Implementation Of Deep Learning Models To The Cognitive Development Of Early Childhood - Rita Fay; Ester Klakik; Genoveva Beto; Selvina Kristina Baitanu; Yona M. Masu; Fredericksen Victoranto Amseke (FKIP UNSULTRA, 2026)
Cognitive development is an important aspect influenced by the application of learning models in early childhood. The aim of this research is to determine the effect of the application of the deep learning model on the cognitive development of children aged 4–5 years at PAUD Weldy Kuanheum. The method used in this research is quantitative with an ex-post facto research design. The sampling technique used total sampling, comprising all 10 children aged 4–5 years at PAUD Weldy Kuanheum. Data were collected using questionnaires with instruments in the form of a deep learning model scale and a cognitive development scale. The data analysis technique used was simple linear regression with the SPSS 25.0 program. The results found that the deep learning model had a positive and significant effect on the cognitive development of children aged 4–5 years, with an R Square value of 0.213, or 21.3%, while the remaining 78.7% was influenced by other factors. The value of p = 0.001 (p < 0.05) indicates that the hypothesis is accepted. This shows that the consistent and structured application of the deep learning model can have a meaningful impact on the cognitive development of early childhood. It is expected that teachers can implement a deep learning model based on the principles of Mindful, Meaningful, and Joyful learning, in order to create child-centered learning, so that children feel active, comfortable, enthusiastic, and motivated in developing their cognitive abilities and critical thinking skills from an early age.