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Record W4412847264 · doi:10.18806/tesl.v42i1/1423

Enhancing Intermediate English Learners’ Proficiency in Narrative Tenses

2025· article· en· W4412847264 on OpenAlexvenueno aff
Tetyana Bidna

Bibliographic record

VenueTESL Canada Journal · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeLinguisticsPsychologyLanguage proficiencyMathematics educationPhilosophy

Abstract

fetched live from OpenAlex

This article explores the meaning, form, and pronunciation of narrative tenses for intermediate English language learners, addresses common learner issues, and proposes solutions through a combination of literature review and classroom-based activities. Challenges include differentiating between tenses, correct usage, and pronunciation of past forms. Solutions involve using engaging activities and games to enhance understanding and retention. Additionally, the article addresses teaching issues related to memorization and pronunciation of irregular verbs, offering methodologies for improving student engagement and accuracy. Practical strategies are provided to help language teachers improve narrative tense instruction and overcome common obstacles in language learning. Cet article explore le sens, la forme et la prononciation des temps verbaux narratifs pour les apprenants d’anglais de niveau intermédiaire, aborde les défis communs des apprenants et y propose des solutions en combinant une revue de la littérature et des activités à réaliser en classe. Les défis comprennent la différenciation des temps verbaux, l’usage correct et la prononciation des formes du passé. Les pistes consistent à utiliser des activités et des jeux engageants pour améliorer la compréhension et la rétention. En outre, l’article aborde les défis d’enseignement liés à la mémorisation et à la prononciation des verbes irréguliers, en proposant des moyens pour améliorer l’engagement et la précision des apprenants. Des stratégies pratiques sont proposées pour aider les enseignants de langues à améliorer l’enseignement des temps narratifs et à surmonter les obstacles communs à l’apprentissage des langues.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.229
Teacher spread0.217 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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