The Challenge of gathering self-reported moods: Cases using a classroom orchestration tool
| Autor: | Milica Vujovic, Marc Beardsley, Davinia Hernández-Leo, Emily Theophilou, Marta Portero Tresserra |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Social and emotional learning
Matching (statistics) Computer science education Emotion measurement Data validation Affect (psychology) Multimodal learning Variation (linguistics) Mood mental disorders User interface design Orchestration tool Orchestration (computing) Set (psychology) Cognitive psychology |
| Zdroj: | ICALT |
| Popis: | 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 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. This work has been partially funded by the European Regional Development Fund, Erasmus+, and the National Research Agency of the Spanish Ministry of Science, Innovation and Universities, under project grants TIN2017-85179-C3-3-R, 2018-1-ESOI-KA20I-050646, and MDM-2015-0502. D. Hernández-Leo acknowledges the support by ICREA under the ICREA Academia programme. |
| Databáze: | OpenAIRE |
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