How can we enhance enjoyment of secondary school? The student view
Stephen Gorard & Beng Huat See
This paper considers enjoyment of formal education for young people aged 14 to 16, largely from their own perspective, based on the view of around 3000 students in England. The data include documentary analysis, official statistics, interviews and surveys with staff and students. Enjoyment of school tends to be promoted by factors such as successful social relationships, small classes, variation in learning and students having some control of their learning. Enjoyment tends to be inhibited by perceived lack of respect or concern by teaching staff and passive pedagogy. For some disengaged students, a work or college environment with more adult relationships appears to restore enjoyment and enthusiasm. Enjoyment, unlike attainment, for example, is not particularly stratified by the standard student background variables. Nor is there evidence of a clear school effect. This means that enjoyment should be easy to enhance more widely, positively affecting the learner identities of all young people, including the more reluctant learners.
To cite this article: Stephen Gorard & Beng Huat See (2011): How can we enhance enjoyment of secondary school? The student view, British Educational Research Journal, 37:4, 671-690
To link to this article: http://dx.doi.org/10.1080/01411926.2010.488718
The propagation of errors in experimental data analysis: a comparison of pre- and post-test designs
Experimental designs involving the randomization of cases to treatment and control groups are powerful and under-used in many areas of social science and social policy. This paper reminds readers of the pre- and post-test, and the post-test only, designs, before explaining briefly how measurement errors propagate according to error theory. The substance of the paper involves a series of comparisons using the same measurements, all assumed to have a small initial error, and seeing what would happen to that error in the two different experimental designs. The findings from these calculations and simulations are that although post-test only and pre- and post-test designs yield different ‘manifest’ results with the same data, the substantive conclusions drawn would be similar in most real-life situations. However, if these manifest results are assumed to be in error, stemming from small initial errors in the measurements at pre- and post-test, then these substantive conclusions could be completely wrong. In one example, the pre- and post-test designs propagate an initial maximum measurement error of 10% to an error of over 60,000% in the answer. In general, and perhaps counter-intuitively, the post-test only results are less misleading. The paper ends by summarizing the lessons drawn. The key message is that all other things being equal, the post-test only design is to be preferred. We may also need to use bigger samples, and more strictly accurate measures, capable of objective calibration focus on seeking larger effect sizes.
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How Unstable are ‘School Effects’ Assessed by a Value-Added Technique?
Stephen Gorard, Rita Hordosy, Nadia Siddiqui
This paper re-considers the widespread use of value-added approaches to estimate school ‘effects’, and shows the results to be very unstable over time. The paper uses as an example the contextualised value-added scores of all secondary schools in England. The study asks how many schools with at least 99% of their pupils included in the VA calculations, and with data for all years, had VA measures that were clearly positive for five years. The answer is – none. Whatever it is that VA is measuring, if it is measuring anything at all, it is not a consistent characteristic of schools. To find no schools with five successive years of positive VA means that parents could not use it as a way of judging how well their primary age children would do at age 16 in their future secondary school. Contextualised value-added (CVA) is used here for the calculations because there is good data covering five years that allows judgement of its consistency as a purported school characteristic. However, what is true of CVA is almost certainly true of VA approaches more generally, whether for schools, colleges, departments or individual teachers, in England and everywhere else. Until their problems have been resolved by further development to handle missing and erroneous data, value-added models should not be used in practice. Commentators, policy-makers, educators and families need to be warned. If value-added scores are as meaningless as they appear to be, there is a serious ethical issue wherever they have been or continue to be used to reward and punish schools or make policy decisions.
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To cite this article: Gorard, S., Hordosy, R. and Siddiqui, N. (2013) How stable are ‘school effects’ assessed by a value-added technique?, International Education Studies, 6: 1, 1-9, http://dx.doi.org/10.5539/ies.v6n1p1
Does the index of segregation matter? The composition of secondary schools in England since 1996
This paper presents a new analysis of segregation between schools in terms of pupils living in poverty, for all secondary schools in England from 1996 to 2005. This shows that the clustering of similar pupils in specific schools increased noticeably from 1996 to 2001, but then settled at a level still below that of 1989 when official records began. The analysis uses four estimates of segregation using figures for take-up of, and eligibility for, free school meals compiled to create both the dissimilarity index and what has been termed the Gorard index of segregation. All four estimates give the same substantive results and the findings for the dissimilarity index and the Gorard index of segregation using either measure of free school meals are indistinguishable. The two indices are, therefore, measuring the same thing. However, the Gorard index of segregation is again shown to be more tolerant of the precise measure being used and so more strongly composition invariant than the dissimilarity index. This has important implications both for the past debate on how to measure segregation between schools and for how education authorities go about estimating segregation in the future.
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To cite this article:Gorard, S. (2009) Does the index of segregation matter? The composition of secondary schools in England since 1996, British Educational Research Journal, 35: 4, 639-652
The impact of socio-economic status on participation and attainment in science
Stephen Gorard and Beng Huat See
In this paper we combine the findings from two recent studies relating to
participation and attainment in school science – a re-analysis of existing official
data for England and a review of wider international research evidence in the
literature relevant to the UK. Although the secondary data are drawn mainly
from England, the comprehensiveness of these datasets, together with our
inclusion of a review of international studies on maths and science participation
provides a useful reference point for an international audience. The research was
prompted by concerns over a reduction in the uptake of the physical sciences
post-16 and especially in higher education and interest in ways of encouraging
the study of science by students from less prestigious socio-economic status
backgrounds. Such concerns are not unique to the UK. Using large-scale official
datasets we show that participation and attainment in science are stratified by
socio-economic status. Students from poorer families are less likely to take
sciences at post-16 than many other subjects and those who do are then less
likely to obtain grades high enough to encourage further study of the subject. No
conclusive evidence has been found to explain this satisfactorily. Plausible
reasons suggested in the literature include the relative scarcity of local
opportunities putting off those who do not wish to study away from home or the
perceived time demands of studying science, and so the difficulties of combining
part-time study and part-time work for those needing to continue earning while
studying. Direct support from professional parents may also lead to greater
participation in post-16 science for students from higher SES. Perhaps the
simplest explanation is that participation in science at any level is often
predicated upon success at the previous educational stage. There are clear
differences in science attainment at age 16 between students of differing
backgrounds, which could explain the subsequent differential participation.
However, these differences are not dissimilar to those for all subjects. The
largest gap presented in the paper is between students eligible and not eligible
for free school meals. We also show that these patterns appear early in the life of
children. At ages 7 and 11, attainment in the three core subjects (English, maths
and science) is negatively related to living in an area of deprivation. The paper
ends with a discussion of suggestions for research, policy and practice emerging
from this review of the evidence.