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A Correlational Study of Language Learning Motivation and Strategies of Chinese Undergraduate UNE ÉTUDE CORRÉLATIVE SUR LA MOTIVATION DE L'APPRENTISSAGE DE LANGUE ET LA STRATÉGIES DES ÉTUDIANTS CHINOIS DU PREMIER CYCLE

2010· article· fr· W1951148164 on OpenAlexvenueno aff
Chun-huan Feng

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languagefr
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsLanguage acquisitionPsychologyLanguage learning strategiesExperiential learningMathematics educationPedagogyCognitionMetacognition

Abstract

fetched live from OpenAlex

Since the 1960s the focus of research in second language acquisition has shifted from teaching to learning, and language learners become the center of language teaching and learning. As to learners, language learning motivation and language learning strategies are two main research topics. The present study investigates Chinese college students’ motivation types and strategy use as well as the relationships between language learning motivation and language learning strategies. The study aims to show whether motivation is related to learning strategies, and to shed light on the study of learning motivation, learning strategies, and pedagogy. Key Words: language learning motivation; language learning strategies; gender; correlation

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)0.004
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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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