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Record W4393312523 · doi:10.5539/ies.v17n2p80

A Model for Supervision Management to Improve the Education by Using the Area as Base in Digital Era under Primary Educational Service Area in the Northeastern Region

2024· article· en· W4393312523 on OpenAlexvenueno aff
Warunee Teena, Sakdinaporn Nuntee, Chao Inyai

Bibliographic record

VenueInternational Education Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Leadership and Teacher Performance
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)Base (topology)Technology integrationService modelEducational technologyMathematics educationPedagogyComputer scienceSociologyPsychologyBusinessMarketingMathematics

Abstract

fetched live from OpenAlex

Educational reform in the modern era which the school administrators and all personnel in the school Must improve and develop themselves to keep up with changes in the era of globalization. By using the supervisory management model process to develop educational quality, these research objectives are to: 1) Study the problems and elements of supervision. Target group: 15 people 2) Create a supervisory model. By conducting in-depth interviews with 15 people involved. 3) Experiment with the supervision model with a sample group of 3 schools 4) Evaluate the use of the supervision model. By organizing a seminar with 15 experts and asking for opinions about its usefulness. Feasibility, appropriateness, and correctness of the format from 291 study supervisors. The instrument used was a questionnaire. Statistics were used to find the mean and standard deviation. It can be summarized as follows: 1) Problems in supervision include an insufficient number of supervisors. Study supervisors lack knowledge Lack of good supervision skills and no systematic planning. There are 5 important elements as follows: (1) objectives, (2) planning, (3) supervision, (4) monitoring and reflection, and (5) development and application. 2) Creating a model for supervision, including (1) objectives,(2) content of supervision, (3) process, (4) method, (5) supervisor and supervisor, (6) duration, (7) planning, (8) execution, (9) Evaluation (10) teamwork (11) network building (12) knowledge management (13) learning and quality development (14) building morale and (15) improving development. 3) The results of the trial use of the model had a reliability value of .80. Average comparison results in Knowledge before training and after training, tested with a t-test, and were found to be different. Statistically significant is at the .01 level. They were satisfied with the model. Overall, it is at the highest level (x̅ = 4.90, S.D. = 0.53) and the results of the overall evaluation of the use of the format are at the highest level (x̅ = 4.89) and overall satisfaction with the use of the format is at the highest level (x̅ = 4.63) 4) Model evaluation results are useful feasibility, suitability, and correctness. Overall, it is at the highest level (x̅ = 4.63, S.D. = 0.12).

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)0.000
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 score0.258
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.144
GPT teacher head0.405
Teacher spread0.260 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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