Development of a model for predicting the need for specialized teachers for inclusive education

Abstract

In the modern educational landscape, inclusive education is firmly established, creating an urgent need for qualified personnel capable of adequately responding to the educational and social needs of a wide range of students. This article focuses on developing a forecasting model for the need for specialized teachers for inclusive education in the context of statistical and socio-psychological dynamics. Using multivariate regression analysis, time series and neural network algorithms, the study seeks to identify critical parameters such as the rate of inclusion of educational institutions, the growth in the number of students with special educational needs (SEN) - an increase of 17% over the last 5 years, and socio-demographic indicators. Analyzed data from 215 schools that use inclusive practices and took into account the performance of more than 15,000 teachers. The research is carried out on the basis of methodological synthesis, integrating qualitative and quantitative research methods. Empirical material was obtained using multilevel random sampling analysis, which takes into account both intragroup and intergroup differences. The importance of developing clear criteria and indicators for assessing the effectiveness of inclusive education cannot be underestimated, as these metrics are key for monitoring and subsequent adaptation of programs and initiatives.