Play-Based Learning as a Pedagogical Approach to Promote Islamic Values in Early Childhood Education
Bibliographic record
Abstract
This research article explores the integration of play-based learning and Islamic values in early childhood education, aiming to understand how playful experiences can enhance moral and social development in young learners. Employing a systematic literature review methodology, the study synthesises findings from various scholarly articles to identify key themes and effective teaching strategies. The significant findings reveal that play serves as a crucial medium for developing moral values, social skills, cognitive abilities, and cultural awareness among children. Specifically, play-based activities foster empathy, cooperation, and critical thinking while promoting respect for diversity. Effective strategies such as storytelling, role play, cooperative games, and creative expression are highlighted as valuable methods for teaching Islamic values. In conclusion, integrating play-based learning with Islamic values education offers a holistic approach to nurturing well-rounded individuals. This research contributes to the existing body of knowledge by providing a comprehensive overview of how play can instil ethical principles and foster social responsibility in early childhood settings. By emphasising the importance of play in moral development, this study encourages educators to adopt innovative practices that align with educational and cultural objectives, ultimately preparing children for compassionate and responsible participation in society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".