Next Article in Journal / Special Issue
Predicting Students’ Behavioral Intention to Use Open Source Software: A Combined View of the Technology Acceptance Model and Self-Determination Theory
Previous Article in Journal
Optimization Design of Actuator Parameters with Stepless Capacity Control System Considering the Effect of Backflow Clearance
Previous Article in Special Issue
Technology-Enhanced Learning for Graduate Students: Exploring the Correlation of Media Richness and Creativity of Computer-Mediated Communication and Face-to-Face Communication
Open AccessArticle

Prediction of High Capabilities in the Development of Kindergarten Children

1
Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Ciudad de México 07700, Mexico
2
Center for Pedagogical Studies and Department of Computer Sciences of the University of Ciego de Ávila, Ciego de Ávila 67100, Cuba
3
Centro de Investigación en Computación, Instituto Politécnico Nacional, Ciudad de México 07700, Mexico
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(8), 2710; https://doi.org/10.3390/app10082710
Received: 24 March 2020 / Revised: 2 April 2020 / Accepted: 2 April 2020 / Published: 14 April 2020
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. View Full-Text
Keywords: student performance; kindergarten children; nearest neighbor; imbalanced data student performance; kindergarten children; nearest neighbor; imbalanced data
Show Figures

Figure 1

MDPI and ACS Style

Villuendas-Rey, Y.; Rey-Benguría, C.F.; Camacho-Nieto, O.; Yáñez-Márquez, C. Prediction of High Capabilities in the Development of Kindergarten Children. Appl. Sci. 2020, 10, 2710.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop