Transformasi Pembelajaran Matematika SD Melalui Deep Learning: Strategi untuk Meningkatkan Motivasi dan Prestasi

This study aims to systematically examine various mathematics learning strategies based on deep learning approaches that can enhance elementary school students’ motivation and academic achievement. In the context of education, deep learning refers to learning processes that emphasize conceptual understanding, interrelated knowledge, and the development of critical and reflective thinking skills. Using the Systematic Literature Review (SLR) method, this research analyzes 20 relevant scholarly articles published between 2015 and 2024, sourced from leading databases such as Google Scholar. The review findings indicate that strategies such as problem-based learning (PBL), project-based learning (PJBL), metacognitive strategies, and the use of interactive learning technologies consistently improve student engagement, foster intrinsic motivation, and enhance mathematics learning outcomes. These findings suggest that integrating deep learning-based instructional strategies is highly relevant for elementary mathematics education, aiming to create more meaningful, student-centered learning experiences.