BCS is not as reliable as that coming from the NCDS or the NPD. It shouldalso be noted that the NCDS and the BCS cover Great Britain, not England alone.

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Table 3Gender Differences in Achievement at the End of Secondary School

(gaps in proportion achieving qualification level, boys relative to girls)

5+A*–C grades Maths A*–C grades English A*–C grades

(1) 1974 NCDS –0.018 0.042 –0.090(0.006) (0.006) (0.007)

(2) 1986 BCS 0.009 0.068 –0.072(0.011) (0.011) (0.012)

(3) 1998 NPD –0.097 –0.010 –0.161(0.001) (0.001) (0.001)

(4) 2003 NPD –0.097 –0.017 –0.154(0.001) (0.001) (0.001)

Notes: Standard errors in parentheses. Sample sizes are (1) 14,331; (2) 6,949; (3) 551,046; 528,780; 521,497;(4) 600,522; 586,218; 578,965.

Table 2Gender Differences in Achievement at the End of Primary School

(percentile gaps, boys relative to girls)

NCDS BCS KS2 KS2Age 11 in 1969 Age 10 in 1980 Age 10/11 in 1996 Age 10/11 in 2003

Maths 0.79 2.65 1.24 2.71(0.49) (0.53) (0.08) (0.07)

Reading –0.44 –4.06 –8.96 –6.79(0.49) (0.51) (0.08) (0.07)

Notes: Standard errors in parentheses; Sample sizes are: NCDS maths, 14,129; NCDS reading, 14,133;BCS maths, 11,706; BCS reading, 12,775; KS2 1996 maths, 564,538; KS2 1996 reading, 560,262; KS2 2003maths, 645,998; KS2 2003 reading, 622,830.

With regard to maths, the gender differential fa-voured boys in 1974 (3 percentage points) and 1986(6.8 percentage points). In 1998, the gap favouredgirls—they were more likely to get an A*–C gradeby 1 percentage point. By 2003, this had risen to 1.7percentage points.

There has always been a strong differential inEnglish which favours girls. There is small differ-ence between the NCDS and the BCS, where thegaps were 9 and 7.2 percentage points, respec-tively. By 1998, the gap had more than doubled to16.1 percentage points. It was slightly lower in 2003,at 15.4 percentage points.

One question is to what extent these patterns aresensitive to differential entry to the examinations—especially bearing in mind that participation wasmuch lower in the earlier cohorts (NCDS and BCS).In general, results are very similar to those reportedin Table 3 if the reference group is the whole birthcohort. The one important difference applies to theBCS, where the coefficient on achievement in mathsreduces from 0.068 to 0.002, suggesting that thegender differential in maths at this time is mainly drivenby differential selection into the examination.9

The next question we consider is whether thesedifferentials are reduced when achievement at age

9 Other differences are as follows: for the NCDS, the gender differential in maths and English changes to 0.029 and –0.075,respectively. For the BCS, the gender differential in 5+ A*–C grades changes to –0.023.

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11 is taken into account. This will be the case if thegender gap at this age explains most of the gendergap observed at the end of secondary school.Results are shown in Table 4. With regard to theoverall measure of performance (five or more A*–Cgrades), there is very little difference. In the mostrecent year, the gap closes by 1 percentage point. Inmaths, the gap closes by over half if we consider theNCDS (to 1.9 percentage points) but widens in themost recent cohort (to 2.3 percentage points). Thisshows that while in the past much of the gender gapin this subject could be explained by a differentialemerging by the age of 11, in more recent times the gapwidens during secondary school. In English, the gapwidens slightly in earlier cohorts and reduces slightlyin later cohorts. Even controlling for prior achieve-ment, the gap is sizeable in each period.

Overall, the gender gap is little changed after takingaccount of prior achievement. This suggests that itcannot be dealt with simply by addressing whatgives rise to the gender gap in primary school (andbefore that). The early teenage years are vitallyimportant in explaining the observed gender gap atage 16. We now consider some possible explana-tions and remedies.

