Development of a Practical Urban Parenting Module Using Deep Learning Approach - Gustri Wahyuni; Herlina; Rusmayadi; Syamsuardi; Salma Samputri (Smart Edu Center, 2026)
This study aims to develop a Deep Learning-based collaborative parenting module to support the socio-emotional development of children aged 4–7 years in urban early childhood education. The research employed a Research and Development design using the 4-D model, consisting of Define, Design, Develop, and Disseminate stages. The study involved 20 parents, 4 teachers, and 20 children in an urban kindergarten setting. Data were collected through questionnaires, interviews, observations, expert validation sheets, and pretest–posttest assessments. The results show that the developed module is highly valid with a Total Average Validation Score of 3.59. The practicality test indicated very high acceptance from parents with a mean score of 4.91 and positive responses from teachers regarding usability and collaboration support. The effectiveness analysis using the Wilcoxon Signed Ranks Test revealed a statistically significant improvement in children’s socio-emotional development (Z = -4.002, p < 0.001), with all participants showing positive improvement from pretest to posttest. In conclusion, the Deep Learning-based collaborative parenting module is feasible, practical, and shows promising potential effectiveness in enhancing parent–teacher collaboration and supporting children’s socio-emotional development in urban early childhood education contexts.