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Record W3179122808 · doi:10.5539/ijel.v11n4p76

A Study on the Effects of Chinese EFL Learners’ English Proficiency and Involvement Load on Incidental Vocabulary Acquisition

2021· article· en· W3179122808 on OpenAlexvenueno aff
Yao Fan

Bibliographic record

VenueInternational Journal of English Linguistics · 2021
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyTest (biology)PsychologyReading (process)Task (project management)Reading comprehensionMathematics educationComputer scienceLinguisticsEngineering

Abstract

fetched live from OpenAlex

The effects of EFL learners’ English proficiency and involvement load induced by tasks on incidental vocabulary acquisition are observed in this study. 163 students of non-English majors in a local university of China were divided into two groups of different English proficiency according to their scores of College English Test Band 4 (CET-4). The students in each group were randomly assigned one of three tasks (reading-for-comprehension, blank-filling, and writing) involving 10 target words. Fifteen minutes after they finished the task, they were required to take an immediate vocabulary test about the target words. Two weeks later, they were asked to take the same kind of vocabulary test to examine their delayed memory of the target words. All of the students did not know about the vocabulary tests beforehand. The results show that: in the process of immediate incidental vocabulary acquisition, both learners’ English proficiency and involvement load have a main effect on immediate memory, but the interactive effect of these two factors on incidental vocabulary acquisition is not significant; in the vocabulary retention test, learners’ English proficiency does not have a significant main effect on delayed memory, but the main effect of involvement load is still significant; at the same time, the interactive effect of these two factors is still not significant.

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)0.045
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.045
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)0.0010.000

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 head0.315
Teacher spread0.302 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicSecond Language Acquisition and LearningFrench-language works237,207