Presenting approaches based on traditional machine learning and regression on predicting the performance of students of higher institutions

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction

Predicting student performance has become an urgent demand in most educational and higher education institutions. This is essential to help at-risk students and ensure their retention, provide excellent learning resources and experiences, and improve the ranking and reputation of institutions. However, this may be difficult to achieve for start-up organizations with small records to analyze. The purpose of the current research was to provide approaches based on traditional machine learning and regression on predicting students' performance.

Method

The current research was of the qualitative research type and applied in terms of purpose and experimental analytical research in terms of method. Linear regression, decision tree, random forest and support vector machine methods were used in this research. In this section, after introducing the implementation environment, simulation parameters were introduced. In the following, by introducing the efficiency evaluation criteria of the proposed method, based on the described evaluation criteria, the findings were compared with other similar methods. For these comparisons, deep learning approach based on deep convolutional network and other deep learning approaches are used. In this research, the data collection of Dr. Hasht Roudi boys' school, which is among the top 10 institutions in Tehran, was used. The data of this institution are publicly available and can be downloaded through the GitHub site. Further investigation has been done on these data. The figure below shows the frequency of features in the dataset. that these features are considered as and on models.

Language:
Persian
Published:
Journal of New Approach to Children's Education, Volume:5 Issue: 4, 2024
Pages:
31 to 44
https://www.magiran.com/p2725752