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Record W2803506753 · doi:10.5539/ijel.v8n5p125

A Verification of Involvement Load Hypothesis on Chinese Adult English Learners

2018· article· en· W2803506753 on OpenAlexvenueno aff
Shuyun Huang

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyTest (biology)Repetition (rhetorical device)InferencePredictabilityPsychologyCognitionComputer scienceCognitive loadCognitive psychologyLinguisticsArtificial intelligenceStatisticsMathematics

Abstract

fetched live from OpenAlex

The present research designed six tasks with various distributions of involvement components: need, search and evaluation to verify the predictability of Involvement Load Hypothesis on Chinese adult English learners. The results showed that the vocabulary exercises did facilitate the incidental vocabulary acquisition, but the exercise with higher involvement load did not necessarily benefit the students more than the exercise with lower involvement. Three components of involvement did not reveal the same effect on incidental vocabulary acquisition. And the superiority of exercise with higher involvement load existing in the immediate vocabulary test did not survive in the delayed vocabulary test. In the delayed vocabulary test there were not any statistically significant differences among six groups. The further analysis reported besides the cognitive processing aroused by the tasks, other critical factors also worked on the incidental vocabulary acquisition: inference skill and repetition of occurrence.

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)0.000
metaresearch head score (Gemma)0.084
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 score0.705
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.084
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)0.0060.000

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 head0.019
GPT teacher head0.316
Teacher spread0.297 · 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
Published2018
Admission routes1
Has abstractyes

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