Article

Analysis of Factors Affecting Student Performance Using Machine Learning Techniques

Ibrohimbek YusupovTashkent University of Information Technologies,Department of Artificial Intelligence,Tashkent,UzbekistanBakhtiyor MakhkamovTashkent University of Information Technologies,Department of Artificial Intelligence,Tashkent,UzbekistanKhakimjon ZaynidinovTashkent University of Information Technologies,Department of Artificial Intelligence,Tashkent,UzbekistanDanish AtherSonal PathakSchool of Computer Applications, Manav Rachna International Institute of Research and Studies (MRIIRS),Faridabad,Haryana,IndiaTemurbek KuchkorovTashkent University of Information Technologies,Department of Artificial Intelligence,Tashkent,Uzbekistan

2024en

ABI

Abstract

This paper makes a comparative analysis of several factors that are likely to influence performance of students based on a set of data collection parameters that include study habits, attendance, parental involvement among others. In this analysis, decision trees and logistic regression are employed for estimating final examination grades. Parental involvement, attendance and study hours were identified as having the greatest influence on performance.

Topics

Technology and Data Analysis Online Learning and Analytics Education and Learning Interventions

Identifiers

DOI: 10.1109/icisct64202.2024.10956817

Citations and references

Cited by 00 references

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