A4 Article in conference proceedings

Measuring Students’ Stress with Mood Sensors: First Findings




List of Authors: Henri Kajasilta, Mikko-Ville Apiola, Erno Lokkila, Ashok Veerasamy, Mikko-Jussi Laakso

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

Title of series: Lecture Notes in Computer Science

Volume number: 11841

ISBN: 978-3-030-35757-3

DOI: http://dx.doi.org/10.1007/978-3-030-35758-0_9

URL: https://link.springer.com/chapter/10.1007/978-3-030-35758-0_9


Abstract

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.



Last updated on 2021-24-06 at 10:07