Review of Genetic Algorithm to improve Students Academic Performance by applying Smart Learning

被引：0

作者：

Ortiz-Suarez, Luis Arturo ^{[1
]}

Reyes-Hernandez, Yaneth ^{[1
]}

Hernandez, Uriel Amado Ramirez ^{[1
]}

Sanchez, Joel Silos ^{[1
]}

Perez, Luis Jose Gomez ^{[1
]}

Trejo-Macotela, Francisco Rafael ^{[1
]}

Camarillo, Daniel Robles ^{[1
]}

机构：

[1] Univ Politecn Pachuca, Zempoala, Mexico

来源：

INTERNATIONAL JOURNAL OF COMBINATORIAL OPTIMIZATION PROBLEMS AND INFORMATICS | 2023年 / 14卷 / 03期

关键词：

Smart learning; genetic algorithm; ENVIRONMENT;

D O I：

10.61467/2007.1558.2023.v14i3.401

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper reviews the use of genetic algorithms for enhancing academic performance through Smart learning. The study reveals that the application of technology in teaching can improve students' grades. It also analyzes the implementation of cognitive training and the benefits obtained for a better comprehension of the information received by individuals. A literature review is provided to give an overview of how these issues have impacted various parts of the world. The importance of integrating novel approaches to Smart learning, such as genetic algorithms and cognitive training, to enrich pedagogical strategies is highlighted.

引用

页码：117 / 137

页数：21

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