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Mapping prevalence of children with SLCN

Why?

We know there is huge variation in the incidence of SCLN across schools and different types of students. This is because the assignment of children to different types of SCLN provision is a discretionary decision of either teachers or other professionals such as educational psychologists. Practices vary in different settings and as a result there is substantial variation in SCLN provision across schools and LAs. It is essential that we better understand the extent of such LA variation and in particular how the incidence of SLCN varies across school type, geographical area and pupil characteristics. We also want to know whether assignation of a pupil to the SCLN category and the accompanying support appears to improve pupil outcomes. Differences in patterns of provision across LAs mean that children with similar Speech, Language and Communication needs receive different support in different areas. We ask whether these differences in support then impact on pupil outcomes.

There are also important issues in relation to different demographic variables such as ethnic group, gender and economic disadvantage. Previous research with the pupil level School Census (SC) (Strand & Lindsay, 2008) has suggested that differential patterns of identification exist. For example Chinese, Black African and Black Caribbean students are over-represented among those identified with SLCN relative to White British students. Controls for socio-economic disadvantage, sex and age reduced the degree of over-representation of the Black groups somewhat, although they remain over-represented, but did not effect the identification of Chinese students who remained twice as likely to be identified with SCLN as their White British peers. Distinctive patterns of over- and under-representation were also identified for Autistic Spectrum Disorders (ASD) and Hearing Impairment (HI).

How?

We will use administration education data from the National Pupil Database and the Pupil Level School Census that can help us map the entire population of SLCN children in England. We can identify their characteristics, in terms of such indicators as whether they are eligible for Free School Meals, gender and ethnicity. Furthermore, we can identify which areas and schools they are located in. We can then use multivariate regression analysis to consider the following questions:
• What is the incidence of SLCN among different demographic groups?
• What is the association between child level factors and identification of a Speech, Language and Communication Need?
• What are the trends in over- or under-representation in the national data over the period 2005-2009?
• What is the educational achievement of SLCN pupils in different settings mindful of the fact that a) individuals with SLCN have differing levels of de facto support and provision that is difficult to identify in the data and b) that establishing causality is problematic?
• What are the flows of resources for SLCN and how they are allocated to children?

In terms of methodology we will use an adapted Contextualised Value Added model for this research (Ray, 2006). CVA adjusts schools’ expected performance to take into account not only of the prior attainment of students but also some other pupil and school characteristics associated with performance differences that are outside a school’s control, such as whether a child is eligible for free school meals and whether she or he has special educational needs. Such models can be adapted to examine the value added or progress made by particular sub-groups of students, in this case students with SCLN.

Outcomes?

The outcomes from this project will be:
• A map of SLCN incidence across the pupil population in England
• An indication of the extent of over and under-representation in SLCN, ASD and HI by ethnicity, gender and economic disadvantage, and whether there are any trends in the national data over the period 2005-2009?
• Identification of measurable flows of resources being allocated to SLCN and the problems inherent in identifying resource flows
• Better understanding of the relative achievement of SLCN pupils in different contexts.