IV. POSSIBLE SCHOOL-BASEDEXPLANATIONS FOR THEGENDER ACHIEVEMENT GAP

(i) School Inputs

One possibility is that the gender gap at a point intime (or changes over time) might be explained bydifferences between schools in terms of resources,gender mix, teachers (and gender of teacher), etc.According to a review by Arnot et al. (1998),attempts over the last two decades to show thatone system of school organization is more effec-tive than another have not yielded much fruit.They report that very little work has focuseddirectly on the question of whether some schools aremore effective for one sex or the other. Burgess etal. (2004) examine this question using the NPD.They compare the gender differential acrossdifferent types of school in terms of good or poorperformance, gender mix, admissions policy, andpercentage of pupils eligible for free school meals.

They find that the gender gap is not affected byany of the leading observable school character-istics.

However, it is possible that the gender gap may beaffected by a combination of observed and unob-served characteristics of schools or pupil intakesthat vary across schools. To examine this possibility,we use the NPD for two adjacent years (2002 and2003) and examine whether the gender gap isreduced when one removes the effects of time-constant school characteristics (through the inclu-sion of school fixed effects) and prior achievementof the student. This is reported below in Table 5,where we show the gender differential withoutcontrolling for school fixed effects (row 1) and alsocontrolling for school fixed effects (row 2). Al-though there are small differences between thesesets of results, there is little change in the gendergap. Hence the average differential cannot beexplained by factors that vary across schools. Thisshould not be interpreted as suggesting that there isnothing schools can do to reduce the gender gap.Rather, these results suggest that variation betweenschools in what they do is not the factor which givesrise to the observed gender gap. One possibility isthat teaching strategies might mitigate factors givingrise to the gender gap.

(ii) Teaching Practice

Researchers often point to differences in the per-sonal characteristics of boys and girls that mayexplain the gender differential in achievement. Salis-bury et al. (1999) suggest that girls and boys preferto learn in different ways and that boys get boredmore readily as their levels of concentration arelower and organizational skills poorer than girls.Jacob (2002) points to poor ‘non-cognitive’ skillsamong boys, including inability to pay attention inclass, to work with others, to organize and keeptrack of homework or class materials, and to seekhelp from others. He finds such non-cognitive skillsto be a very important reason for gender differencesin college attendance rates in the USA. He statesthat it would be interesting to know whether certainschool characteristics foster the development ofsuch skills and if certain types of curriculum, peda-gogy, or learning environments are more effectivefor one gender than the other.

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Table 5Gender Differences at the End of Secondary School:

Controlling for School Inputs and Value Added(gaps in proportion achieving qualification level, boys relative to girls,

conditional upon KS 2 performance)


(1) 2003 and 2002 KS data –0.070 –0.014 –0.117(0.001) (0.001) (0.001)

(2) As (1), school fixed effects –0.072 –0.011 –0.125(0.001) (0.001) (0.001)

Notes: OLS regressions. Coefficient on dummy for boys reported; standard errors in parentheses (clusteredat school level in row 2); The sample sizes are 1,190,237; 1,156,903; 1,141,296. Controls for reading score,age 11, maths score, age 11, missing variable dummies for maths and English, and year dummy.

Table 4Gender Differences at the End of Secondary School: Value-added Model

(gaps in proportion achieving qualification level, boys relative to girls)


(1) 1974 NCDS –0.021 0.019 –0.113(0.004) (0.003) (0.007)

(2) 1986 BCS –0.008 0.053 –0.098(0.011) (0.012) (0.013)

(3) 2003 NPD –0.087 –0.023 –0.140(0.001) (0.002) (0.001)

Notes: Probit regressions. Marginal effect on dummy for boys reported; standard errors in parentheses;sample sizes are (1) 14,331; (2) 6,949; (3) 600,522; 586,218; 578,965.

There has been much interest in the effect ofstrategies such as single-sex teaching (e.g.Younger and Warrington, 2003), although re-views of this literature point to no conclusiveevidence that single-sex schooling is better thanco-educational schooling (Elwood and Gipps, 1999;OfSTED, 2003).10 Other strategies suggested todeal with gender differences in performance in-clude mentoring and role-modelling (West andPennell, 2003) and grouping arrangements (Franciset al., 2002). In terms of large-scale changes inteaching practice that may help to explain observedchanges in the gender gap since the late 1990s, the

