Unpacking the Complexity: Why Current Feedback Systems Fail to Improve Learner Self-Regulation of Participation in Collaborative Activities

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Bibliographic Details
Title: Unpacking the Complexity: Why Current Feedback Systems Fail to Improve Learner Self-Regulation of Participation in Collaborative Activities
Language: English
Authors: Xavier Ochoa (ORCID 0000-0002-4371-7701), Xiaomeng Huang (ORCID 0000-0002-6992-061X), Adam Charlton
Source: Journal of Learning Analytics. 2024 11(2):246-267.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index
Peer Reviewed: Y
Page Count: 22
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Learning Analytics, Feedback (Response), Independent Study, Cooperative Learning, Learning Activities, Learning Processes, Goal Orientation
ISSN: 1929-7750
Abstract: Even before the inception of the term "learning analytics," researchers globally had been investigating the use of various feedback systems to support the self-regulation of participation and promote equitable contributions during collaborative learning activities. While some studies indicate positive effects for distinct subgroups of learners, a common finding is that the majority of learners do not modify their behaviour, even after repeated interventions. In this paper, we assessed one such system and, predictably, did not find measurable improvements in equitable participation. Informed by self-regulated learning theory, we conducted a mixed-methods study to explore the diverse paths that learners take in the self-regulation process initiated by the feedback. We found that the observed deviations from the expected path explain the difficulty in measuring a generalized effect. This study proposes a shift in research focus from merely improving the technological aspects of the system to a human- and pedagogical-centred redesign that takes special consideration of how learners understand and process feedback to self-regulate their participation.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1441158
Database: ERIC
Description
Abstract:Even before the inception of the term "learning analytics," researchers globally had been investigating the use of various feedback systems to support the self-regulation of participation and promote equitable contributions during collaborative learning activities. While some studies indicate positive effects for distinct subgroups of learners, a common finding is that the majority of learners do not modify their behaviour, even after repeated interventions. In this paper, we assessed one such system and, predictably, did not find measurable improvements in equitable participation. Informed by self-regulated learning theory, we conducted a mixed-methods study to explore the diverse paths that learners take in the self-regulation process initiated by the feedback. We found that the observed deviations from the expected path explain the difficulty in measuring a generalized effect. This study proposes a shift in research focus from merely improving the technological aspects of the system to a human- and pedagogical-centred redesign that takes special consideration of how learners understand and process feedback to self-regulate their participation.
ISSN:1929-7750