Inclusion and education

BOX 3.3: 
Bulgaria is improving identification of special 
education needs
As countries adopt an inclusive approach to education, they
need to reform the way they identify special education needs.
In Bulgaria, the Ministry of Education and Science and its 
28 regional inclusive education centres, in collaboration with 
UNICEF, have been introducing the ICF into education since 
2018. This classification is based on the biopsychosocial model, 
combining aspects of the social and medical models in disability 
assessment. It is designed to document not only children’s 
characteristics but also the influence of their environment.
The ministry plans to introduce a functional assessment toolkit 
in at least 400 schools and kindergartens under the Support for 
Inclusive Education project. About 15 teachers in each school 
and kindergarten, or about 6,000 teachers in all, will be involved 
in cascade training on the toolkit’s implementation. About 
12,000 students, or 30 per education institution, on average, will 
be covered when functional assessment of special education 
needs is rolled out by 2021. A methodology for conducting 
functional assessment in the Bulgarian context is also planned. 
This new model will improve local teams’ expertise to support 
personal development, improving the quality of additional 
education support geared to children’s individual profiles.
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a non-categorical approach to determining special needs, 
focusing instead on level of support given. 
The medical approach promotes a ‘wait to fail’ attitude: 
Diagnosis outside the learning setting is accompanied 
by an expectation that the student will fail without 
intervention. A non-categorical approach has implications 
for data. Instead of aggregate statistics on the number 
of students with specific conditions, data refer to the 
number of students who receive support, where they 
receive it, for how long and how effective it is. The use 
of special education needs categories for instructional 
purposes can be separated from the use of a reduced set 
of categories for resource allocation (Norwich, 2014).