National Literacy and Numeracy Strategies may beimportant. One might expect the highly structuredmethod of teaching introduced as a result of thesestrategies (‘the literacy hour’, ‘the numeracy hour’)to help deal with low ‘non-cognitive’ skills amongboys. Indeed, the School Inspectorate for Englandreports that boys often respond better to lessons thathave a clear structure (OfSTED, 2003). The SchoolInspectorate in Wales reports that boys are morelikely to respond negatively to poor teaching throughdisengagement and indifference or through disrup-tive behaviour (OHMCI, 1997). Hence it might bethought that the literacy hour and numeracy hour

10 Looking at the NPD (2003), the gender gap between boys and girls in terms of the percentage obtaining five or more GCSEsis lower in single-sex schools (6 per cent) than in mixed schools (8 per cent), after controlling for prior attainment at KS 2. However,according to Burgess et al. (2004), there is a high degree of collinearity between ‘single-sex’ status and whether the school is a grammarschool. Furthermore, there may be differential selection into single-sex schools according to other pupil characteristics. Hence, alower gender gap given entry into a single-sex school is not evidence of the efficacy of single-sex teaching.

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would be particularly beneficial for boys. Thesestrategies aim to raise standards of literacy andnumeracy in primary schools by improving thequality of teaching through more focused instructionand effective classroom management. Key compo-nents are a framework for teaching, which setsout termly teaching objectives for the 5–11 agerange and provides a practical structure of time andclass management for daily literacy and numeracyhours. Before the introduction of the National Strat-egies, they were introduced into a subset of LocalEducation Authorities (LEAs) in the context of theNational Literacy Project (NLP) and the NationalNumeracy Project (NNP). The literacy hour wasintroduced to particular LEAs between September1996 and 1998 (when the policy was rolled outnationally). The numeracy hour was set up withindifferent LEAs between September 1996 and 1999(when the policy was rolled out nationally).11 Machinand McNally (2004) explain the details of the ‘lit-eracy hour’ and its evaluation in some detail. In

brief, we aim to see whether the ‘literacy hour’ and‘numeracy hour’ had a differential impact by genderby comparing schools where the respective strate-gies were introduced before the national roll-outrelative to similar schools, where they were notintroduced. We implement a ‘difference-in-differ-ences’ strategy since we compare treatment andcontrol schools before and after the respectivepolicies were introduced.12 The ‘policy on’ yearsare school years 1996/7 and 1997/8 and the ‘policyoff’ year is 1995/6.13 The regressions control for arange of school characteristics and school fixedeffects.

In Table 6, we report the ‘difference-in-difference’coefficient for the NLP and NNP. There are fouroutcome variables. With regard to the NLP, theyare as follows: the probability of attaining the re-quired standard or above at age 11 (‘level 4’) inEnglish and the percentile score in reading. For theNNP, they are the probability of attaining the re-

11 The literacy hour and numeracy hour were introduced in different schools in the context of the NLP (1996–8) and the NNP(1996–9). They are largely within different LEAs (a deliberate policy). Furthermore, it was intended that non-participating LEAswould not learn about these strategies (at least not formally).

12 Control schools are in LEAs that are geographically adjacent to schools in treatment LEAs, with a similar prior educationalperformance. See Machin and McNally (2004) for further details.

13 Although we could have used one more ‘policy on’ year for the NNP, we know that many schools implemented the ‘numeracyhour’ the year before the national roll-out (as discussed with John Stannard, former director of the National Literacy Project andNational Literacy Strategy).

Table 6The Role of Teaching Strategies

Boys Girls

(1) Proportion Level 4 or aboveLiteracy hour 0.042 0.021

(0.012) (0.011)Numeracy hour 0.025 0.038

(0.010) (0.011)(2) Percentile score

Literacy hour 3.412 1.781(0.741) (0.752)

Numeracy hour 1.969 2.135(0.630) (0.658)

Notes: OLS regressions. Standard errors (clustered on school) in parentheses; all specifications includeyear dummies, a range of school characteristics, and school fixed effects (interacted with gender). Samplesizes are 104,608 for the literacy hour and 140,537 for the numeracy hour. See Machin and McNally (2004)for a detailed explanation of the data and methodology with regard to the literacy hour. Analysis for thenumeracy hour is done in a similar way, using the same set of controls. The treatment and control groupsof schools are different for the literacy hour and the numeracy hour.

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0

10

20

30

40

50

60

1975 1980 1985 1990 1995 2000 2005

Figure 1Percentage of Students Achieving Five or more A*–C Grades in Examinations at Age 16

Source: Department for Education and Skills.

quired standard or above in maths and the percentilemaths score.

