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Journal Articles International Journal of Human-Computer Studies Year : 2020

EMODASH: A dashboard supporting retrospective awareness of emotions in online learning

Abstract

We present EMODASH, an interactive dashboard supporting tutors' retrospective awareness of learners' emotions in a video-conferencing learning environment. Socio-affective relationships play an important role in learning processes and learning outcomes, but they are harder to develop in online-learning. This can be explained by a lack of emotion awareness due to the asynchronous interactions, technical challenges, and tutors' focus on properly conducting the learning activity and gearing towards pedagogical outcomes. We conducted an eight-week long field study with five professional tutors on how they used EMODASH while writing feedback to learners after language learning sessions. We found that EMODASH led tutors who were already sensitive to learners' emotions to incorporate more affective elements in their reports, suggesting a stronger awareness of learners' emotions. Tutors also wrote more formative and less summative feedback. Furthermore, our results suggest that glanceable visualizations of learners' emotions may be preferred and sufficient to foster tutors' awareness of learners' emotions. Finally, the dashboard led tutors to reflect on the way they conduct their lessons, using learners' positive emotions as a proxy evaluation of their teaching.
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Dates and versions

hal-02490259 , version 1 (25-02-2020)

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Mohamed Ez-Zaouia, Aurélien Tabard, Elise Lavoué. EMODASH: A dashboard supporting retrospective awareness of emotions in online learning. International Journal of Human-Computer Studies, 2020, 139, pp.102411. ⟨10.1016/j.ijhcs.2020.102411⟩. ⟨hal-02490259⟩
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