MétaCan
Menu
Back to cohort
Record W4389523464 · doi:10.23977/aetp.2023.071620

Leadership Development in Educational Management: Successful Cases and Best Practices

2023· article· en· W4389523464 on OpenAlexvenueno aff
Jiaxi Zhang

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEducational leadershipQuality (philosophy)Public relationsBest practiceKnowledge managementEngineering ethicsPolitical scienceBusinessSociologyEngineeringPedagogyComputer science

Abstract

fetched live from OpenAlex

With the rapid development of education in the 21st century, the role of leadership in educational management has become increasingly crucial. This article comprehensively explores how to cultivate and develop leadership in the field of education through in-depth research on various successful cases and best practices. By analyzing the practical application of leadership in educational institutions, the paper also discusses the positive impact of leadership on enhancing education quality, promoting school efficiency, and inspiring educational innovation. Educational innovation is a key issue in the contemporary education sector, and the effective role of leadership can serve as an engine for driving innovation. Leaders with an innovation-oriented approach can encourage teachers to experiment with new teaching methods and adopt advanced technological tools, thereby stimulating students' interest and potential for learning. Enlightened decision-making and active support from leaders also contribute to breaking the constraints of traditional education, making schools more dynamic in adapting to emerging educational trends. In conclusion, a profound understanding and effective cultivation of leadership are crucial for establishing a stronger, more flexible, and adaptive educational management team. This not only helps improve education quality and school efficiency but also drives educational innovation, enabling educational institutions to better adapt to and lead the rapidly changing educational environment of today.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.117
GPT teacher head0.472
Teacher spread0.355 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Educational Technology and PsychologySame topicTechnology-Enhanced Education StudiesFrench-language works237,207