Author(s)

Jamyandorj Narantuya¹, Tsend Ganbat²

¹Department of Science and Engineering, University of Mandakh, Ulaanbaatar, Mongolia.
²School of Information and Communication Technology, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.

Mongolian territory is 1.5 million square kilometers, there are 1.439 kindergartens that include 263.333 children. Mongolia has 5 regional zones. The research was made on selected provinces such as Sukhbaatar district from Ulaanbaatar region, Huvsgul aimag from Khangai region, Umnugobi from Central region, Dornod aimag from Eastern region and Bayan-Ulgii from Western region. Total 450 preschool children at age of 3 - 5 years old (30 children at every 3, 4 and 5 years old) were selected randomly, they performed 5 tasks of Math according to the curriculum. The classification of age, sex and region was made under cluster analyses of children’s mathematical ability using research method. The purpose of the research is classification of province zone, determination of inequality and difference between rural and urban areas. It is made support for developer’s policy and decision makers of education under the base of financing and sharing kindergarten budget, specialization, retraining of teachers and children, developing, elaboration and planning curriculum.

Data Mining, Machine Learning, Clustering HCPC, R Programming

Narantuya, J. and Ganbat, T. (2022) The Evaluation of Child Capacity by Machine Learning According to the Region. Journal of Computer and Communications, 10, 90-98. doi: 10.4236/jcc.2022.106008.