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Record W3004555913

A review of peer interaction and second language learning for ELL students in academic contexts

2019· review· en· W3004555913 on OpenAlexaff
Vander Tavares

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typereview
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsYork University
Fundersnot available
KeywordsLanguage proficiencyPsychologyRelation (database)Identity (music)Second languageMathematics educationPedagogyLinguisticsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This review explores the relationship between language proficiency and ELL (English Language Learners) students’ experiences in higher education contexts, with specific reference to the role of conversational peer interaction. The two major concerns that guide this review are the academic challenges faced by students from an ELL background in relation to conversational interaction, and the impact of conversational language proficiency on their overall academic experience. Findings suggest that insufficient language proficiency results in several challenges for ELL students, most notably the inability to share their expertise and knowledge with their peers, and participate successfully in classroom oral discussions. In addition, however, the literature suggests that language proficiency has a strong impact on the overall experiences of students and on their abilities to navigate the social structures of the academic community and to establish their own identity.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.451
GPT teacher head0.632
Teacher spread0.180 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2019
Admission routes1
Has abstractyes

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