<![CDATA[Early childhood education plays a fundamental role in optimizing children's development during the golden age through holistic and integrated learning experiences. One of the current learning approaches that emphasizes meaningful, mindful, and joyful learning is the deep learning model. However, empirical evidence regarding its contribution to the development of responsibility character in early childhood remains limited. Therefore, this study aimed to examine the effect of the deep learning model on the development of responsibility character among children aged 5–6 years at PAUD Diaspora Danau Ina, Kupang City. This study employed a quantitative approach with an ex-post facto design. The respondents consisted of 26 children selected using purposive sampling. Data were collected using questionnaires measuring the implementation of the deep learning model and the development of responsibility character. The data were analyzed using descriptive statistics and simple linear regression with SPSS version 25.0. The results revealed that the implementation of the deep learning model was predominantly in the high category (46%), followed by the moderate (35%) and low (19%) categories. Likewise, the development of responsibility character was mostly in the high category (51%), followed by the moderate (25%) and low (24%) categories. The regression analysis demonstrated that the deep learning model had a positive and significant effect on the development of responsibility character (R = 0.444; R² = 0.197; F = 5.906; p = 0.023), indicating that the model contributed 19.7% to the formation of responsibility character, while the remaining 80.3% was influenced by other factors. These findings suggest that the deep learning model can serve as an effective learning approach to strengthen responsibility character in early childhood through active, meaningful, and enjoyable learning experiences, thereby contributing to character education practices in early childhood education institutions.]]>
