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Record W2331286655 · doi:10.20360/g2xw2k

The Effect of Explicit Pronunciation Instruction on Undergraduate EFL Learners' Vowel Perception

2016· article· en· W2331286655 on OpenAlexvenueno aff
Mohammad Reza Ghorbani, Malihe Neissari, Hamid Reza Kargozari

Bibliographic record

VenueLanguage and Literacy · 2016
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsnot available
Fundersnot available
KeywordsPronunciationVowelPsychologyPerceptionPersianTest (biology)Mathematics educationLinguisticsComputer scienceSpeech recognition

Abstract

fetched live from OpenAlex

Since English pronunciation errors are often caused by the transfer of the Persian language sound system, the present study investigated the effect of explicit pronunciation instruction on undergraduate English as a Foreign Language (EFL) learners’ vowel perception enhancement. The nonequivalent group, pretest-posttest design was employed to study two classes of English literature and English teaching students at Kosar University of Bojnord (KUB) as the experimental group (EG) and control group (CG) respectively. A 40-item minimal pair test was developed based on the 3rd edition of the book Ship or Sheep written by Baker (2006). The reliability of the test was estimated 0.75 through KR-21 formula. After the pretest administration, both groups were exposed to the same activities; however, only the EG received the treatment regarding explicit pronunciation instruction. At the end of an eight-week training program, the pretest was used as the posttest. The results of the independent samples t-test from the posttest revealed that the EG had a better performance than the CG suggesting that EFL learners’ vowel perception can improve if they are explicitly made aware of their pronunciation errors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.145

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.320
Teacher spread0.312 · 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.

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

Citations6
Published2016
Admission routes1
Has abstractyes

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