Estimating orchestration load in CSCL situations using EDA
Estimating orchestration load in CSCL situations using EDA
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
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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 when orchestrating CSCL Pyramid scripts.Description
Comunicació presentada a: ICALT 2022 International Conference on Advanced Learning Technologies, celebrat del 1 al 4 de juliol de 2022 a Bucarest, Rumania.