04 SES 14 A, Impacts of Labelling Students with Special Educational Needs – Theory and Empirical Evidence
A general cross-national pattern is that boys outnumber girls among special education (SE) students, and the same is true for children from low versus high SES families (Dyson & Gallannaugh, 2008; Hibel et al., 2010). These observations raise the question of whether SE placement is truly due to students’ emotional, behavioral, and/or learning difficulties, or if cultural selection and bias play an influential role when students are assigned to SE. The large expenditures on SE also makes it important to ensure that those in need of SE are indeed offered it. In addition to the important question of whether selection into SE is somewhat due to cultural bias, is the ongoing debate of to what degree SE is helpful for enhancing the academic achievements of children in need. Despite of extensive research on SE, the efficacy of these well-intended, yet costly efforts remains unclear, and this is related to the cross-sectional design of most studies to date, and the use of observational data. Nevertheless, the results of longitudinal studies, using methods to account for a large number of potential confounders, show that the evidence for a strong benefit of SE for improving academic achievements is not very compelling (e.g. Dempsey & Valentine, 2017; Sullivan & Field, 2013). Based on all of the above, we need to ask what are the real benefits and costs of maintaining a system of SE practices? The aim of the current presentation is twofold; First, we will review the findings of the most well-designed studies related to selection into SE, and the effects of SE on children’s academic achievements. Second, results from The Trondheim Early Secure Study will be presented (e.g. Kvande et al. 2017; Kvandeet al., 2018). Based on a community sample of n=1000 Norwegian children, we have examined the role of gender and socio-economic status for selection into SE services from 3rd to 5th grade – and the effect of SE on children’s academic achievements and task motivation from 1st to 5th grade. In the effect study we have combined two methods to account for potential confounders, propensity scoring and fixed effects regression, which has the advantage of ruling out all time-invariant confounders (e.g. genetics). Although results reveal support for the differential-needs hypotheses in terms of selection into SE, evidence of SE as effective in order to improve academic performance and task motivation was not supported.
Dempsey, I., & Valentine, M. (2017). Special Education Outcomes and Young Australian School Students: A Propensity Score Analysis Replication. Australasian Journal of Special Education, 41(1), 68-86. doi:10.1017/jse.2017.1 Hibel, J., Farkas, G., & Morgan, P. L. (2010). Who Is Placed into Special Education? Sociology of Education, 83(4), 312-332. doi:10.1177/0038040710383518 Kvande, M. N., Belsky, J., & Wichstrøm, L. (2017). Selection for special education services: the role of gender and socio-economic status. European Journal of Special Needs Education, 1-15. doi:10.1080/08856257.2017.1373493 Kvande, M. N., Bjørklund, O., Lydersen, S., Belsky, J., & Wichstrøm, L. (2018). Effects of special education on academic achievement and task motivation: a propensity-score and fixed-effects approach. European Journal of Special Needs Education, 1-15. doi:10.1080/08856257.2018.1533095 Nordahl, T., & Sunnevåg, A. (2008). Spesialundervisningen i grunnskolen: stor avstand mellom idealer og realiteter [The ideal versus the reality of special education in elementary school]. Hedmark, Norway: Hedmark University of Applied Sciences. Pihl, J. (2010). Etnisk mangfold i skolen: det sakkyndige blikket [Ethnic Diversity in the School Setting]. Universitetsforlaget AS. Sullivan, A. L., & Field, S. (2013). Do preschool special education services make a difference in kindergarten reading and mathematics skills?: A propensity score weighting analysis. Journal of School Psychology, 51(2), 243-260. doi:10.1016/j.jsp.2012.12.004
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