Multi-output based hybrid integrated models for student performance prediction
H Xue, Y Niu - Applied Sciences, 2023 - mdpi.com
In higher education, student learning relies increasingly on autonomy. With the rise in
blended learning, both online and offline, students need to further improve their online …
blended learning, both online and offline, students need to further improve their online …
Student performance prediction using XGBoost method from a macro perspective
K Yan - 2021 2nd International Conference on Computing and …, 2021 - ieeexplore.ieee.org
Student performance prediction has attracted more and more attention in the educational
data mining field in recent years. An accurate and useful forecast on student performance …
data mining field in recent years. An accurate and useful forecast on student performance …
[Retracted] Predicting Course Grade through Comprehensive Modelling of Students' Learning Behavioral Pattern
D Hooshyar, Y Yang - Complexity, 2021 - Wiley Online Library
While modelling students' learning behavior or preferences has been found as a crucial
indicator for their course achievement, very few studies have considered it in predicting …
indicator for their course achievement, very few studies have considered it in predicting …
Student achievement analysis and prediction based on the whole learning process
M Wu, H Zhao, X Yan, Y Guo… - 2020 15th International …, 2020 - ieeexplore.ieee.org
Blended learning is increasingly used in college teaching, and formative evaluation has
become the main method for assessing student performance. Based on the formative …
become the main method for assessing student performance. Based on the formative …
Student-performulator: student academic performance using hybrid deep neural network
Educational data generated through various platforms such as e-learning, e-admission
systems, and automated result management systems can be effectively processed through …
systems, and automated result management systems can be effectively processed through …
Predicting academic performance using an efficient model based on fusion of classifiers
In the past few years, educational data mining (EDM) has attracted the attention of
researchers to enhance the quality of education. Predicting student academic performance …
researchers to enhance the quality of education. Predicting student academic performance …
Machine learning and deep learning-based students' grade prediction
Predicting student performance in a curriculum or program offers the prospect of improving
academic outcomes. By using effective performance prediction methods, instructional …
academic outcomes. By using effective performance prediction methods, instructional …
Predicting student academic performance using multi-model heterogeneous ensemble approach
OW Adejo, T Connolly - Journal of Applied Research in Higher …, 2018 - emerald.com
Purpose The purpose of this paper is to empirically investigate and compare the use of
multiple data sources, different classifiers and ensembles of classifiers technique in …
multiple data sources, different classifiers and ensembles of classifiers technique in …
Multiclass prediction model for student grade prediction using machine learning
Today, predictive analytics applications became an urgent desire in higher educational
institutions. Predictive analytics used advanced analytics that encompasses machine …
institutions. Predictive analytics used advanced analytics that encompasses machine …
Students learning performance prediction based on feature extraction algorithm and attention-based bidirectional gated recurrent unit network
C Yin, D Tang, F Zhang, Q Tang, Y Feng, Z He - Plos one, 2023 - journals.plos.org
With the development of information technology construction in schools, predicting student
grades has become a hot area of application in current educational research. Using data …
grades has become a hot area of application in current educational research. Using data …