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Comparative statistics and indicators on students with SEN Israel November 21, 2007
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UNESCO definition of special needs education (SNE) in ISCED emphasises: –Change in provision from special school/institutions to regular schools and community approach –Increased breadth of definition to include all those failing at school (at least in some countries) –The need for additional resources
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The understanding of the concept of SNE varies widely from country to country and following the ISCED definition led to the development of a resource-based definition. In addition, the definitions of different categories of students with special needs varies from country to country.
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Resource-based model: Those with special educational needs are defined by the additional public and/or private resources provided to support their education. Resources may be personnel, material or financial.
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It is clear that this covers children with very different types of histories and problems and for educational policy purposes putting them all together is not very helpful. But broadly speaking, they can be divided into those with Disabilities, Learning Difficulties and Disadvantages (DDD).
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Disability Those with organic pathologies. Educational need arises mainly from problems associated with these disabilities.
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Learning Difficulty Those with behavioural or emotional disorders or specific learning difficulties. Educational need arises mainly from problems in the interaction between the student and the educational context.
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Disadvantage Those with problems arising mainly from socio-economic or cultural/linguistic factors. The educational need is to compensate for the disadvantage associated with these factors.
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Number of students receiving additional resources over the period of compulsory education in cross-national category A as a percentage of all students in compulsory education
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Percentages of students receiving additional resources over the period of compulsory education in cross-national category A by location
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Number of students receiving additional resources over the period of compulsory education in cross-national category B as a percentage of all students in compulsory education
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Student performance on the PISA mathematics scale
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Percentages of students receiving additional resources over the period of compulsory education in cross-national category B by location
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Number of students receiving additional resources over the period of compulsory education in cross-national category C as a percentage of all students in compulsory education
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Percentages of students receiving additional resources over the period of compulsory education in cross-national category C by location
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Percentages of boys over the period of compulsory education in cross-national category A
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Percentages of boys over the period of compulsory education in cross-national category B
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Percentages of boys over the period of compulsory education in cross-national category C
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Belgium (Fl.) preliminary trend analysis 1999-2005 2005 data are provisional
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Belgium (Fl.) preliminary trend analysis 1999-2005 2005 data are provisional
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Number of students receiving additional resources in special schools as a proportion of all students by age
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Student/teacher ratios (public and private, all categories), 2003 Primary education Lower secondary education Special schools All classes Special schools All classes Belgium5.7 * 13.43.2 *x Czech Republic6.0 19.46.414.5 Finland5.0 16.16.310.9 Mexico19.3 2728.029.2 Slovak Republic7.1 20.75.714.5 * Data is the mean of Flemish and French Communities of Belgium
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Worked with this model in South-Eastern Europe Using ABC to generate categories of data Countries’ databases need to be developed
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Advantages of model Focus on resources allows for consideration of their distribution – a principle feature of equity Focus on full participation through curriculum access stresses quality and improved outcomes Focus on inclusion beyond those with disabilities emphasising the need to develop a continuum of provision to promote quality education for all The approach provides internationally comparable data It is easily understood and widely applicable
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Thank you peter.evans@oecd.org
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