Penerapan Model Deep Learning Terhadap Perkembangan Kognitif Anak Usia Dini

Abstract

Cognitive development is one of the important aspects in early childhood education as it relates to the ability to think, understand, remember, categorize information, and solve problems. Efforts to optimize children's cognitive development require learning that is not only oriented toward mastery of subject matter, but also capable of providing meaningful learning experiences. One approach that can be used is deep learning instruction, which emphasizes the principles of mindful learning, meaningful learning, and joyful learning. This study aims to describe the implementation of deep learning instruction and analyze the cognitive development of children aged 5–6 years at PAUD Sabalus Vani Naimata. This study uses a quantitative approach with a quasi-experimental method using a One Group Pretest-Posttest Design. The research sample consisted of all children in the 5–6 age group, determined using a total sampling technique. Data were collected through tests (pre-test and post-test), observation, and documentation, then analyzed using descriptive statistics and the Paired Sample t-Test with the assistance of IBM SPSS Statistics. The results showed that deep learning instruction had been implemented through activities that encourage active child engagement, connect material to real-life experiences, and create an enjoyable learning atmosphere. The implementation of this learning approach had a positive impact on children's cognitive development, as indicated by improvements in their ability to observe, categorize information, think logically, solve simple problems, and develop creativity.