The Applikation Of Deep Learning Using Loose Part To Enhance Early Childhood Creativity Development

Abstract

Background: Creativity is a fundamental aspect of early childhood development because it supports children's ability to generate original ideas, solve problems, and express themselves through meaningful learning experiences. The Deep Learning approach integrated with Loose Parts media has been introduced as an innovative child-centered learning strategy that promotes mindful, meaningful, and joyful learning. However, empirical evidence regarding its implementation in authentic early childhood classrooms remains limited. Objective: This study aimed to analyze the effect of the Deep Learning approach integrated with Loose Parts media on the creativity development of children aged 4–5 years at PAUD Joel, Kupang City. Method: This quantitative study employed an ex post facto research design involving 20 children selected through total sampling. Data were collected using observation, documentation, and creativity assessment instruments and analyzed using descriptive statistics and simple linear regression. Results: The findings revealed that the implementation of the Deep Learning approach with Loose Parts media had a positive and statistically significant effect on children's creativity development (p < 0.05). The coefficient of determination (R² = 0.131) indicated that the approach explained 13.1% of the variance in creativity development, while the remaining variance was influenced by other factors. Novelty: This study provides empirical evidence of integrating the Deep Learning approach with Loose Parts media through an ex post facto design in an authentic early childhood education setting. Conclusion: The Deep Learning approach with Loose Parts media can positively support children's creativity development by providing meaningful, exploratory, and child-centered learning experiences.