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Record W4382500714 · doi:10.5430/wjel.v13n6p97

Influence of Students Perceived Classroom Climate on English Language Learned Helplessness in China’s Vocational Colleges: Mediation of Classroom Silence and Academic Self-Efficacy

2023· article· en· W4382500714 on OpenAlexvenueno aff
Jia Qi Wei, Chia Ching Tu

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsLearned helplessnessSilenceScale (ratio)PsychologyMediationVocational educationChinaClassroom climateMathematics educationSocial psychologyPedagogySociologyPolitical scienceSocial scienceGeography

Abstract

fetched live from OpenAlex

In this study, we investigated the mediating effects of classroom silence and academic self-efficacy on the relationship between English classroom climate and learned helplessness among vocational college students. A total of 501 students from 5 postsecondary vocational colleges in Fujian Province, China, were assessed using the Classroom Climate Scale, Classroom Silence Scale, Learning Self-Efficacy Scale, and English Learned Helplessness Scale. Structural equation modelling was used to evaluate the mediating effects of classroom silence and academic self-efficacy on the relationship between classroom climate and learned helplessness. We found that perceived classroom climate negatively affected students’ learned helplessness. In addition, classroom silence and academic self-efficacy fully mediated the relationship between perceived classroom climate and learned helplessness. This study provides relevant recommendations for educational administrators, English teachers, and students.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.381
Teacher spread0.356 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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