Investigating Real-Life Features Associated with Student Stress

Yicong LIANG, Di ZOU, Haoran XIE, Fu Lee WANG, Leung Pun WONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

Abstract

In recent years, the issue of student stress has attracted increasing attention from mental health professionals, educators, and researchers. Understanding the factors contributing to student stress is essential for effective interventions and support systems. This paper aims to investigate the real-life features associated with stress among students. In particular, this work examines and compares how stress levels correlate to five categories of factors, which consist of twenty features in total. The experiment was conducted on a publicly accessible dataset, and the analysis results show that students' stress associated with features from five factors demonstrates different patterns. Bullying and poor sleep quality are the main stressors among students.
Original languageEnglish
Title of host publicationProceedings : 2025 International Symposium on Educational Technology ISET 2025
EditorsKwok Tai CHUI, Chaiporn JAIKAEO, Jitti NIRAMITRANON, Wattana KAEWMANEE, Kwan-Keung NG, Pornthipa ONGKUNARUK
PublisherIEEE
Pages60-65
Number of pages6
ISBN (Electronic)9798331595500
ISBN (Print)9798331595517
DOIs
Publication statusE-pub ahead of print - 19 Aug 2025
Event2025 International Symposium on Educational Technology - Bangkok, Thailand
Duration: 22 Jul 202525 Jul 2025

Publication series

NameInternational Symposium on Educational Technology
PublisherIEEE
Volume2025
ISSN (Print)2766-2128
ISSN (Electronic)2766-2144

Conference

Conference2025 International Symposium on Educational Technology
Abbreviated titleISET
Country/TerritoryThailand
CityBangkok
Period22/07/2525/07/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Funding

The research has been supported by Teaching Development Grant (TDG) entitled "Flipping and Gamifying Data Science Classrooms" (Project No. 102722) and UGCfunded Inter-institutional Collaborative Activities for Fund for Innovative Technology-in Education (IICA-FITE) entitled "Advancing digital competency for university teachers and students in the era of generative artificial intelligence" (Project No. 120045) of Lingnan University, Hong Kong. This research has received the financial support from HKMU Conference Award for Research Students.

Keywords

  • Student stress
  • stress factors
  • stress feature analysis

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