Transforming educational insights: Strategic integration of federated learning for enhanced prediction of student learning outcomes

U Farooq, S Naseem, T Mahmood, J Li… - The Journal of …, 2024 - Springer
Numerous educational institutions utilize data mining techniques to manage student
records, particularly those related to academic achievements, which are essential in …

Predicting students' performance at higher education institutions using a machine learning approach

S Mohd Zaki, S Razali, MAR Awang Kader, MZ Laton… - Kybernetes, 2024 - emerald.com
Purpose Many studies have examined pre-diploma students' backgrounds and academic
performance with results showing that some did not achieve the expected level of …

Predictive analytics for university student admission: a literature review

KC Li, BTM Wong, HT Chan - International Conference on Blended …, 2023 - Springer
This paper presents a literature review on the use of learning analytics to support prediction
in university student admission. The review covers four areas: types of research issues …

Predicting the impact of internet usage on students' academic performance using machine learning techniques in Bangladesh perspective

SH Hemal, MAR Khan, I Ahammad, M Rahman… - Social Network Analysis …, 2024 - Springer
Education systems have significantly changed with the emergence of the internet. It has a
significant impact on how students learn things. Nevertheless, its impact can also be …

Educational data mining model using support vector machine for student academic performance evaluation

A Bisri, S Supardi, Y Heryatun… - … of Education and …, 2025 - edulearn.intelektual.org
In the educational landscape, educational data mining has emerged as an indispensable
tool for institutions seeking to deliver exceptional and high-quality education. However …

[HTML][HTML] Evaluation of early student performance prediction given concept drift

B Sonnleitner, T Madou, M Deceuninck… - … and Education: Artificial …, 2025 - Elsevier
Forecasting student performance can help to identify students at risk and aids in
recommending actions to improve their learning outcomes. That often involves elaborate …

Predicting the Strength Performance of Hydrated-Lime Activated Rice Husk Ash-Treated Soil Using Two Grey-Box Machine Learning Models

A Baghbani, A Soltani, K Kiany, F Daghistani - Geotechnics, 2023 - mdpi.com
Geotechnical engineering relies heavily on predicting soil strength to ensure safe and
efficient construction projects. This paper presents a study on the accurate prediction of soil …

Balancing Performance and Explainability in Academic Dropout Prediction

A Zanellati, SP Zingaro… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Academic dropout remains a significant challenge for education systems, necessitating
rigorous analysis and targeted interventions. This study employs machine learning …

[HTML][HTML] Renewal of the Concept of Diverse Education: Possibility of Further Education Based on a Novel AI-Based RF–ISSA Model

E Li, Z Wang, J Liu, J Huang - Applied Sciences, 2024 - mdpi.com
The traditional graduate admission method is to evaluate students' performance and
interview results, but this method relies heavily on the subjective feelings of the evaluators …

[PDF][PDF] Critical Review of Stack Ensemble Classifier for the Prediction of Young Adults' Voting Patterns Based on Parents' Political Affiliations.

G Elo, B Ghansah, E Kwaa-Aidoo - Informing Sci. Int. J. an Emerg …, 2024 - inform.nu
ABSTRACT Aim/Purpose This review paper aims to unveil some underlying machine-
learning classification algorithms used for political election predictions and how stack …