Vol. 1 No. 1 (2025): Regular Issue: March 2025 | Artificial Intelligence in Learning

This regular March 2025 issue comprises five original research articles authored and co-authored by 13 contributors representing 5 countries: Pakistan, South Korea, Indonesia, Malaysia, and Thailand.

Published: 2025-03-03

Comparing Random Forest and Logistic Regression for Predicting Student Completion in Online University Courses Using Behavioral Data

👥 Muhamad Irfan, Abdul Sattar, Ahmad Sher, Muhamad Ijaz

📈 Abstract: 75

🗎 PDF

📄 1-19

🗎 PDF: 41

📌 10.63913/ail.v1i1.25

Predicting Student Achievement Using Socioeconomic and School- Level Factors

👥 Thosporn Sangsawang, Liu Yang

📈 Abstract: 87

🗎 PDF

📄 20-34

🗎 PDF: 46

📌 10.63913/ail.v1i1.49

Clustering Student Behavioral Patterns: A Data Mining Approach Using K-Means for Analyzing Study Hours, Attendance, and Tutoring Sessions in Educational Achievement

👥 Yusuf Durachman, Abdul Wahab Bin Abdul Rahman

📈 Abstract: 94

🗎 PDF

📄 35-53

🗎 PDF: 45

📌 10.63913/ail.v1i1.48

Evaluating the Impact of Affirmative Action on Student Selection Outcomes: A Data Mining Approach Using SKD Test Performance at STMKG

👥 Husni Teja Sukmana, Lee Kyung Oh

📈 Abstract: 52

🗎 PDF

📄 54-74

🗎 PDF: 23

📌 10.63913/ail.v1i1.22

Analyzing the Impact of School Type on Student Outcomes Across Counties: A Comparative Study Using ANOVA

👥 I Gede Agus Krisna Warmayana, Yuichiro Yamashita, Nobuto Oka

📈 Abstract: 51

🗎 PDF

📄 75-92

🗎 PDF: 19

📌 10.63913/ail.v1i1.21

Journal Metrics
Acceptance Rate	49%
Review Speed	45 days
Issues per Year	4
Number of Volumes	2
Number of Issues	5
Number of Articles	25
Number of Reviewers	5
Number of Contributors	57
Contributing Countries	6
WoS Citations	18
Scopus Citations	33
Google Scholar Citations	53
Abstract Views	2,422 views
PDF Downloads	1,016
Updated at 18 May 2026

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Articles

Comparing Random Forest and Logistic Regression for Predicting Student Completion in Online University Courses Using Behavioral Data

Predicting Student Achievement Using Socioeconomic and School- Level Factors

Clustering Student Behavioral Patterns: A Data Mining Approach Using K-Means for Analyzing Study Hours, Attendance, and Tutoring Sessions in Educational Achievement

Evaluating the Impact of Affirmative Action on Student Selection Outcomes: A Data Mining Approach Using SKD Test Performance at STMKG

Analyzing the Impact of School Type on Student Outcomes Across Counties: A Comparative Study Using ANOVA