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Record W2965589210 · doi:10.35631/ijepc.4310017

ESSENTIAL ELEMENTS OF CHILDREN’S STORY BOOKS IN ISLAMIC PEDAGOGY BASED ON AL-QURAN TO CULTIVATE PROSOCIAL BEHAVIOUR AMONG PRESCHOOL CHILDREN

2019· article· en· W2965589210 on OpenAlexaff
Ilyani Mohd Rosmadi, Zainiah Mohamed Isa

Bibliographic record

VenueInternational Journal of Education Psychology and Counseling · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsProsocial behaviorPsychologyNarrativeTest (biology)Significant differenceRepetition (rhetorical device)Developmental psychologyMathematics educationSocial psychologyLiteratureLinguisticsArtMathematicsPhilosophy

Abstract

fetched live from OpenAlex

It is a very concerning situation we are having today when seeing youngsters showing less involvement and not being helpful toward the ones in need. Having children to be exposed to storybooks is to introduce them with moral values that help in building their characters. Storybooks are developed containing pedagogies adapted from the Quran that convey the value of prosocial behavior effectively. The pedagogies are narrative, dialogue, repetition, and questioning. Typography, illustrations and simplified phrases are additional elements that are also included. This research involved 60 children aged 5 to 6 years old from selected preschools in Malaysia. 30 children are presented with the original version of the storybooks and the rest are presented with modified storybooks. Modified Prosocial Behaviour Questionnaire which consists of 15 items is required to be filled during pre and post-test. There was no significant difference in the pretest (M= 32.07, SD= 3.89) and post-test (M= 32.80, SD= 8.57) when using the original books; t(29)= -0.427, p= 0.672 while there was a significant difference in the pretest (M= 23.83, SD= 7.33) and post-test (M- 32.50, SD= 7.93) when using the modified books; t(29)= -16.478, p= 0.000.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.380
Teacher spread0.371 · 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.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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