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Reasons for rising school dropout rates of rural girls in India - An analysis using soft computing approach

Author: 
Dr. R. Uma Rani
Subject Area: 
Physical Sciences and Engineering
Abstract: 

Education means expansion of cultural horizons and employment opportunities to an individual. But for nations, it means enhanced prospect of social and economic development. Education is a major factor influencing health (especially female education). The world map of illiteracy coincides with map of poverty, malnutrition, ill health, and high child mortality rates. There is a wide gender disparity in the literacy rate in India: effective literacy rates (age 7 and above) in 2011 were 82.14% for men and 65.46% for women. The low female literacy rate has had a dramatically negative impact on family planning and population stabilization efforts in India. India spends 1.8% of the national budget on its children, who form nearly 25% of its population. This explains why we are a country of 330 million illiterates, why 50 to 60% of children do not go beyond their primary schooling and why more than 50 millions become drop-outs. Amid all the celebrations over the Right to Education (RTE) coming into effect from April 1, there is an elephant in the room that nobody is talking about. It's called dropout rate. The spotlight till now has been on expanding the infrastructure, appointing teachers, ensuring that schools are at walk able distances, and so on. The Right to Education Act covers children in the 6 to 14 years age group — precisely for these classes in school. So, the dropouts need to be the biggest focus of the implementation mechanism being set up. Since the benefits that accrue to a country by having a literate population are multidimensional it becomes imperative to study the determinants of school drop-outs. The present paper attempts the same in villages in and around Salem District, Tamil Nadu as surveys indicate that majority of the drop-outs belong to poorest and least developed area of the country especially backward rural areas and urban slums. Hence an attempt has been made, to analyze the primary reasons for drop-outs among rural girl children and to identify the age group of rural girls with high drop-out rate. For this analysis, fuzzy matrix, one of the soft computing techniques has been used.

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