Validation of an Innovative Learning Model: Deep Learning Based on Eco-STEAM and Edutainment for Elementary School Science Education - Melva Zainil; Ary Kiswanto Kenedi; Nurfarhanah; Syafri Ahmad; Asna Mardin (Postgraduate, University of Mataram, 2025)
Science education at the elementary school level requires an approach that can improve conceptual understanding and higher-order thinking skills, such as computational thinking. A Deep Learning-based learning model integrated with Eco-STEAM and Edutainment has the potential to facilitate more in-depth, contextual, and engaging science learning. This study aims to test the validity of this learning model for application in elementary schools. The approach used is research and development (R&D) with validation techniques by three education experts through the first stage for initial assessment and the second stage after revisions based on expert input. The results show that the developed learning model obtained an average score of 148.4 out of 175 in the first stage (valid category) and increased to 160.9 in the second stage (highly valid category) after improvements were made to several model components. The discussion shows that this model effectively integrates deep learning with the Eco-STEAM approach and edutainment media, which supports students' understanding of science concepts while developing their CT skills and ecological awareness. This study implies that this model can be implemented in science learning in elementary schools, considering further revisions involving field implementation and adjustments to local characteristics and school infrastructure.