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Record W6962549413 · doi:10.18415/ijmmu.v10i1.4378

The Effect of the Number Dice Game on the Logical-Mathematical Intelligence in Children 5-6 Years Old

2023· article· en· W6962549413 on OpenAlexaff

Bibliographic record

VenueInternational Journal of Multicultural and Multireligious Understanding · 2023
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsDiceNonprobability samplingChecklistData collectionSampling (signal processing)Significant difference

Abstract

fetched live from OpenAlex

This study aims to determine the effect of the number dice game on the logical-mathematical intelligence in children 5-6 years old. This study used a quantitative pre-experiment design method with one group pretest-posttest type. The sampling technique was purposive sampling, which consisted of 17 children. The data collection technique used the checklist observation sheet on the development of the ability to recognize number concepts. Then, the data is processed by t-test. The results showed that there was an average increase in children's ability to recognize the concept of numbers after being given a number dice game. The results of hypothesis testing also prove that t count is greater than t table. This means, that there is a significant difference between the pre-test and post-test in the experimental group. So, it can be said that the number dice game has an effect on the logical-mathematical intelligence in children 5-6 years old.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.073
GPT teacher head0.370
Teacher spread0.297 · 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 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

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