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Record W4391810141 · doi:10.1080/00461520.2023.2294881

An integrated model of socially shared regulation of learning: The role of metacognition, affect, and motivation

2024· article· en· W4391810141 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEducational Psychologist · 2024
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMetacognitionPsychologyAffect (linguistics)Self-regulated learningCognitionCognitive psychologyTask (project management)ElaborationSocial psychology

Abstract

fetched live from OpenAlex

The purpose of this paper is to present an integrated theoretical model of socially shared regulation of learning (SSRL), which is an elaboration of Efklides’ Motivation and Affect in Self-Regulated Learning model that situates metacognition, affect, and motivation at the socially shared level. Building from existing theoretical and empirical work, the role of metacognition, affect and motivation in socially shared regulation of learning is described along with how these facets may facilitate or constrain regulatory phases and processes in relation to the individual and the group, and in consideration of the learning task. Educational implications are discussed including increasing focus on the social and cognitive processes involved in SSRL in pre-service teaching programs and advocating for the development of learning situations where students practice SSRL strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.424
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it