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Record W2319606882 · doi:10.20360/g2dw2x

The Effect of Negotiating Pedagogies in Saudi College EFL Writing Classrooms

2016· article· en· W2319606882 on OpenAlexvenueno aff
Osman Z. Barnawi

Bibliographic record

VenueLanguage and Literacy · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsTUTORNegotiationPedagogyMathematics educationAgency (philosophy)LiteracySociologyConstruct (python library)PsychologyComputer science

Abstract

fetched live from OpenAlex

Studies on the application of centre applied linguistics circles’ writing pedagogies in EFL settings have placed great emphasis on the agency and innovativeness of local teachers. Local teachers often exercise absolute power over students’ learning processes by transplanting Western approaches to writing into their local contexts. However, the active roles of student-writers in negotiating, constructing and transforming these pedagogical imports to suit their needs have been overlooked in the literature. This study examined how my students’ negotiations with writing pedagogies that I imported from the USA helped them to move from writing to display knowledge to writing in order to construct and transform knowledge, at levels such as self, content and form. It was found that these pedagogies helped me critically reflect upon my position as an EFL writing tutor as well as scaffold my students’ learning accordingly. They also helped my students to assume active roles in writing classes.

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)0.010
metaresearch head score (Gemma)0.048
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 score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0100.003
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.010
GPT teacher head0.275
Teacher spread0.264 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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