The results show that both strategies were effectivefor boys and girls. However, the magnitude of theimpact is greater for the gender that is generallyweaker in a particular subject. Hence, with regardto English, the ‘literacy hour’ had a greater relativeimpact on boys, raising the probability of attainingthe required standard by 4.2 percentage points(compared to 2.1 percentage points for girls) and thereading score by 3.412 percentile points (as com-pared to 1.781 for girls). In contrast, the ‘numeracyhour’ had a greater relative impact on girls, raisingthe probability of attaining the required standard inmaths by 3.8 percentage points (compared to 2.5percentage points for boys) and the maths score by2.135 percentile points (compared to 1.969 forboys). Although these results are consistent with theidea that the ‘literacy hour’ in particular is helping tomitigate the poor non-cognitive skills of boys, theyare also consistent with a more general explanation:whatever the reasons for the differential performanceof boys and girls in maths and English, a better way ofteaching these subjects disproportionately helps theweaker student: traditionally boys have been weakerin English and a little stronger in maths at age 11.With regard to changes in the gender differentialbetween 1996 and 2003 (observed in Table 2), theintroduction of these national strategies is consistentwith the narrowing of the gender gap with respect

to reading and the widening of the gender gap withrespect to maths at age 11.

(iii) The Examination System: O-levels toGCSEs

Although the literacy and numeracy strategies mayhelp to explain changes in the gender differentialover time at primary school, they are too recent tohave an impact on the gender gap at secondaryschool that widened so dramatically between 1986and 1998. A vital clue as to the possible explanationcan be obtained by observing the whole time seriesof achievement at age 16 from the mid-1970s to thepresent time. In Figure 1, we show (by gender) thepercentage of students achieving five or more A*–C grades in the examination at age 16.

The gender gap in this measure of achievement wasvery slight or non-existent between 1975 and 1987.From 1988, there was a divergence, which quicklyincreased and then subsequently displayed verylittle variation. The National Curriculum was intro-duced by the 1988 Education Reform Act (whichreduced the scope for specialization in particularsubjects). This was also the year in which the GCSEexamination (General Certificate of SecondaryEducation) replaced O-levels (the General Certifi-cate of Education, ordinary level). As described byGipps and Murphy (1994), this reform involved anumber of important changes. Importantly, there

girls

boys

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was a move away from measuring performance inrelation to peers to ‘criterion-based assessment’.This ended rationing of the top grades. Many morepupils were entered for GCSE than for O-levels.14

Given the timing of the change in the gender gap, itseems reasonable to infer that the change in exami-nation system was a major contributory factor. Oneof the consequences was the enhanced role given tocoursework (i.e. continuous assessment by teach-ers) in the GCSE system. Initially, the weighting ofthe continuous assessment component varied from20 to 100 per cent depending on the subject and onthe syllabus offered by the centres responsible forthe GCSE examination. The permissible weightgiven to the continuous assessment component hasreduced over time. The coursework is marked bythe teacher of the pupil and moderated by someoneexternal to the school.

The importance of coursework in the GCSE exami-nation is likely to be a key explanation for theemergence of the gender gap at this time. Powney(1996) cites a number of studies showing that themode of assessment is a factor explaining thedifferential performance of boys and girls. Theyshow that boys tend to be favoured by multiple-choice questions and girls by essays and course-work.15 In the present context, Stobart et al. (1992)find a direct relationship between the relative im-provement in girls’ achievement and the weightingand type of coursework required in different sub-jects for GCSE between 1988 and 1990. It is moredifficult to identify the reasons for this. Gipps andMurphy (1994) cite evidence showing that femalesdo less well in timed examinations owing to higherlevels of anxiety.

