Regularized ensemble learning for prediction and risk factors assessment of students at risk in the post-COVID era
The COVID-19 pandemic has had a significant impact on students' academic performance.
The effects of the pandemic have varied among students, but some general trends have …
The effects of the pandemic have varied among students, but some general trends have …
[HTML][HTML] Machine learning model (RG-DMML) and ensemble algorithm for prediction of students' retention and graduation in education
Automated prediction of students' retention and graduation in education using advanced
analytical methods such as artificial intelligence (AI), has recently attracted the attention of …
analytical methods such as artificial intelligence (AI), has recently attracted the attention of …
Framework for suggesting corrective actions to help students intended at risk of low performance based on experimental study of college students using explainable …
H Singh, B Kaur, A Sharma, A Singh - Education and Information …, 2024 - Springer
Today, the main aim of educational institutes is to provide a high level of education to
students, as career selection is one of the most important and quite difficult decisions for …
students, as career selection is one of the most important and quite difficult decisions for …
A model for predicting academic performance on standardised tests for lagging regions based on machine learning and Shapley additive explanations
Data are becoming more important in education since they allow for the analysis and
prediction of future behaviour to improve academic performance and quality at educational …
prediction of future behaviour to improve academic performance and quality at educational …
A survey on predicting at-risk students through learning analytics
This paper analyses the adoption of learning analytics to predict at-risk students. A total of
233 research articles between 2004 and 2023 were collected from Scopus for this study …
233 research articles between 2004 and 2023 were collected from Scopus for this study …
A Stacking Machine Learning Model for Student Performance Prediction Based on Class Activities in E-Learning.
MJ Shayegan, R Akhtari - Computer Systems Science & …, 2024 - search.ebscohost.com
After the spread of COVID-19, e-learning systems have become crucial tools in educational
systems worldwide, spanning all levels of education. This widespread use of e-learning …
systems worldwide, spanning all levels of education. This widespread use of e-learning …
[HTML][HTML] Enhancing Student Academic Success Prediction Through Ensemble Learning and Image-Based Behavioral Data Transformation
S Zhao, D Zhou, H Wang, D Chen, L Yu - Applied Sciences, 2025 - mdpi.com
Predicting student academic success is a significant task in the field of educational data
analysis, offering insights for personalized learning interventions. However, the existing …
analysis, offering insights for personalized learning interventions. However, the existing …
Predicting student success with and without library instruction using supervised machine learning methods
Purpose The main purpose of this analysis was to demonstrate the value of predictive
modeling of student success and identify the key groups of students for which library …
modeling of student success and identify the key groups of students for which library …
Technology-mediated method for prediction of global government investment in education toward sustainable development and aid using machine learning and …
K Okoye - 2023 IEEE Global Humanitarian Technology …, 2023 - ieeexplore.ieee.org
Predicting and monitoring of global government investment, eg, using AI-based method, is
becoming an emerging topic aimed at applying technological-based solutions to address …
becoming an emerging topic aimed at applying technological-based solutions to address …
The impact of emotional valence on students learning performance and evaluation: A text mining of students' opinion data
K Okoye - 2024 4th International Conference on Electrical …, 2024 - ieeexplore.ieee.org
Emotions classification or valence extraction in textual datasets, eg the students' opinion
data, is becoming an emerging topic aimed at understanding the impact or intensities of …
data, is becoming an emerging topic aimed at understanding the impact or intensities of …