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Record W3129089152 · doi:10.5539/ies.v14n2p63

Synthesis of Plans to Increase the Results of Ordinary National Education Test by All-Round Tutoring Process for Primary School Grade 6

2021· article· en· W3129089152 on OpenAlexvenueno aff
Nuttakan Pakprod, Kanokrat Jirasatjanukul, Damrong Tumthong, Prapa Amklad, Wipa Lekchom

Bibliographic record

VenueInternational Education Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)National standardMathematics educationStandard deviationNational educationPsychologyPrimary educationBasic educationMathematicsStatisticsPedagogyEngineering

Abstract

fetched live from OpenAlex

The objective of this research is to study the results of activities to increase the scores of Ordinary National Education Test. Cluster; teachers of Phetchaburi Rajabhat University comparing the results of Ordinary National Education Test in 2017-2018 and studying the satisfaction of the activities. The target group is 49 schools in Phetchaburi and Prachuap Khiri Khan Provinces, data were analyzed using mean and standard deviation. The study found that the difference of the scores of the Ordinary National Education Test was higher in 32 schools and there is a difference in scores of Ordinary National Education Test tests lower by 2 schools, representing 94.12, with the satisfaction of the participation in the activity of increasing the basic educational testing at the basic level is at a high level with an average of 4.22, standard deviations 0.73, which the participants are satisfied with the process. The process of organizing activities was at the highest with an average of 4.28, standard deviations 0.76 and continues organizing activities to increase the scores of Ordinary National Education Test.

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)0.049
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.049
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 integrity0.0000.000
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 head0.087
GPT teacher head0.480
Teacher spread0.393 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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