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Record W2297306746 · doi:10.1515/lifijsal-2015-0008

Vocabulary learning: The effect of instruction type and methodological choices in the context of French as a second language

2015· article· en· W2297306746 on OpenAlexafffund
Farzin Gazerani, Ahlem Ammar, Isabelle Montésinos‐Gelet

Bibliographic record

VenueLanguage in Focus · 2015
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec-Société et Culture
KeywordsVocabularyReading (process)Repetition (rhetorical device)PsychologyContext (archaeology)Vocabulary developmentCognitive psychologySecond-language acquisitionComputer scienceMathematics educationLinguisticsTeaching method

Abstract

fetched live from OpenAlex

Abstract Research indicates that lexical gains through reading are limited (Nation, 2001). Based on the literature about form focused instruction (FFI) (instruction that draws learners’ attention to the formal properties of of the target language) in second language (L2) acquisition, Laufer (2005) states that it is necessary to combine reading with FFI targeting vocabulary. The objective of this study is to examine the effects of different FFI teaching approaches and methodological choices on vocabulary learning. Nine intermediate adult Iranian learners of French as an L2 participated in this experimental multiple-case study. The experimental intervention was spread over a period of two weeks and targeted 36 vocabulary items. It comprised three experimental conditions (integrated FFI, isolated FFI and repetition) and a control condition (incidental learning through reading). Results indicate significant benefits of FFI on receptive immediate posttests. The intervening effects of recency and receptive and productive tests administration order are also evaluated.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0040.000

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 head0.034
GPT teacher head0.358
Teacher spread0.324 · 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
Published2015
Admission routes2
Has abstractyes

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