However, it is unlikely that the relative advantage ofgirls in the GCSE system was entirely driven by thecoursework component. According to Elwood(1995), the gender gap did not reduce in parallel withthe restriction of the coursework component to 40

per cent of the overall score for English from 1994onwards. However, she suggests that both theexamination and coursework material in GCSEEnglish emphasize aspects of the subject wheregirls are more proficient—large amounts of ex-tended writing ‘may be putting boys at a disadvan-tage, but this is compounded by boys’ own devalu-ation of the subject’. Also, coursework is a relativelysmall component in GCSE maths, but the syllabus inGCSE is very different to that for O-level. Hence,an important reason why a gender gap might emergeto coincide with a change in the examination systemis a gender differential in skills that are taught andtested in different types of system (as well as themode of assessment). This implies that an apparentgender gap can emerge in measured outcomes,whereas there might be no change if boys and girlswere tested over time using the same mode ofassessment and based on the same syllabus. Yet,even in this case the phenomenon would be ofsubstantive interest since performance at GCSEmatters for what students go on to achieve in theeducation system and in the labour market. InAppendix Figure 1, we show the evolution of thegender gap at A-level (i.e. school leavers with twoor more A-levels as a percentage of the 17-year-oldpopulation).16 The emergence of a gender gapfavouring girls at A-level is consistent with thehypothesis that transition to the GCSE system hadconsequences for subsequent educational outcomes.

V. RELEVANCE OF NON-SCHOOL-BASED FACTORS

There are many other factors that may be relevantin explaining the gender gap at a point in time or itsevolution over time. In an economic, Becker-typemodel, the education of children is viewed as afamily investment (Haveman and Wolfe, 1995).The essence of such models is that children beginlife with ‘inherited ability’ and parents make subse-quent investments, influenced by preferences, in-

14 Together with the introduction of the National Curriculum, this may explain why the differential entry by gender intomathematics has reduced over time. For example, for those entering the exam in 1974 (i.e. in the NCDS survey), 33 per cent ofboys entered the maths exam compared to 27 per cent of girls. The equivalent numbers for 2003 (from administrative data sets)are 97.4 per cent for boys and 97.8 per cent for girls.

15 With regard to performance in multiple choice, this is often attributed to less willingness on the part of girls to guess, preferringto respond only where they are confident (Powney, 1996).

16 A-levels are the academic qualifications that students may pursue after they obtain their qualifications for GCSE/O-levels (andexaminations are held 2 years later). In most cases, students must obtain the equivalent of at least two A-levels to proceed to highereducation.

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come, and fertility. A question arising from this iswhether factors influencing parental investmentdecisions have changed over time in a way to affectthe gender differential in educational achievement.Possible candidates are (i) the rise of women’seducation over time—and hence a change in thehuman capital of mothers; (ii) the rise in householdincome over time. With regard to the former, thesocial and cultural changes over recent decades thathave changed women’s participation in the labourforce and the incentive for women to obtain educa-tion might have a stronger impact on their daughtersthan on their sons, since it may change the daugh-ter’s expectation of her own future and the prefer-ence of mothers for investing in their daughters’education. With regard to the second issue, a rise inhousehold income might be expected to increaseinvestment in the education of sons and daughters.Blanden et al. (2005) show that the relationshipbetween income and education has become strongerover time in the UK. Whether this change has astronger impact on sons or daughters depends onfactors such as the mechanism giving rise to thehigher income (e.g. which parent receives the in-come) and household preferences regarding invest-ment decisions.

To investigate the importance of such issues, weexamine how the gender gap changes for the NCDS

and BCS cohorts when controls for parental educa-tion and parental income are included (Table 7). Inboth cases, there is almost no change in the gendergap.17 This is also the case when one uses morerecent data (as reported in Appendix Table 3, usingthe General Household Survey).

However, there are other studies that suggest animportant role for economic factors in explaining thegender differential in educational achievement. Forexample, Jacob (2002) shows that higher wagereturns are an important reason for the collegeattendance gap between men and women in theUSA. Charles and Luoh (2003) show that theanticipated dispersion of future wages is importantin explaining gender differences in completed yearsof schooling in the USA. Although such factors areused to explain variation in educational decisions ata later stage—post-compulsory schooling deci-sions—it is entirely possible that such considera-tions affect achievement prior to school-leaving.UK evidence shows that the wage returns to edu-cational qualifications are higher for women than formen. Machin (2005) shows that the average wagereturn to degree-level qualifications increased fasterfor women than for men from 1985 to 1990. How-ever, from 1990 onwards, the average return to adegree changed very little for women, whereas itcontinued to rise for men. It seems likely that wage

Table 7Gender Achievement Gaps and Parental Education and Income

(5+ A–C O-levels, boys relative to girls)

