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Record W2735290982 · doi:10.66887/jltl.v6i1.17

The effect of training on vocabulary strategy use: Explicit teaching of word family, word network and word card strategies

2019· article· en· W2735290982 on OpenAlex
Constance Lavoie

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

VenueJournal of Language Teaching and Learning · 2019
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsWord (group theory)VocabularyControl (management)Vocabulary developmentComputer scienceTraining (meteorology)PsychologyArtificial intelligenceNatural language processingLinguistics

Abstract

fetched live from OpenAlex

This study measured the impact of explicit teaching of three lexical strategies on the extent to which these strategies were used when faced with unknown words. Seven elementary school teachers from different Innu communities implemented three vocabulary strategies (word family, word network and word card) for a period of three weeks. To assess the impact of strategy training, the students in the experimental (N = 39) and control groups (N = 15) performed tasks using the targeted strategies. There was a statistically significant difference between the two groups, with the experimental group using more efficiently the strategies taught. These results confirmed the positive impact that explicit teaching of vocabulary strategies and it describes the progress made by the students regarding strategic use.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.305
Teacher spread0.288 · 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