Detecting emotions in a learning environment: a multimodal exploration

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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 languageEnglish
Title of host publicationProceedings 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)
EditorsMikhail Fominykh, Maria Aristeidou
Pages71-82
Number of pages12
Publication statusPublished - 2021
Event16th European Conference on Technology Enhanced Learning, EC-TEL 2021 - Online Conference, Bolzano, Italy
Duration: 20 Sep 202124 Sep 2021
Conference number: 16

Publication series

NameCEUR workshop proceedings
PublisherRheinisch Westfälische Technische Hochschule
Volume3076
ISSN (Print)1613-0073

Conference

Conference16th European Conference on Technology Enhanced Learning, EC-TEL 2021
Abbreviated titleEC-TEL 2021
Country/TerritoryItaly
CityBolzano
Period20/09/2124/09/21

Keywords

  • Affective computing
  • Emotion detection
  • Psychophysiology
  • Wearables in education

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