NCDS Age 16 BCS70 Age16

(1) Basic value-added specification –0.021 –0.008(0.004) (0.011)

(2) (1) plus parents’ education –0.020 –0.011(0.004) (0.011)

(3) (1) plus parental income –0.018 –0.008(0.004) (0.014)

(4) (1) plus parents’ education and parental income –0.018 –0.010(0.004) (0.014)

Notes: Standard errors in parentheses. Sample sizes range from 9,025 in (4) to 14,257 in (1) for NCDS, andfrom 4,846 in (4) to 7,307 in (1) for BCS70. The same pattern of results emerges if restricted to the smallestsample size within each cohort. All specifications include age 10/11 maths and reading test scores.

17 Of course, parental education and income are important determinants of GCSE performance themselves, but this is true forboth boys and girls, and thus they do not explain the existence of a gender achievement gap.

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returns to qualifications affect the incentive for boysand girls to work hard at school—though it is harderto believe (especially given Figure 1) that the timingof the change in the gender achievement gap at age16 is related to contemporaneous trends in the wagereturn to qualifications.

VI. CONCLUSIONS

Girls now outperform boys in most subjects at allstages of compulsory education in England. Therelative under-performance of boys is raised timeand again as a serious policy concern. Questionsarise as to what causes the gender gap and whetherthere is any role for policy in advocating methods toreduce it.

We show how the gender gap has evolved over timein English schools at the end of primary and second-ary education. With regard to primary school, themore important change over time has been in read-ing, where the gender gap favouring girls is morepronounced than it was in the past. However, thegap has reduced between the mid-1990s and thepresent. The gender gap in secondary schools hasdisplayed greater change over time. This has beenparticularly dramatic for the overall indicator ofperformance (whether the student obtains five ormore A*–C grades). It is also true for specificsubjects in secondary school: the relative perform-ance of boys used to be higher in maths—now theopposite is true; girls always performed better inEnglish than boys, but the gender differential hasdoubled since the mid-1980s. Furthermore, acrossall indicators, the gender gap at age 16 is not stronglyinfluenced by whether or not we take account ofprior achievement at age 11. This suggests thatcauses of the gender gap (and possible solutions)should not be thought of only in relation to youngchildren. From this analysis, it appears that theexplanation for changes in the gender gap over timeis to be found in the teenage, secondary school,years—and not in early experience at school or athome.

We consider some possible explanations for thegender gap. We find that variation in school-levelcharacteristics in secondary schools across Eng-land cannot be used to explain the average genderdifferential in achievement. This does not mean that

school practices are unable to address gender-specific learning difficulties. We show that both theNational Literacy and the National Numeracy Strat-egies have had a differential impact by gender. Theimpact of these highly structured methods of teach-ing literacy and numeracy has been greater on thegender that is traditionally weaker in a particularsubject. Hence, the ‘literacy hour’ had a morepositive impact on boys, whereas the ‘numeracyhour’ had a stronger impact on girls. The evidencepresented here is consistent with the argument thatthese strategies have influenced the observed trendin the gender differential at age 11 in recent years.

These strategies are too recent to have had animpact on trends in the gender achievement gap atage 16. It is very notable that the change in thegender gap at age 16 coincides exactly with theintroduction of the GCSE examination. This seemslikely to be the primary factor responsible for changesin the gender gap since 1988. There is evidence tosuggest that the importance of coursework in theGCSE exam is a reason for the high relative per-formance of girls. It may not be the only reason—other factors could include assessor bias or a genderdifferential in skills that are rewarded by assess-ment in GCSE.

Finally, one might think that large social and eco-nomic changes which affect girls and boys differ-ently would influence their relative achievement atage 16. For example, the large increase over time inthe education and labour-market participation ofmothers might be important. However, includingcontrols for parental education and income does nothelp to explain the gender gap in educational achieve-ment. Other studies point to the importance ofrelative wage returns in explaining gender differen-tials in post-compulsory education. It is likely thatsuch considerations could also be relevant for influ-encing the incentive to work hard at school. Buttrends over time in relative wage returns are unlikelyto explain the specific timing of the emergence ofthe gender gap in educational achievement at age16. The most compelling evidence for this comesfrom a change in the examination system. Taken inconjunction with the evidence from the literacy andnumeracy strategies, it is therefore evident thateducation policy can have an impact (whetherintended or unintended) upon the achievement gapbetween boys and girls.

