Abstract
Learner-emotions are intrinsically linked with learning experiences and academic outcomes. Therefore, intelligent learning environments need to be emotion-aware to bring learners to theirzone of proximal development. In this paper, we describe the first steps towards such a system. In this study, we manipulated task difficulty with the aim of detecting the physiological indicators of accompanying emotions, namely boredom/anger (during an easy task), enjoyment (during a moderately challenged task) and frustration/boredom (during a difficult task). Twenty-one adults (13 females and 8 males, Mage = 24.1 years) participated in a repeated- measures quasi-experimental set-up. Data were collected via Empatica E4 wristbands and self-reports. Results indicate that varying task difficulty may be associated with changes in skin temperature, phasic and tonic skin conductance, and heart rate. Findings encourage further exploration and thoughts on study design are discussed.
Original language | English |
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Title of host publication | Proceedings of the Doctoral Consortium of the Sixteenth European Conference on Technology Enhanced Learning co-located with the Sixteenth European Conference on Technology Enhanced Learning (EC-TEL 2021) |
Editors | Mikhail Fominykh, Maria Aristeidou |
Pages | 71-82 |
Number of pages | 12 |
Publication status | Published - 2021 |
Event | 16th European Conference on Technology Enhanced Learning, EC-TEL 2021 - Online Conference, Bolzano, Italy Duration: 20 Sept 2021 → 24 Sept 2021 Conference number: 16 |
Publication series
Name | CEUR workshop proceedings |
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Publisher | Rheinisch Westfälische Technische Hochschule |
Volume | 3076 |
ISSN (Print) | 1613-0073 |
Conference
Conference | 16th European Conference on Technology Enhanced Learning, EC-TEL 2021 |
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Abbreviated title | EC-TEL 2021 |
Country/Territory | Italy |
City | Bolzano |
Period | 20/09/21 → 24/09/21 |
Keywords
- Affective computing
- Emotion detection
- Psychophysiology
- Wearables in education