Exploring the Utilization of Deep Learning in Early Childhood Art Education: A Study of PAUD Teachers in Pandeglang Regency

This research explores the potential and challenges of implementing deep learning in early childhood art education, focusing on the experiences and perspectives of PAUD (Early Childhood Education) teachers in Pandeglang Regency. The study aims to understand how deep learning can enhance art education by personalizing learning experiences to meet individual children's needs. A qualitative approach was employed, using in-depth interviews, classroom observations, and document analysis to gather data from selected PAUD teachers. The findings reveal that while teachers show enthusiasm for technological innovations, their understanding of deep learning is limited, and the application of such technology in teaching practices remains minimal. Major challenges include insufficient infrastructure, lack of teacher training, and concerns about reduced direct interaction in the classroom. Despite these barriers, the study indicates that deep learning has significant potential to create dynamic, personalized, and engaging art education experiences. Recommendations for improving the integration of technology in PAUD education include providing comprehensive teacher training, enhancing technological infrastructure, and fostering collaborations between government, educational institutions, and technology providers to ensure sustainable and effective educational transformation.