Educational data mining to predict students' academic performance: A survey study

S Batool, J Rashid, MW Nisar, J Kim, HY Kwon… - Education and …, 2023‏ - Springer
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …

Systematic literature review on machine learning and student performance prediction: Critical gaps and possible remedies

B Sekeroglu, R Abiyev, A Ilhan, M Arslan, JB Idoko - Applied Sciences, 2021‏ - mdpi.com
Improving the quality, develo** and implementing systems that can provide advantages to
students, and predicting students' success during the term, at the end of the term, or in the …

Using machine learning to predict factors affecting academic performance: the case of college students on academic probation

L Al-Alawi, J Al Shaqsi, A Tarhini… - Education and Information …, 2023‏ - Springer
This study aims to employ the supervised machine learning algorithms to examine factors
that negatively impacted academic performance among college students on probation …

Identifying the Factors Affecting Student Academic Performance and Engagement Prediction in MOOC using Deep Learning: A Systematic Literature Review

S Rizwan, CK Nee, S Garfan - IEEE Access, 2025‏ - ieeexplore.ieee.org
The increasing reliance on Massive Open Online Courses (MOOCs) has transformed the
landscape of education, particularly during the COVID-19 pandemic, where e-learning …

Prediction of student exam performance using data mining classification algorithms

D Khairy, N Alharbi, MA Amasha, MF Areed… - Education and …, 2024‏ - Springer
Student outcomes are of great importance in higher education institutions. Accreditation
bodies focus on them as an indicator to measure the performance and effectiveness of the …

[HTML][HTML] AI-Enhanced Decision-Making for Course Modality Preferences in Higher Engineering Education during the Post-COVID-19 Era

A Mehrabi, JW Morphew, BN Araabi, N Memarian… - Information, 2024‏ - mdpi.com
The onset of the COVID-19 pandemic has compelled a swift transformation in higher-
education methodologies, particularly in the domain of course modality. This study highlights …

AI-Driven Educational Transformation in Secondary Schools: Leveraging Data Insights for Inclusive Learning Environments

D Duraes, R Bezerra, P Novais - 2024 IEEE Global …, 2024‏ - ieeexplore.ieee.org
In recent years, in the field of education, there has been a progressive trend towards
teaching that is more personalised to students' characteristics and some models of …

Optimal machine learning models for kitsune to detect mirai botnet malware attack

A Alabdulatif, SSH Rizvi, MA Hashmani - Journal of Hunan University …, 2021‏ - jonuns.com
The network intrusion detection system (NIDS) is the key player to detect and mitigate Botnet
Malware attacks. A plug-and-play NIDS, Kitsune, was proposed in the literature in 2018 as …

Optimizing adult learner success: Applying random forest classifier in higher education predictive analytics

E Barnes, J Hutson, K Perry - International …, 2024‏ - digitalcommons.lindenwood.edu
This study examines the application of the Random Forest Classifier (RF) model in
predicting academic success among adult learners in higher education. It focuses on …

[PDF][PDF] Investigating the Performance of Feature Selection Methods in Classifying Student Success

ÖB Güre - International Journal of Education Technology and …, 2023‏ - ijetsar.com
The present study investigates the optimization of machine learning algorithms, specifically
the Naïve Bayes classifier, in the context of Educational Data Mining (EDM). The primary …