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Record W1976098679 · doi:10.1080/09658416.2013.863899

Differential effects of explicit form-focused instruction on morphosyntactic development

2014· article· en· W1976098679 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage Awareness · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsPluralPsychologyLinguisticsNounDifferential effectsGrammarControl (management)MorphemeCognitive psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This study explores whether and to what degree explicit form-focused instruction (FFI) facilitates the use of morphosyntactic forms in second language oral production and also whether it has differential effects on morphosyntactic forms with different linguistic variables. Twenty-seven university-level Chinese EFL participants were randomly assigned to a control group and an experimental group. While the control group watched a television episode in English, the experimental group completed two form-focused activities (rule review and self-correction) designed to draw their attention to noun plural, past tense, and third-person singular in English in their oral production. All participants completed oral production pre- and post-test measures, the results of which showed that explicit FFI promoted the use of the target forms and that the facilitative effects were dependent on the complexity and regularity of the morphosyntactic forms. Regular (as opposed to irregular) and more complex morphosyntactic forms appeared to benefit more significantly from explicit FFI.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.452

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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