An Analysis of Student's Academic Achievement in Genetic Algorithms Based on Mobile Learning Applications

Abstract

Several scholars have focused on this area due to the significance of mobile technology in the educational process, resulting in a substantial body of scholarly work. The primary objective of this study is to investigate the impact of mobile learning on students’ academic performance. The meta-analysis approach was utilized in this research. The available research was examined using several databases to find the relevant studies that were within the scope of the investigation. The study’s inclusion criteria and components were implemented following a literature review. This research proposes a mobile education system approach based on genetic algorithms to address the issues with the current system. The analysis findings indicate that most of them stay at around 10%. The salary only slightly increases when numerous individuals teach, but it also falls within a regular, appropriate range that can accommodate more complex tasks. According to the factor analysis findings, the influence of mobile educational devices on students’ learning performance varied depending on the course and subject. However, it remained constant regardless of the students’ education level and implementation duration. Apart from the previously mentioned research findings, this article also includes a descriptive analysis of the studies that were part of the meta-analysis.