Multimodal assessment of best possible self as a self-regulatory activity for the classroom

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  • dc.contributor.author Sayis, Batuhan
  • dc.contributor.author Beardsley, Marc Yoshimi
  • dc.contributor.author Portero Tresserra, Marta
  • dc.date.accessioned 2024-02-12T14:04:23Z
  • dc.date.available 2024-02-12T14:04:23Z
  • dc.date.issued 2023
  • dc.description Comunicació presentada a 2021 9th International 11th International Conference on Affective Computing and Intelligent Interaction (ACII), celebrat del 10 al 13 de setembre de 2023 a Cambridge, Estats Units.
  • dc.description.abstract Best possible self (BPS) is a positive psychological intervention shown to enhance well-being which involves writing a description of an ideal future scenario. This paper presents a comparison of psychophysiological effects of a BPS activity that has been adapted for classroom settings and a timematched control activity (NA). Thirty-three undergraduate students participated in the study that assessed state anxiety (State-Trait Anxiety Inventory, STAI), affect (Affective Slider, AS), and cardiac vagal activity (heart-rate variability, HRV) as an indicator of self-regulatory resource usage, at three time periods (PRE, DURING, POST). Results show that BPS led to a significantly greater increase in positive valence (DURING) and overall higher levels of cardiac vagal activity (HRV) compared to NA. These findings suggest that BPS has promising characteristics as a self-regulatory technique aimed at fostering positive affect and positively impacting self-regulatory resources. As BPS does not require expert knowledge nor specialized technology to administer, it may be a suitable activity for educators to use when teaching and having students practice self-regulation. This study presents evidence collected in a replicable multimodal approach of the self-regulatory effects of a brief BPS activity on undergraduate students.
  • dc.description.sponsorship This work has been partially funded by Universitat Pompeu Fabra Initiatives (Planetary Wellbeing: PLAWB00321, PLAWB00322; PlaCLIK: E2022014338), Erasmus+ program (2021-1-ES01-KA220-SCH000032801, RemixED), Spanish Ministry of Science and Innovation (PID2020-112584RB-C33 granted by MICIN/AEI/ 10.13039/ 501100011033) and European Union-NextGenerationEU, Ministry of Universities and Recovery, Transformation and Resilience Plan, through a call from Universitat Pompeu Fabra (Barcelona).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Sayis B, Beardsley M, Portero-Tresserra M. Multimodal assessment of best possible self as a self-regulatory activity for the classroom. In: 11th International Conference on Affective Computing and Intelligent Interaction (ACII); 2023 Sept. 10-13; Cambridge, USA. USA: IEEE; 2023. 7 p. DOI 10.1109/ACII59096.2023.10388153
  • dc.identifier.doi http://dx.doi.org/10.1109/ACII59096.2023.10388153
  • dc.identifier.isbn 9798350327434
  • dc.identifier.issn 2156-8103
  • dc.identifier.uri http://hdl.handle.net/10230/59086
  • dc.language.iso eng
  • dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
  • dc.relation.ispartof 11th International Conference on Affective Computing and Intelligent Interaction (ACII); 2023 Sept. 10-13; Cambridge, USA. USA: IEEE; 2023. 7 p.
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-112584RB-C33
  • dc.rights © 2023 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/ACII59096.2023.10388153
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.title Multimodal assessment of best possible self as a self-regulatory activity for the classroom
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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