MétaCan
Menu
Back to cohort
Record W1972186878 · doi:10.5539/ijel.v1n2p203

The Relationship between Language Learning Motivation and the Choice of Language Learning Strategies among Chinese Graduates

2011· article· en· W1972186878 on OpenAlexvenueno aff
Xiuyan Xu

Bibliographic record

VenueInternational Journal of English Linguistics · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyNormalityDescriptive statisticsTest (biology)Mathematics educationPearson product-moment correlation coefficientLanguage learning strategiesCorrelationChinese languageNormality testStatistical hypothesis testingSocial psychologyStatisticsMathematicsLinguisticsCognition

Abstract

fetched live from OpenAlex

This research is aimed to investigate the relationship between language learning motivation and the choice of language learning strategies among Chinese graduates of non-English majors. A total of 300 graduates participated in this survey research and 284 subject responses were valid and used for the statistical analysis. The collected data were computed and analyzed through descriptive statistics, test of normality, test of linearity and Pearson correlation. The major findings of the study were: (1) Chinese graduates tended to be more extrinsically motivated. (2) Their motivation was found significantly correlated with their learning strategy use. The more motivated students were the more strategies they tended to use. (3) Motivational strength and personal goals were found to have the highest correlation with the overall strategy use among Chinese graduates.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.297
Teacher spread0.250 · 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

Citations46
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicEFL/ESL Teaching and LearningFrench-language works237,207