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Record W2161907766 · doi:10.5539/elt.v5n1p76

An Investigation into Ambiguity Tolerance in Iranian Senior EFL Undergraduates

2011· article· en· W2161907766 on OpenAlexvenueno aff
Amin Marzban, Hossein Barati, Ahmad Moinzadeh

Bibliographic record

VenueEnglish Language Teaching · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsModerationPsychologyAmbiguityAmbiguity toleranceSyllabusScale (ratio)Mathematics educationSocial psychologyLinguistics

Abstract

fetched live from OpenAlex

The present study aimed to explore how tolerant of ambiguity Iranian EFL learners at university level are and if gender plays a role in this regard. To this end , upon filling in the revised SLTAS scale of ambiguity tolerance 194 male and female Iranian teacher trainees were assigned to three ambiguity tolerance groups; namely, high, moderate and low. Cluster analysis of the SLTAS scores indicated that Iranian EFL learners were mostly moderate as far as tolerance of ambiguity was concerned. Examining the gender differences through an independent sample t-test manifested that female participants were less tolerant of ambiguity than their male peers. Also, the differences between the expected and observed number of participants categorized in the three AT groups were non-significant undermining the role of gender as a moderator variable in assigning participants to AT groups and further approving of SLTAS validity. Implications for classroom practice are presented in the light of findings. The results are helpful in syllabus design and teaching methodology.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.319
Teacher spread0.293 · 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 designObservational
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

Citations16
Published2011
Admission routes1
Has abstractyes

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