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Record W4392960762 · doi:10.23977/aetp.2024.080205

A Study on the Relationship between Foreign Language Enjoyment and English Learning Performance in Chinese Context: the Mediating Role of L2 Grit

2024· article· en· W4392960762 on OpenAlexvenueno aff
Yuan Gao, Jiayi Cui

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsGritPsychologyContext (archaeology)Foreign languageEnglish as a foreign languageLinguisticsSocial psychologyMathematics educationHistoryPhilosophy

Abstract

fetched live from OpenAlex

Foreign language learning is a complex process that can be influenced by internal, external and other variables. However, studies that focus on language learners' emotions such as foreign language enjoyment and learners' personality such as L2 grit are still in its infancy, especially in Chinese context. With the development of positive psychology, it is crucial to explore the relationship between positive emotions and learners' foreign language learning performance. Therefore, the study attempts to investigate the relationship between foreign language enjoyment and learners' English learning performance in Chinese context. The data were collected from 766 senior high school students in China. Findings of this study revealed that there existed positive and significant correlations among foreign language enjoyment, English learning performance and L2 grit but at different levels. Besides, L2 grit played mediating role between foreign language enjoyment and English learning performance. At last, implications and suggestions for future research are also discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.372
Teacher spread0.350 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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