University of Oulu

Sobocinski, M., Malmberg, J. & Järvelä, S. Exploring Adaptation in Socially-Shared Regulation of Learning Using Video and Heart Rate Data. Tech Know Learn (2021). https://doi.org/10.1007/s10758-021-09526-1

Exploring adaptation in socially-shared regulation of learning using video and heart rate data

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Author: Sobocinski, Márta1; Malmberg, Jonna1; Järvelä, Sanna1
Organizations: 1Learning and Educational Technology Research Unit, University of Oulu, P.O.BOX 2000, 90014, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021120258586
Language: English
Published: Springer Nature, 2021
Publish Date: 2021-12-02
Description:

Abstract

In socially shared regulation of learning, adaptation is a key process for overcoming collaborative learning challenges. Monitoring the learning process allows learners to recognize the situations that require a need to change, revise, or optimize the current learning process. This can be done through adapting their strategies, task perception, goals, or standards for monitoring their progress. This process is called small-scale adaptation. It is not yet clear how shared monitoring in groups activates small-scale adaptation “on the fly” or how this phenomenon can be detected using multimodal data. The aim of this study is to explore how small-scale adaptation emerges during collaboration. Video and heart rate data were collected from four groups of three high-school students (age 16–17) who worked together during six 75-min advanced physics lessons. The results show small-scale adaptation occurs most often when groups switch from enacting tasks to defining them. Physiological synchrony occurred throughout the collaboration and was not significantly more prevalent before or after adaptation occurred. The opportunities and challenges of combining video observation to identify monitoring and adaptation events, and physiological synchrony as a possible indicator of “sharedness,” are discussed, contributing to the literature about using multimodal data to study learning processes.

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Series: Technology, knowledge and learning
ISSN: 2211-1662
ISSN-E: 2211-1670
ISSN-L: 2211-1662
Issue: Online first
DOI: 10.1007/s10758-021-09526-1
OADOI: https://oadoi.org/10.1007/s10758-021-09526-1
Type of Publication: A1 Journal article – refereed
Field of Science: 516 Educational sciences
Subjects:
Funding: Research funded by the Finnish Academy, Project No. 275440 (SLAM, PI: Paul A. Kirschner). The research was conducted in the Oulu University LeaF research infrastructure.
Academy of Finland Grant Number: 275440
Detailed Information: 275440 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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