The Challenge of gathering self-reported moods: Cases using a classroom
orchestration tool

Beardsley, Marc Yoshimi; Vujovic, Milica; Theophilou, Emily; Hernández Leo, Davinia; Portero Tresserra, Marta

doi:http://dx.doi.org/10.1109/ICALT49669.2020.00114

The Challenge of gathering self-reported moods: Cases using a classroom orchestration tool

Citation

Beardsley M, Vujovic M, Theophilou E, Hernàndez-Leo D, Portero Tresserra M. The Challenge of gathering self-reported moods: Cases using a classroom orchestration tool. In: ICALT 2020 International Conference on Advanced Learning Technologies and Technology-enhanced Learning; 2020 Jul 6-9; Tartu, Estonia. New York: IEEE; 2020. p. 355-9. DOI: 10.1109/ICALT49669.2020.00114

Abstract

Self-reports of affective states are increasingly being collected in educational settings. However, individual definitions and usage of emotion and mood terms are often subjective despite objective definitions becoming more widely accepted. We explore whether the variation among individual learners in how mood terms are defined presents an obstacle to using self-reported mood data for group comparison studies. Following a design-based research methodology, we ran two case studies to explore the use of ClassMood App in a multimodal learning study and the validity of the self-reported mood data it collected. During the first case, 24 primary school students experienced difficulty understanding the words used to describe the moods in ClassMood App. In the second case, involving 77 university students, we explored whether the misunderstanding of mood words persisted with older students. Participants were asked to rate their familiarity with and match definitions to a set of 8 mood words. We found that levels of familiarity with the mood words varied greatly and 17.9% of all definition matching attempts were incorrect. The results suggest that the variation in subjective definitions of mood terms is likely to affect the validity of the data collected by the ClassMood App for group comparison studies.

Description

Comunicació presentada a: ICALT 2020 International Conference on Advanced Learning Technologies and Technology-enhanced Learning, organitzada a Tartu, Estònia, del 6 al 9 de juliol de 2020