A4 Refereed article in a conference publication
Measuring Students’ Stress with Mood Sensors: First Findings
Authors: Henri Kajasilta, Mikko-Ville Apiola, Erno Lokkila, Ashok Veerasamy, Mikko-Jussi Laakso
Editors: Michael A. Herzog, Zuzana Kubincová, Peng Han, Marco Temperini
Conference name: International Conference on Web-Based Learning
Publication year: 2019
Journal: Lecture Notes in Computer Science
Book title : Advances in Web-Based Learning – ICWL 2019
Series title: Lecture Notes in Computer Science
Volume: 11841
First page : 92
Last page: 99
ISBN: 978-3-030-35757-3
DOI: https://doi.org/10.1007/978-3-030-35758-0_9
Web address : https://link.springer.com/chapter/10.1007/978-3-030-35758-0_9
Emotions and stress have considerable impact to wellbeing, growth and academic achievement. However, while devices with signal accuracy that is valid for clinical field research have become available, there is still a significant gap in knowledge about the relevance of such devices for digital learning. In this pilot study, a group of 17 university students of computing wore a moodmetrics smart ring device for one week. In addition, students kept short diaries about their study-related activities. Results from statistical analysis show a strong correlation between non-study and study-related stress level averages. Even when comparing the daily stress values, the correlation was strong and significant within the 95% confidence level. A total of 53 non-study and study average pairs were observed in the data. Our results reveal that stress of these students seemed not to vary between short-term study-events but it was found to be a more comprehensive issue. In the future, larger samples and more data are needed for more reliable research on individual study activities.