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Record W4380151792 · doi:10.5430/wje.v13n2p31

Empowering Teachers' Learning to Develop Students' Inspirational Skills

2023· article· en· W4380151792 on OpenAlexvenueno aff
Montri Kromthamma, Phramaha Suphachai Supakicco

Bibliographic record

VenueWorld Journal of Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyEmpowermentAction researchProfessional developmentVariety (cybernetics)Mathematics educationPedagogyConceptual frameworkSociologyComputer science

Abstract

fetched live from OpenAlex

This research was based on a project to empower teachers to develop their skills as motivational players for their students. It is one of a series of research projects on 21st century skills which was an operation that recognized the importance of the knowledge-based and digital society. It brought together a variety of perspectives on the development of 21st century skills spreading across the Internet. The gathered data were processed through research methodology leading to the attainment of educational innovations that can be used for the development of people who would later develop their own work for the professional betterment. It was expected that if a person has knowledge and put that knowledge into practice, it would empower that people to work more efficiently. By doing so, a working concept is changed from "knowledge is power" to "knowledge and action is power". From this concept had led to the conceptual framework of Research and Development (R&D) methodology used in this research that encourages the use of educational innovations for teacher empowerment then teachers apply the learned knowledge for the student development. The outcome of this current research is an innovation called an online self-learning program for the teacher empowerment and the development of teachers’ skills as student motivator. The online learning program was attested through the research method and proved to have helped the teachers and the students to attain the following criteria: 1) The teacher learning outcome on the posttest score met the standard criteria of 90/90 and the posttest score was significantly higher than the pretest score, and 2) The posttest score from the students' inspirational skill assessment was significantly higher than the pretest score. Based on this finding, it was sufficient to say that the online self-learning program it's efficient to be used for the development of teachers and students in the secondary schools under the jurisdiction of the national commissions of basic education. The application of this online learning program would be beneficial for educational management and encourage freedom of learning where people can learn anywhere anytime.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.419
Teacher spread0.397 · 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 designNot applicable
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

Citations7
Published2023
Admission routes1
Has abstractyes

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