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Record W3030489404 · doi:10.5539/ies.v13n6p153

On the Relationship Between Teacher Autonomy and Learner Autonomy

2020· article· en· W3030489404 on OpenAlexvenueno aff
Ligang Han

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsLearner autonomyPracticumAutonomyPedagogyPsychologyForeign languageTeacher educationLanguage acquisitionLanguage educationMathematics educationPolitical scienceComprehension approach

Abstract

fetched live from OpenAlex

With the research on fostering and cultivating learner autonomy in foreign/second language teaching and learning, teacher autonomy has gained momentum in the research of foreign language teacher education. There have been many theoretical research and discussions about the definitions of learner autonomy. Many researchers acknowledge that language teachers play important roles in developing learner autonomy. However, the relationship between teacher autonomy and learner autonomy needs to be explored. The focal point of the present paper is a tentative discussion on the relationship between teacher autonomy and learner autonomy in foreign language education and teacher education. This paper sheds light to foreign language education and teacher education in that language teachers should change their traditional roles to ones catering and facilitating the development of learner autonomy, and teacher education and training programs should include and design courses, practicum to enhance and promote teacher-learner autonomy.

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)0.012
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.011
Scholarly communication0.0040.006
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.280
GPT teacher head0.382
Teacher spread0.102 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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