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Record W4385249211 · doi:10.55849/ijen.v1i4.382

Analysis of Children’s Numeracy Skills in The Village Pagar Dewa Kaur with Math Approach Realistic

2023· article· en· W4385249211 on OpenAlex
Jessica Adelia Saputri, Resti Komala Sari, Uwe Barroso, Eladdadi Mark

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Educational Narratives · 2023
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNumeracyMathematics educationTest (biology)CurriculumFactor (programming language)MathematicsPsychologyPedagogyComputer scienceLiteracy

Abstract

fetched live from OpenAlex

Background. The relevance of math materials to children's daily lives is an important factor in the success of this approach. Purpose. This study aims to analyze the counting ability of children in Pagar Dewa Village Kaur with Realistic Mathematics approach. Method. The research sample consisted of 30 children aged 6-8 years. Data was collected through counting ability test and observation. Results. he results showed that most of the children in Pagar Dewa Village Kaur had low counting skills. However, after learning with the Realistic Mathematics approach, there was a significant increase in children's understanding and application of mathematical concepts. Conclusion. This study provides recommendations for educators and curriculum developers to apply the Realistic Mathematics approach in children's mathematics learning in rural areas.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.384
Teacher spread0.348 · 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