In recent years, schools have shown interest in utilizing data mining to improve the quality of education. To enhance academic performance, accurately predicting how students will perform in their classes is crucial, which is essential for their progress in further education. Some students encounter challenges upon entering higher education, and predicting their performance early on is vital to keeping them on the right track. Our research aims to assess student performance using various classification strategies to identify the most accurate one. We utilize a Kaggle dataset for this study. Initially, we clean up the dataset by removing duplicate records and filling in any missing information. Subsequently, we apply six different classifier...
Abstract Student performance prediction is an important aspect of education that has gained signific...
The availability of educational data obtained by technology-assisted learning platforms can potentia...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...
In recent years, schools have shown interest in utilizing data mining to improve the quality of educ...
Educational Data Mining and Deep learning play a crucial role in identifying academically weak stude...
The data in E-learning is generated as a result of the students' interactions during the learning se...
Predicting students’ academic performance at an early stage of a semester is one of the most ...
Educational data mining is an emerging interdisciplinary research area involving both education and ...
Educational Data Mining plays a crucial role in identifying academically weak students of an institu...
Data mining is the process of extracting hidden patterns and useful information from large set of da...
Student performance in higher education has become one of the most widely studied area. While modell...
The objective of the study is to use a method to predict student performance during the semesters a...
An educational institution's primary objective is to create a learning environment that enhances stu...
In recent years, there has been evidence of a growing interest on the part of universities to know i...
Educational data generated through various platforms such as e-learning, e-admission systems, and au...
Abstract Student performance prediction is an important aspect of education that has gained signific...
The availability of educational data obtained by technology-assisted learning platforms can potentia...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...
In recent years, schools have shown interest in utilizing data mining to improve the quality of educ...
Educational Data Mining and Deep learning play a crucial role in identifying academically weak stude...
The data in E-learning is generated as a result of the students' interactions during the learning se...
Predicting students’ academic performance at an early stage of a semester is one of the most ...
Educational data mining is an emerging interdisciplinary research area involving both education and ...
Educational Data Mining plays a crucial role in identifying academically weak students of an institu...
Data mining is the process of extracting hidden patterns and useful information from large set of da...
Student performance in higher education has become one of the most widely studied area. While modell...
The objective of the study is to use a method to predict student performance during the semesters a...
An educational institution's primary objective is to create a learning environment that enhances stu...
In recent years, there has been evidence of a growing interest on the part of universities to know i...
Educational data generated through various platforms such as e-learning, e-admission systems, and au...
Abstract Student performance prediction is an important aspect of education that has gained signific...
The availability of educational data obtained by technology-assisted learning platforms can potentia...
A comprehensive systematic study was carried out in order to identify various deep learning methods ...