Development of Ethno-Algebra-Based Deep Learning to Enhance Conceptual Understanding Among Elementary School Students
Keywords:
Deep Learning, Geogebra, Ethnomathematics, Conceptual Understanding, GeogebraAbstract
This study aims to synthesize and develop a conceptual framework for Deep Learning-based Ethnogebra to enhance elementary students’ conceptual understanding in mathematics. Ethnogebra integrates Deep Learning (DL), GeoGebra (dynamic mathematics software), and ethnomathematics into a unified instructional approach. A systematic literature review design was employed to analyze 30 peer-reviewed articles published between 2015 and 2025 focusing on deep learning, technology integration, cultural context in mathematics, and conceptual understanding. The findings indicate that DL strengthens reflective and connected thinking, GeoGebra supports dynamic visualization of abstract concepts, and ethnomathematics enhances contextual relevance and learning meaning. The integration of these components forms a reflective, visual, and contextual learning model that potentially improves students’ conceptual understanding more comprehensively than partial approaches. This framework contributes theoretically to technology- and culture-integrated mathematics instruction and provides practical guidance for developing innovative learning models in elementary education.
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