04 SES 05 A, Secondary Education
In this paper, we study how Finnish special education students move on to post-compulsory education and complete their studies at the upper secondary level after completing comprehensive school. We also examine the effect of special education students on share of students continuing studies at the upper secondary education. With these models, our purpose is to evaluate the effect of special education. We estimate fixed effects models with school fixed effects (capturing time constant unmeasured school effects) and test the effect of share of special education students on several different dependent variables. They include the percentage students continuing studies at the secondary school level in the first, second and third year after completing comprehensive school. As our other independent variables we use different measures of socioeconomic status of students, school resources, resources for special education and school size. The data covers three cohorts of students, those completing compulsory schooling in 2004, 2006 and 2009. We are able to follow the students for four years. This is the first study to provide cohort wide information on Finnish special education students at the upper secondary level.
We are able to identify the number of students receiving special education by the level of curriculum adjustments at the end of the comprehensive schooling. Special education students are divided into three different groups based on their curriculum adjustments. They are students with individualized curriculum in some subjects (i.e. students with mild disabilities), students with individualized curriculum in almost or all subjects (i.e. students with severe disabilities) and students with fully individualized curriculum (student with severe and/or multiple disabilities. These three groups of students are compared to students completing the general education curriculum without any individualized adjustments.
Crawford, C. – Vignoles, A. (2010). An analysis of the educational progress of children with special educational needs. DoQSS Working Paper No. 10-19, November 2010. Institute of Education, University of London. Hanushek, E. – Kain, J. – Rivkin, S. (2002): Inferring Program Effects for Special Populations: Does Special Education Raise Achievement for Students with Disabilities? The Review of Economics and Statistics, 84, 584-599. Jahnukainen, M. (2001) Two models for preventing students with special needs from dropping out of education in Finland. European Journal of Special Needs Education 16 (3), 245–258. Keslair, F., Maurin, E. & McNally, S. (2012) Every Child Matters? An Evaluation of “Special Educational Needs” Programmes in England. Economics of Education Review (2010), doi:10.1016/j.econedurew.2012.06.005. Lavy, V. – Schlosser, A. (2005). Targeted remedial education for underperforming teenagers: Costs and benefits. Journal of Labor Economics, 23, 839-874. McGee, A. (2011) Skills, standards, and disabilities: How youth with learning disabilities fare in high school and beyond. Economics of Education Review 30: 109-129. Morgan, P. L. – Frisco, M. L. – Farkas, G. – Hibel, J. (2010). A propensity score matching analysis of the effects of special education services. The Journal of Special Education, 43, 236-254.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
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