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Record W3112087655 · doi:10.5539/jel.v10n1p7

Empirical Research on Leadership Capacity of Secondary Vocational Teachers in Yunnan Province of China

2020· article· en· W3112087655 on OpenAlexvenueno aff
Xiaoyao Yue

Bibliographic record

VenueJournal of Education and Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
FundersChina Postdoctoral Science Foundation
KeywordsLikert scalePromotion (chess)Vocational educationEducational leadershipPsychologyInstructional leadershipPedagogyProfessional developmentChinaMathematics educationSociologyPolitical science

Abstract

fetched live from OpenAlex

Teacher leadership continues to be a growing educational reform initiative across the world. With the rapid development of Chinese language education, the role of teacher leadership in education reform is becoming more and more prominent. Based on the survey data of 104 teachers in a secondary vocational school in Yuxi City, this study investigated the level of teacher leadership capacity and discussed their promotion strategies. Based on Lambert’s (2003a) theory of teacher leadership capacity, the author developed a research questionnaire that including four structures of teacher leadership capacity, which focus on the vision, reflection and innovation, shared governance, supervision, and response to student achievement. This study adopted the five-likert point scale. Data analysis shows that the average scores of 17 items does not exceed 4.00 points, while the highest and lowest score are from “focus on the vision.” To improve the teacher leadership capacity, the study suggests that leaders should concentrate on the school’s vision as well as establish collaborative culture and atmosphere among teachers.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.438
GPT teacher head0.490
Teacher spread0.052 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2020
Admission routes1
Has abstractyes

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