Estimating orchestration load in CSCL situations using EDA

Crespi, Francisco; Amarasinghe, Ishari; Vujovic, Milica; Hernández Leo, Davinia

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Estimating orchestration load in CSCL situations using EDA

Document Type: Speech/Conference communication

Version: Accepted version

Date: 2022

Name: Crespi_ica_esti.pdf

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Citation: Crespi F, Amarasinghe I, Vujovic M, Hernández-Leo D. Estimating orchestration load in CSCL situations using EDA. In: 2022 International Conference on Advanced Learning Technologies, ICALT 2022; 2022 Jul 1-4; Bucharest, Romania. [New York]: IEEE; 2022. p. 128-32. DOI: 10.1109/ICALT55010.2022.00046

Permanent link: http://hdl.handle.net/10230/54282

Description:

Comunicació presentada a: ICALT 2022 International Conference on Advanced Learning Technologies, celebrat del 1 al 4 de juliol de 2022 a Bucarest, Rumania.

Abstract:

This study investigates the extent to which Electrodermal Activity (EDA) sensor data can be triangulated with self-perception measures to estimate facets of teachers’ orchestration load in the context of Computer-Supported Collaborative Learning (CSCL). It was expected to observe variances in the EDA signal as a result of stressful moments and incidents related to orchestration. Study findings indicated that EDA variations concurred with situations in which the teacher reported feeling stressed ...