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Record W2788970100 · doi:10.18806/tesl.v34i2.1266

Comparing the Effectiveness of Processing Instruction and Production-Based Instruction on L2 Grammar Learning: The Role of Explicit Information

2017· article· en· W2788970100 on OpenAlexvenueno aff
Adem Soruç, Jingjing Qin, YouJin Kim

Bibliographic record

VenueTESL Canada Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyGrammarTurkishLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article reports on a study that investigated whether processing instruction (PI) or production-based instruction (PBI) is more effective for the teaching of regular past simple verb forms in English. In addition, this study examined whether explicit grammatical information (EI) mediates the effectiveness of PI or PBI. A total of 194 Turkish EFL students were randomly assigned to one of the four experimental groups—PI+EI, PI–EI; PBI+EI, PBI–EI—or a control group and then completed interpretation and production tasks. The results demonstrated that (a) the PI–EI group and PBI–EI group performed equally well on both interpretation and production tasks; (b) when EI was a factor, the PI+EI group outperformed the PBI+EI group on only the interpretation task, while no significant difference was found on the production task; (c) no significant differences were found between the PI+EI or –EI groups, and the PBI+EI or –EI groups. Pedagogical implications of these findings are discussed, and suggestions made for future research.Cet article porte sur une étude qui a voulu déterminer quelle méthode – l’instruction basée sur la compréhension et impliquant une réflexion sur le sens des formes (PI) ou l’instruction basée sur la production (PBI) – est plus efficace pour l’enseignement des formes verbales du passé en anglais. De plus, cette étude a examiné le rôle de l’information grammaticale explicite (EI) sur l’efficacité de l’instruction PI et de l’instruction PBI. Nous avons réparti, de façon aléatoire, 194 étudiants d’ALE d’origine turque à un de quatre groupes expérimentaux - PI+EI, PI–EI; PBI+EI, PBI–EI – ou à un groupe témoin. Par la suite, les étudiants ont complété des tâches d’interprétation et de production. Les résultats indiquent que : (a) le rendement du groupe PI–EI aux tâches d’interprétation et de production était aussi bon que celui du groupe PBI–EI; (b) quand l’information grammaticale explicite (EI) jouait un rôle, le rendement du groupe PI+EI aux tâches d’interprétation était supérieur à celui du groupe PBI+EI mais aucune différence significative n’a été constatée pour la tâche de production; (c) aucune différence significative n’a été constatée entre les groupes PI+EI et les groupes –EI, ni entre les groupes PBI+EI et les groupes –EI. Nous discutons des implications pédagogiques de ces résultats et offrons des suggestions de recherche complémentaire.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.016
GPT teacher head0.211
Teacher spread0.195 · 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 designOther design
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

Citations2
Published2017
Admission routes1
Has abstractyes

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