Application Of The Deep Learning Model On The Cultivation Of Tolerance Values In Children Aged 3–6 Years

Abstract

Background: Tolerance is a fundamental character that should be cultivated during early childhood because it supports children's ability to respect diversity, cooperate with others, and build positive social relationships. Developing tolerance requires meaningful and child-centered learning experiences that actively engage children in the learning process. Objective: This study aimed to examine the effect of the deep learning model on the cultivation of tolerance values among children aged 3–6 years at PAUD Weldy Kuanhueum. Method: This quantitative study employed an ex-post facto research design involving 30 children selected through total sampling. Data were collected using structured questionnaires measuring the implementation of the deep learning model and children's tolerance values. The instruments were tested for validity and reliability prior to data collection. Data were analyzed using descriptive statistics and simple linear regression with SPSS version 25.0. Results: The findings revealed that the deep learning model had a positive and significant effect on children's tolerance values (p = 0.001 < 0.05). The coefficient of determination (R² = 0.361) indicated that the model explained 36.1% of the variance in tolerance values, while 63.9% was influenced by other factors beyond the scope of this study. Novelty: This study provides empirical evidence that integrating Mindful Learning, Meaningful Learning, and Joyful Learning effectively supports tolerance development in authentic early childhood education settings. Conclusion: The consistent implementation of the deep learning model can strengthen children's tolerance values and should be integrated into daily classroom activities through collaboration between teachers and parents.