Predicting student retention: A comparative study of machine learning approach utilizing sociodemographic and academic factors by Reymark D. Deleña, Norniña J. Dia, Redeemtor R. Sacayan, Joseph C. Sieras, Suhaina A. Khalid, Amer Hussien T. Macatotong, Sacaria B. Gulam

“…The study offers a scalable and transferable modeling framework for higher education institutions seeking to implement early warning systems. …”
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A comparative approach of machine learning models to predict attrition in a diabetes management program. by Samantha Kanny, Grisha Post, Patricia Carbajales-Dale, William Cummings, Janet Evatt, Windsor Westbrook Sherrill

“…However, the machine learning models showed poor overall performance, with AUC values ranging from 0.53 - 0.64 and F-1 scores between 0.19 - 0.36, indicating low predictive power. …”
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Mapping artificial intelligence models in emergency medicine: A scoping review on artificial intelligence performance in emergency care and education by Göksu Bozdereli Berikol, Altuğ Kanbakan, Buğra Ilhan, Fatih Doğanay

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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

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Environmental impacts of economic growth: A STIRPAT analysis using machine learning algorithms by J. Krishnendu, Biswajit Patra

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Machine learning analysis of factors affecting college students’ academic performance by Jingzhao Lu, Yaju Liu, Shuo Liu, Zhuo Yan, Xiaoyu Zhao, Yi Zhang, Chongran Yang, Haoxin Zhang, Wei Su, Peihong Zhao

“…By employing the chi-square test to identify features closely related to academic performance, this paper discussed the main influencing factors and utilized machine learning models (such as LOG, SVC, RFC, XGBoost) for prediction. …”
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Revolutionizing Nursing and Midwifery Informatics Curriculum Evaluation in Ghana: A Data-Driven Machine Learning Approach by Iven Aabaah, Japheth Kodua Wiredu, Bakaweri Emmanuel Batowise, Nelson Abuba Seidu

“…This research assessed NMI educational programs in Ghana using machine learning techniques to analyze key factors influencing student performance, engagement, and satisfaction. …”
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Navigating Data Corruption in Machine Learning: Balancing Quality, Quantity, and Imputation Strategies by Qi Liu, Wanjing Ma

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Best practices for developing microbiome-based disease diagnostic classifiers through machine learning by Peikun Li, Min Li, Wei-Hua Chen

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An exploratory study of high-educated poverty through machine learning approach: a case study of East Java, Indonesia by Dias Satria, Risti Permani, Kodrad Winarno, David Kaluge, Citra Rahayu Indraswari, Radityo Putro Handrito

“…Research methodology – using data from the Indonesian National Survey, this study employs Random Forest (RF), Extreme Gradient Boosting (XGBoost), Artificial Neural Network (ANN), and K-Nearest Neighbor (KNN) algorithms as classification methods in machine learning.  Findings – the analysis results show that all agorithms has high accuracy with XGboost as the best performing model. …”
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Detection and Classification of Dress Code Violations in Educational Environments Using Deep Learning by Aminu Suleiman Bashir, Ahmed Ibrahim Mahmud, Muhammad Yahya

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Machine learning for post-diploma educational and career guidance: a scoping review in AI-driven decision support systems by Flavio Manganello, Elisa Rasca, Alberto Villa, Andrea Maddalena, Giannangelo Boccuzzi

“…The increasing complexity of career decision-making, shaped by rapid technological advancements and evolving job markets, highlights the need for more responsive and data-informed post-diploma guidance. Machine learning (ML), a core component of artificial intelligence, is gaining attention for its potential to support personalized educational and career decisions by analyzing academic records, individual preferences, and labor market data. …”
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Using Machine Learning for Arabic Sentiment Analysis in Higher Education: Investigating the Impact of Utilizing the ChatGPT and Bard Google by Salah AL-Hagree, Ghaleb Al-Gaphari, Fuaad Hasan Abdulrazzak, Maher Al-Sanabani, Ahmed Al-Shalabi

“…Mobile applications of universities have become an integral part of students’ lives, thus making it imperative to analyze user comments on these apps for SA purposes, where student input is crucial for assessing the effectiveness of educational institutions.  This paper presents a machine learning (ML) based approach to sentiment analysis on students’ evaluation of higher education institutions. …”
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Navigating the future of higher education in Saudi Arabia: implementing AI, machine learning, and big data for sustainable university development by Muhammad Adnan Khan, Abdur Rehman, Asghar Ali Shah, Sagheer Abbas, Meshal Alharbi, Munir Ahmad, Taher M. Ghazal

“…By balancing cutting-edge tech with local needs, GCC universities can provide innovative education while upholding traditions and values. This study explores how AI, Machine Learning, and Big Data can enhance sustainability and effectiveness in Saudi higher education, aligning with relevant UN Sustainable Development Goals. …”
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Optimization of robotic spray painting trajectories using machine learning for improved surface quality by Ritesh Bhat, M. Karuppasamy, M. Maragatharajan, Anandakumar Haldorai, E. Nirmala, Nithesh Naik

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Integrating lipidomics and machine learning to characterize lipid profile differences among goose breeds by Zhi Cao, Maodou Xu, Shangzong Qi, Xinlei Xu, Laidi Wang, Qiang Bao, Yu Zhang, Yang Zhang, Qi Xu, Guohong Chen

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STUDYING AI TECHNOLOGIES  IN EXTRACURRICULAR ACTIVITIES WITH TEENAGERS by Nataliia Valko, Nataliya Kushnir

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Approaches to the Design and Updating of Educational Programs Competence Models Based on the Intellectual Analysis of Employers’ Vacancies by D. V. Minaev

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Predicting student self-efficacy in Muslim societies using machine learning algorithms by Mohammed Ba-Aoum, Mohammed Ba-Aoum, Mohammed Alrezq, Jyotishka Datta, Konstantinos P. Triantis

“…Despite its recognized importance, research on predictors of self-efficacy using machine learning models remains limited, particularly within Muslim societies. …”
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Machine Learning Methods of Providing Informational Management Support for Students’ Professional Development by I. G. Zakharova

“…The effectiveness of this interaction resulted from its information support, based on reliable information, promptly provided to all the members of learning process.The aim of this paper was to study the machine learning methods potential for the effective management of learning process by the example of implementing information support component designed to diagnose and predict the professional development of students based on automatic text analysis.Methodology and research methods. …”
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