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Appendix Table 1Comparing Cohort and National Data

(proportion achieving given qualification)

All Boys Girls

1975 National data and the NCDS5+ O-levels A–C

National data 0.23 0.22 0.23NCDS 0.18 0.17 0.18

English O-level A–C for entrantsNational data 0.55 0.66NCDS 0.69 0.78

Maths O-level A–C for entrantsNational data 0.59 0.53NCDS 0.76 0.70

1986 National data and the BCS5+ O-levels A–C

National data 0.27 0.26 0.27BCS 0.31 0.32 0.31

English O-level A–C for allNational data 0.41 0.35 0.46BCS 0.43 0.39 0.46

Maths O-level A–C for allNational data: % leavers 0.32 0.35 0.30BCS 0.33 0.37 0.30

Appendix Table 2Gender Differences at End of Secondary School

(proportion achieving given qualification)


Boys1974 NCDS 0.17 0.20 0.231986 BCS 0.32 0.37 0.391998 KS Data 0.44 0.47 0.482003 KS Data 0.50 0.50 0.57

Girls1974 NCDS 0.18 0.15 0.321986 BCS 0.31 0.30 0.461998 KS Data 0.53 0.48 0.642003 KS Data 0.60 0.52 0.73

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Appendix Table 3Gender Gaps and Parental Education and Income, Evidence from the General Household

Survey (five or more grades at A*–C in GCSE/O-level, boys relative to girls)

Years Sample size Basic gender gap Plus parental Plus parental Plus parentaleducation earnings education and earnings

1977–9 1,467 –0.002 –0.007 –0.004 –0.007(0.021) (0.018) (0.021) (0.018)

1978–80 1,506 0.000 –0.002 –0.001 0.000(0.021) (0.020) (0.021) (0.020)

1979–81 1,593 0.007 0.000 0.005 0.003(0.020) (0.020) (0.021) (0.020)

1980–2 1,516 0.026 0.024 0.026 0.031(0.021) (0.021) (0.021) (0.021)

1981–3 1,396 0.029 0.030 0.029 0.035(0.022) (0.022) (0.022) (0.022)

1982–4 1,221 0.026 0.025 0.029 0.031(0.024) (0.024) (0.024) (0.024)

1983–5 1,148 0.001 0.002 0.002 0.005(0.025) (0.025) (0.025) (0.025)

1984–6 1,129 –0.004 –0.005 –0.003 –0.002(0.025) (0.025) (0.025) (0.025)

1985–7 1,097 –0.028 –0.031 –0.028 –0.032(0.026) (0.026) (0.026) (0.026)

1986–8 975 –0.042 –0.038 –0.038 –0.038(0.026) (0.026) (0.026) (0.026)

1987–9 857 –0.067 –0.063 –0.068 –0.064(0.026) (0.026) (0.026) (0.026)

1988–90 771 –0.050 –0.041 –0.044 –0.038(0.026) (0.026) (0.026) (0.026)

1989–91 746 –0.066 –0.066 –0.061 –0.063(0.027) (0.027) (0.027) (0.027)

1990–2 718 –0.071 –0.062 –0.055 –0.055(0.028) (0.028) (0.028) (0.028)

1991–3 666 –0.120 –0.106 –0.114 –0.105(0.029) (0.030) (0.030) (0.030)

1992–4 696 –0.089 –0.077 –0.097 –0.078(0.032) (0.033) (0.032) (0.033)

1993–5 709 –0.124 –0.126 –0.135 –0.128(0.034) (0.036) (0.035) (0.036)

1994–6 790 –0.095 –0.116 –0.111 –0.121(0.035) (0.037) (0.036) (0.037)

Note: Standard errors in parentheses.

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0

5

10

15

20

25

30

1975 1980 1985 1990 1995 2000 2005

Appendix Figure 1Gender Differences at A-level: School Leavers with Two or more A-levels as a Percentage

of the 17-year-old Population

Source: SCAA (1996). 1975–87: from the Department of Education and Science, ‘Statistics of Education’CSE and GCSE; 1989–91: ‘Schools Examination Survey’; 1992–5: ‘School Performance Database’. Databased on A-level candidates of all ages in England, Wales, and Northern Ireland.

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