Mining student behaviour patterns for mental health insights using association rule learning

Name: Wai, Hnin Oo

Organization : Mae Fah Luang University. School of Applied Digital Technology

Email : 6631301057@lamduan.mfu.ac.th

Name: Kyaw, Nyein Nyein

Organization : Mae Fah Luang University. School of Applied Digital Technology

Email : 6631301062@lamduan.mfu.ac.th

Name: Thant, Zaw Shin

Organization : Mae Fah Luang University. School of Applied Digital Technology

Email : 6631301068@lamduan.mfu.ac.th

Name: Nilubon Kurubanjerdjit

Organization : Mae Fah Luang University. School of Applied Digital Technology

Email : nilubon.kur@mfu.ac.th

Name: Nupap, Soontarin

Organization : Mae Fah Luang University. School of Applied Digital Technology

Email : soontarin@mfu.ac.th

LCSH: Students -- Mental health

LCSH: Data mining

LCSH: Association rule mining

LCSH: Machine learning

LCSH: Behavioral assessment

LCSH: College students -- Psychology

Abstract: Mental health problems among university students have become a growing global concern, contributing to poor academic outcomes and increased dropout rates. These issues are shaped by intricate behavioural, financial, and psychosocial interactions that conventional statistical models often overlook. This study applies association rule mining (ARM) using the FP-Growth algorithm in RapidMiner to uncover latent patterns influencing student well-being. Survey data collected from 266 Thai university students were analysed to identify frequently co-occurring behavioural and lifestyle factors. The findings show that family financial support consistently acts as a key protective factor, often linked with adequate sleep and constructive stress-management behaviours. Conversely, digital entertainment-including gaming, social media, and television-emerges as a prevalent coping mechanism associated with both financial stability and sleep quality. Multi-factor rules reveal the interconnected roles of coping style, screen exposure, and body image in shaping mental health outcomes. By offering interpretable, rule-based insights, ARM enables educators and counsellors to design holistic, evidence-based interventions for promoting student mental well-being.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2026-03-06

Issued: 2026-03-06

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BibliograpyCitation : In Prince of Songkla University, Phuket Campus. College of Computing. The 9th International Conference on Information Technology (InCIT 2025) (pp.512-517). Phuket : Prince of Songkla University

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