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Record W2047555195 · doi:10.1080/00220670109598761

Cooperative Learning: Listening to How Children Work at School

2001· article· en· W2047555195 on OpenAlexaff
Andréa Mueller, Thomas Fleming

Bibliographic record

VenueThe Journal of Educational Research · 2001
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsQueen's University
Fundersnot available
KeywordsActive listeningCooperative learningEthnographyGroup workPsychologyWork (physics)Mathematics educationPedagogyCollaborative learningTeaching methodSociologyCommunication

Abstract

fetched live from OpenAlex

Cooperative and collaborative learning are recognized as valuable components of classroom learning. However, many questions remain regarding how teachers might structure and guide children's group-learning experiences. An ethnographic case study of 29 Grade 6 and Grade 7 students who worked in groups over 5 weeks was examined to determine what was learned. Data included audiotape recordings of 6 groups of children working together across 11 work sessions, student interviews, children's self-evaluations and drawings, and research reports. Findings revealed that when working in groups, children require periods of unstructured time to organize themselves and to learn how to work together toward a mutual goal.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.167
GPT teacher head0.509
Teacher spread0.342 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations70
Published2001
Admission routes1
Has abstractyes

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