2026-04-17T03:20:25Zhttps://recercat.cat/oai/requestoai:recercat.cat:10230/485512025-12-13T21:18:55Zcom_2072_6col_2072_452952
RECERCAT
author
Amarasinghe, Ishari
author
Hernández Leo, Davinia
2021-10-01T08:20:12Z2021-10-01T08:20:12Z2021
Comunicació presentada a: 14th International Conference on Computer-Supported Collaborative Learning (CSCL) celebrada del 7 a l'11 de juny de 2021 a Bochum, Alemanya.This study presents the orchestration challenges associated with scripted
collaborative learning situations at different scales and how different Learning Analytics (LA)
interventions may facilitate to address those issues. The proposed LA interventions were
characterised as machine-in-control, human-in-control and hybrid approaches given different
agents in charge of orchestration actions. A framing of the proposed LA interventions is
presented considering also the different scales within which those interventions were deployed,
in an attempt to seek the balance between different types of interventions.This work has been partially funded by FEDER, the National Research Agency of the Spanish Ministry of Science, Innovations and Universities MDM-2015-0502, TIN2017-85179-C3-3-R. Davinia Hernández-Leo acknowledges the support by ICREA under the ICREA Academia programme.
Paper published with all rights reserved © 2021 International Society of the Learning Sciences, Inc. [ISLS]. Proceedings available at: https://2021.isls.org/proceedings/.
Poster licensed under a Creative Commons License (BY-NC-ND 4.0 International). https://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess
Computer-Supported Collaborative Learning
Orchestration
Learning analytics
Synergies between humans and machines to support the orchestration of CSCL scripts at different scales
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion