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Record W4214736638 · doi:10.5430/wje.v12n1p45

ELLs in Higher Education: Learning Strategy Use and Goal Orientation

2022· article· en· W4214736638 on OpenAlexvenueno aff

Bibliographic record

VenueWorld Journal of Education · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersScience Foundation of China University of Petroleum, BeijingChina University of Petroleum, Beijing
KeywordsEllGoal orientationPsychologyBachelorBachelor degreeOrientation (vector space)Mathematics educationTeaching methodSocial psychologyMathematics

Abstract

fetched live from OpenAlex

This study examined language learning strategy and goal orientation of college-level English Language Learners (ELLs) by using a questionnaire survey. It analyzed the relationship between goal orientation and demographic characteristics and further explored the correlation between learning strategy use and goal orientation. The results of the study show that non-Asian ELLs had a greater performance goal orientation tendency than Asian ELLs. ELLs who had bachelor’s degree had a higher level of mastery goal orientation, as well as performance-approach goals than those who had master’s and doctoral degree. Female ELLs had a higher level of mastery goal orientation than male ELLs. Mastery goal orientation is positively related to all types of strategy, and it possessed the beneficial role in strategy use. Effective instructional methods for ELLs were provided to promote their adopting of mastery goals.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0020.001
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 head0.058
GPT teacher head0.297
Teacher spread0.239 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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Same venueWorld Journal of EducationSame topicEFL/ESL Teaching and LearningFrench-language works237,207