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Record W4404868294 · doi:10.5539/elt.v17n12p101

Working Memory, Task Type, and Chinese High School Students’ English Vocabulary Acquisition

2024· article· en· W4404868294 on OpenAlexvenueno aff
Weiqing Wang

Bibliographic record

VenueEnglish Language Teaching · 2024
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyVocabularyTask (project management)Vocabulary developmentLinguisticsShort-term memoryCognitive psychologyWorking memoryMathematics educationTeaching methodCognition

Abstract

fetched live from OpenAlex

Audiovisual learning is gaining increasing attention, with factors such as working memory and task type potentially influencing learning outcomes. This study examined English vocabulary acquisition among 110 Chinese high school English as a foreign language learners with varying levels of working memory (high and low) and different types of tasks (input-based and output-based). After engaging in an audiovisual activity, the learners were divided into six groups: a high capacity input group, a high capacity output group, a high capacity control group, a low capacity input group, a low capacity output group, and a low capacity control group. Two vocabulary tests were administered—one immediately after the tasks and the other two weeks later. Using repeated measures ANOVA, the findings revealed that (1) the high capacity learners significantly outperformed the low capacity learners on both the immediate and delayed tests; and (2) while the output groups showed better performance than the input groups on both tests, the differences were not statistically significant. These results add to the findings of existing research on second language (L2) vocabulary acquisition and provide valuable pedagogical insights aimed at improving L2 vocabulary instruction.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.000

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 head0.007
GPT teacher head0.299
Teacher spread0.292 · 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
Published2024
Admission routes1
Has abstractyes

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