TY - JOUR
T1 - Prediction of high capabilities in the development of kindergarten children
AU - Villuendas-Rey, Yenny
AU - Rey-Benguría, Carmen F.
AU - Camacho-Nieto, Oscar
AU - Yáñez-Márquez, Cornelio
N1 - Publisher Copyright:
© 2020 by the authors.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - Analysis and prediction of children's behavior in kindergarten is a current need of the Cuban educational system. Despite such an early age, the kindergarten institutions are devoted to facilitate the integral children development. However, the early detection of high capabilities in a child is not always accomplished accurately; due to teachers being mostly focused on the performance of the children that are lagging behind to achieve their age range's stated goals. In addition, the amount of children with high capabilities is usually low, which makes the prediction an imbalanced data problem. Thus, such children tend to be misguided and overlaid, with a negative impact in their sociological development. The purpose of this research is to propose an efficient algorithm that enhances the prediction in the kindergarten children data. We obtain a useful set of instances and features, thus improving the Nearest Neighbor accuracy according to the Area under the Receiving Operating Characteristic curve measure. The obtained results are of great interest for Cuban educational system, regarding the rapidly and precise prediction of the presence or absence of high capabilities for integral personality development in kindergarten children.
AB - Analysis and prediction of children's behavior in kindergarten is a current need of the Cuban educational system. Despite such an early age, the kindergarten institutions are devoted to facilitate the integral children development. However, the early detection of high capabilities in a child is not always accomplished accurately; due to teachers being mostly focused on the performance of the children that are lagging behind to achieve their age range's stated goals. In addition, the amount of children with high capabilities is usually low, which makes the prediction an imbalanced data problem. Thus, such children tend to be misguided and overlaid, with a negative impact in their sociological development. The purpose of this research is to propose an efficient algorithm that enhances the prediction in the kindergarten children data. We obtain a useful set of instances and features, thus improving the Nearest Neighbor accuracy according to the Area under the Receiving Operating Characteristic curve measure. The obtained results are of great interest for Cuban educational system, regarding the rapidly and precise prediction of the presence or absence of high capabilities for integral personality development in kindergarten children.
KW - Imbalanced data
KW - Kindergarten children
KW - Nearest neighbor
KW - Student performance
UR - http://www.scopus.com/inward/record.url?scp=85084659338&partnerID=8YFLogxK
U2 - 10.3390/APP10082710
DO - 10.3390/APP10082710
M3 - Artículo
SN - 2076-3417
VL - 10
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 8
M1 - 2710
ER -