Application Of Deep Learning Model Towards The Instillation Of Moral Values In Early Childhood

Abstract

Background: Moral value development is a fundamental aspect of early childhood education because it shapes children's character, responsibility, honesty, respect, and positive social behaviour. The implementation of the Deep Learning model, which emphasizes meaningful, mindful, and joyful learning, is expected to support children's moral development through active and contextual learning experiences. Objective: This study aimed to examine the relationship between the implementation of the Deep Learning model and the moral value instillation of children aged 5–6 years at TK Cemarah Liliba. Method: This quantitative study employed an ex post facto correlational design involving 21 children selected through total sampling. Data were collected using a structured questionnaire measuring the implementation of the Deep Learning model and children's moral values and were analyzed using descriptive statistics, the Shapiro–Wilk normality test, Pearson Product Moment correlation, simple linear regression, the coefficient of determination, and SPSS version 25. Results: The findings revealed a positive and statistically significant relationship between the implementation of the Deep Learning model and children's moral value instillation (p < 0.05), indicating that more effective implementation of the model was associated with better moral development. Novelty: This study provides empirical evidence regarding the application of the Deep Learning model within an authentic early childhood education setting to strengthen children's moral values. Conclusion: Integrating meaningful, mindful, and joyful learning into classroom practice can support the development of children's moral values and promote more holistic early childhood education.