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Enhancing Early Mathematics Learning Through an Interactive Storybook: A Development and Validation Study

2025· article· W4415980193 on OpenAlexaff
Yeni Solfiah, Mohd Zakree Ahmad Nazri, Devi Risma, Defni Satria, Nanda Pratiwi, Eva Eriani, Mastuinda Mastuinda

Bibliographic record

VenueJurnal Pendidikan Progresif · 2025
Typearticle
Language
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsNormalityQualitative propertyEarly childhoodEarly childhood educationTest (biology)Descriptive statisticsHomogeneity (statistics)Data collection

Abstract

fetched live from OpenAlex

Enhancing Early Mathematics Learning Through an Interactive Storybook: A Development and Validation Study. Objective: This research aims to develop and implement an active mathematics learning paradigm for early childhood through illustrated storybooks that integrate fundamental mathematical concepts, namely numbers, patterns, geometry, measurement, and statistics. The goal is to provide a developmentally appropriate platform that encourages engagement, improves math proficiency, hones problem-solving skills, and makes learning more meaningful and enjoyable. Methods: The methodology used is a development research based on the Dick and Carey model. The validation process involved mathematicians, early childhood education experts, kindergarten educators, and media experts. Data were obtained through surveys, interviews, observations, and limited trials involving 14 children aged 5–6 years in Pekanbaru, Riau Province, Indonesia. Quantitative data analysis employed descriptive statistics, pretest-posttest comparisons, normality tests, and homogeneity tests. At the same time, qualitative data were obtained from expert evaluations and instructor comments. Findings: The validation results showed that the developed media met the criteria of validity, practicality, and efficacy, with scores from PAUD experts of 88.00%, mathematics experts of 89.33%, early childhood teachers of 81.54%, and media experts of 88.00%, with an overall category of "very good". In the limited trial stage, an average pretest score of 17.59 and a posttest score of 25.2 were obtained, indicating a significant increase in all mathematics indicators. The normality test (p > 0.05) indicated that the data were normally distributed, while the homogeneity test (p > 0.05) indicated that the data were homogeneous. The t-test results showed that the calculated t-value for all indicators was greater than the t-table value (1.771) with a significance level of 0.000 < 0.05, indicating that the media had a significant impact on improving children's mathematics abilities. Observations revealed positive responses from the children, including increased interest, focus, and active involvement. Conclusions: Active math storybooks have been recognized as an innovative learning tool for early childhood, helping educators create a stimulating learning environment and serving as an effective resource for parents. The design, which combines stories, games, and interactive activities, has been proven to strengthen children's math skills. Keywords: active learning design, early childhood, education, mathematics.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.359
Teacher spread0.327 · 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 designBench or experimental
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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