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Record W6884630259 · doi:10.11575/prism/35649

Friendships and group work in linguistically diverse mathematics classrooms: Opportunities to learn for English language learners

2016· other· en· W6884630259 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEllEthnographyFriendshipVariety (cybernetics)Group workEnglish languageWork (physics)Group (periodic table)

Abstract

fetched live from OpenAlex

This ethnographic study examined students’ opportunities to learn in linguistically diverse mathematics classrooms in a Canadian elementary school. I specifically examined the contextual change of group work, which influenced the opportunities to learn for newly arrived English language learners (ELLs). Based on analyses of videorecorded interactions, this study revealed a shift in these ELLs’ opportunities to learn from when they worked with teacher-assigned peers to when they worked with friends. In both settings, ELLs tended to be positioned as novices. However, when working with friends, they accessed a wider variety of work practices. In friend groups, ELLs were occasionally positioned as experts and had more opportunities to raise questions and offer ideas. In contrast, when working with teacher-assigned peers, ELLs tended to remain in the position of being helped. In some teacher-assigned groups, interactions were characterized as authoritative, and ELLs’ contributions and ideas were rejected or neglected without relevant justifications or mathematical authority established by their peers. The findings will contribute to ongoing discussions on group work and friendship in linguistically diverse classrooms.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.236
Teacher spread0.209 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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