Editor-in-chief

Prof. Paul Sudnik

Munich University of Applied Sciences, Germany

As the Editor-in-Chief of IJSSH, I invite you to contribute your scholarly work to our esteemed publication. The journal publishes papers which focus on the advanced researches in the field of all aspects of social science and humanity. I'll endeavour to make this journal grow better and hopefully it will become a recognized journal among researchers and scholars in related fields.

Home > Archive > 2026 > Volume 16, Number 1, 2026
IJSSH 2026 Vol.16(1): 28-32
doi: 10.18178/ijssh.2026.16.1.1274

Activity Management System for Enhancing Online Classroom Interaction Using Support Vector Machine and Random Forest

Akaraj Chunhapinyokul*, Lachana Ramingwong, Sakgasit Ramingwong, Kenneth Cosh, and Narissara Eiamkanitchat
Department of Computer Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand
Email: akaraj_c@cmu.ac.th (A.C.); lachana_r@cmu.ac.th (L.R.); sakgasit_r@cmu.ac.th (S.R.); kenneth_c@cmu.ac.th (K.C.); narissara_e@cmu.ac.th (N.E.)
*Corresponding author

Manuscript received June 9, 2025; accepted September 9, 2025; published February 11, 2026.

Abstract—This paper proposes an Activity Management System (AMS) that uses Support Vector Machine (SVM) and Random Forest (RF) algorithms to classify students into different interaction levels in online classrooms. The system captures behavioral features such as time spent online and chat activity to form data-driven student groups. The approach addresses the lack of interaction in virtual learning environments and promotes more equitable and engaging peer collaboration. The system’s effectiveness was validated using real and CTGAN-generated data, showing improvements in interaction compared to random grouping.

Keywords—online learning, student engagement, Support Vector Machine (SVM), Random Forest (RF), machine learning in education, interaction classification

Cite: Akaraj Chunhapinyokul, Lachana Ramingwong, Sakgasit Ramingwong, Kenneth Cosh, and Narissara Eiamkanitchat, "Activity Management System for Enhancing Online Classroom Interaction Using Support Vector Machine and Random Forest," International Journal of Social Science and Humanity, vol. 16, no. 1, pp. 28-32, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
PREVIOUS PAPER
Difficulties and Support of Out-of-Prefecture Evacuees—Due to the Great East Japan Earthquake and Nuclear Power Plant Accident
NEXT PAPER
No next article

Copyright © 2008-2026. International Journal of Social Science and Humanity. Unless otherwise stated.

E-mail: ijssh.editorial.office@gmail.com