Estimating orchestration load in CSCL situations using EDA

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• dc.contributor.author Crespi, Francisco
• dc.contributor.author Amarasinghe, Ishari
• dc.contributor.author Vujovic, Milica
• dc.contributor.author Hernández Leo, Davinia
• dc.date.accessioned 2022-10-06T05:47:37Z
• dc.date.issued 2022
• dc.description Comunicació presentada a: ICALT 2022 International Conference on Advanced Learning Technologies, celebrat del 1 al 4 de juliol de 2022 a Bucarest, Rumania.
• dc.description.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.
• dc.description.sponsorship This work has been partially funded by the Ministry of Science and Innovation and the National Research Agency (PID2020-112584RBC33/MICIN/AEI/10.13039/501100011033). D. Hernandez- Leo (Serra Hunter) acknowledges the support by ICREA under the ICREA Academia program.
• dc.format.mimetype application/pdf
• dc.identifier.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
• dc.identifier.doi http://doi.org/10.1109/ICALT55010.2022.00046
• dc.identifier.uri http://hdl.handle.net/10230/54282
• dc.language.iso eng
• dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
• dc.relation.ispartof 2022 International Conference on Advanced Learning Technologies, ICALT 2022; 2022 Jul 1-4; Bucharest, Romania. [New York]: IEEE; 2022. p. 128-32.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-112584RBC33
• dc.rights © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://dx.doi.org/10.1109/ICALT55010.2022.00046
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Orchestration Load
• dc.subject.keyword Electrodermal Activity (EDA)
• dc.subject.keyword Computer-Supported
• dc.title Estimating orchestration load in CSCL situations using EDA
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion