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Record W2610921644 · doi:10.18806/tesl.v34i1.1256

Promoting Process-Oriented Listening Instruction in the ESL Classroom

2017· article· en· W2610921644 on OpenAlexvenueno aff
Hương Thị Lan Nguyễn, Marilyn L. Abbott

Bibliographic record

VenueTESL Canada Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningListening comprehensionPsychologyProcess (computing)Mathematics educationComprehensionProduct (mathematics)PedagogyLinguisticsComputer scienceCommunication

Abstract

fetched live from OpenAlex

When teaching listening, second language instructors tend to rely on product-oriented approaches that test learners’ abilities to identify words and answer comprehension questions, but this does li le to help learners improve upon their listening skills (e.g., Vandergri & Goh, 2012). To address this issue, alternative approaches that guide learners through the listening process toward improved comprehension and uency have been recommended in the literature. Based on a review of 6 popular intermediate adult English as a second/foreign language (ESL/EFL) textbooks, we found that most of the listening activities in the texts exemplified a product-oriented approach (testing word recognition or listening comprehension) rather than a process-oriented approach (providing instruction to aid in word recognition and comprehension). To enhance the integration of process-oriented approaches for teaching listening, we provide suggestions for activities to supplement product-oriented teacher-made and textbook activities. We begin with an overview of second language listening theory and research that justi es the incorporation of process-oriented instructional approaches in the ESL classroom. Then we report the results of our textbook review and present examples of recommended activity types that teachers and textbook writers could incorporate into their instructional materials to encourage a balanced approach to teaching listening.Quand les enseignants de langue seconde enseignent l’écoute, ils ont tendance à sefier aux approches orientées sur le produit qui évaluent la capacité de leurs élèves à identifier des mots et à répondre à des questions de compréhension. Pourtant, ce e méthode ne contribue que très peu à l’amélioration des habiletés d’écoute des élèves (par ex., Vandergri & Goh, 2012). Pour aborder ce e question, les chercheurs recommandent des approches alternatives qui guident les apprenants au l du processus d’écoute de sorte à améliorer la compréhension et les compétences. Un examen de 6 manuels populaires d’anglais langue seconde ou étrangère pour adulte a révélé que la plupart des activités d’écoute sont orientées sur un produit (évaluation de la reconnaissance des mots ou la compréhension à l’écoute) plutôt que sur un processus (directives pour aider la reconnaissance des mots et la compréhension). Pour me re en valeur l’intégration des approches axées sur le processus dans l’enseignement de l’écoute, nous o rons des suggestions d’activités pour enrichir les activités créés par les enseignants ou provenant des manuels et qui sont axées sur le produit. Nous commençons par un survol de la recherche et de la théorie qui portent sur l’écoute en langue seconde et qui jus- ti ent l’intégration dans les cours d’ALS d’approches pédagogiques axées sur le processus. Ensuite, nous présentons les résultats de notre examen de manuels et recommandons des exemples de types d’activités que les enseignants et les auteurs de manuels pourraient incorporer dans leur matériel pédagogique pour o rir une approche équilibrée à l’enseignement de l’écoute.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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