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Record W2594145428 · doi:10.5539/ies.v10n3p176

An Increasing of Primary School Teachers’ Competency in Brain-Based Learning

2017· article· en· W2594145428 on OpenAlexvenueno aff
Chaiwat Waree

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
FundersSuan Sunandha Rajabhat University
KeywordsMathematics educationPsychologyCluster samplingEmpowermentStatistical significanceTest (biology)Primary educationMedical educationMedicineMathematicsStatistics

Abstract

fetched live from OpenAlex

The purpose of the study was to develop a powerful and empowering guide (CBT) of elementary school teachers, to compare the ability of elementary school teachers. Management learning uses brain as a base. The experimental group with a control group the experimental group used in this research was a teacher at the grade level. 4-6 in province By randomization group (Cluster Sampling) 2 Education Service Area Office, District 15 schools, three people were 90 percent of the control group in this study is grade 4-6 teachers in the Samut Songkram Province has a total of 90 people selected by model. The instruments used in the trial include training courses Empowerment (CBT) of elementary school teachers. After training, the test results of 60 studies found that the development of training courses to increase the capacity of the elementary school teachers. The experts found that the overall effectiveness of the program at the highest level. Before and after the process of empowerment (CBT), t equals 58.01 posttest scores higher than the previous level of statistical significance .05, comparing the capabilities of elementary school teachers. The experimental group with the control group, the experimental group was 47.98 t test scores than the control group, the experimental group had a statistically significant level .05.

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)0.000
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
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 science0.0000.000
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 head0.081
GPT teacher head0.397
Teacher spread0.316 · 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.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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