Analysis of Factors Affecting Student Performance Using Machine Learning Techniques
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.
Authors
- Khakimjon Zaynidinov
- Sonal Pathak (ORCID: https://orcid.org/0000-0003-4435-1614)
- Bakhtiyor Makhkamov
- Ibrohimbek Yusupov (ORCID: https://orcid.org/0000-0002-2166-6683)
- Temurbek Kuchkorov (ORCID: https://orcid.org/0000-0003-4041-1843)
- Danish Ather (ORCID: https://orcid.org/0000-0003-1596-5553)
Institutions
- Tashkent University of Information Technology (UZ)
- Manav Rachna International Institute of Research and Studies (IN)
Publication Details
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1109/icisct64202.2024.10956817
- Primary Topic
- Technology and Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00