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Record W2990589727 · doi:10.5539/ijel.v9n6p445

Explicit Teaching and Incidental Learning of Vocabulary: Where Is the Pendulum Swinging to?

2019· article· en· W2990589727 on OpenAlexvenueno aff
Faisal Al-Homoud

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
FundersMajmaah University
KeywordsVocabularyReading (process)Meaning (existential)RecallPsychologyMathematics educationVocabulary learningLinguisticsCognitive psychologyPhilosophy

Abstract

fetched live from OpenAlex

The research at hand compared two conditions of L2 vocabulary exposures, i.e. incidental exposure and a mixture of incidental and explicit exposures to words. Forty-five female participants, majoring in English at Al-Imam Mohammad Ibn-Saud Islamic University, Saudi Arabia participated in this research. They were divided into two groups: Reading Only (RO) and Reading Extra (RE). In the RO group, the target words were exposed only through a reading passage that they read twice, while the same target words for the RE group were inserted in the same reading passage, then explained directly by the teacher. Three levels of vocabulary knowledge (form recall, meaning recall, and meaning recognition) were assessed. The results showed that both conditions cater for vocabulary learning, however the RE group had significantly outperformed their RO counterparts. Moreover, the results showed that vocabulary learning in this study followed the general tendency starting from a receptive level to a productive level.

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)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.015
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 integrity0.0000.001
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 head0.009
GPT teacher head0.304
Teacher spread0.295 · 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 designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

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