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Record W2575093256 · doi:10.5539/ijel.v7n2p124

Retrospects and Introspects of Researches on Listening Strategies at Home and Abroad

2017· article· en· W2575093256 on OpenAlexvenueno aff
Huajie Zhou, Wang Zhi

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningStatus quoPsychologyInformational listeningProcess (computing)Field (mathematics)CognitionCognitive strategyMathematics educationListening comprehensionComputer sciencePolitical scienceCommunication

Abstract

fetched live from OpenAlex

Listening strategies refer to thoughts or activities that language learners often use in the process of listening. Listening strategies are the vital branches of learning strategies, and as researches of learning strategies become a specialized research field, researches of listening strategies have spread to the aspects of meta-cognitive strategies, cognitive strategies, socialized and affective strategies, strategy-training, strategy-guiding, strategy-instruction etc. In recent years, with the continuous efforts of scholars at home and abroad, researches of listening strategies tend to be more elaborate in depth and length, which reflects on research contents, research fields, research methods, research subjects etc. In this paper, the authors have mainly made researches on the research status quo of English listening strategies at home and abroad and have given reflections on the research deficiencies. It is expected that we could improve both the learners’ listening proficiency and the strategy-instruction in EFL classrooms at home and abroad.

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)0.000
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.375
Teacher spread0.351 · 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.

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
Published2017
Admission routes1
Has abstractyes

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