Leveraging STEAM Learning and SOLO Taxonomy to Cultivate Deep Mathematical Understanding: A Conceptual Framework for Deep Learning in Primary Education
Keywords:
STEAM Learning, SOLO Taxonomy, Deep Mathematical Understanding, Deep Learning, Primary EducationAbstract
Mathematics proficiency among Indonesian primary school students remains below expectations, as reflected in the 2018 PISA results showing scores significantly below the OECD average. This study proposes a conceptual framework that integrates STEAM (Science, Technology, Engineering, Arts, and Mathematics) learning with the SOLO (Structure of Observed Learning Outcomes) Taxonomy to foster deeper mathematical understanding. Using a qualitative literature review approach, this research analyzes how both frameworks contribute to enhancing students’ conceptual, procedural, and metacognitive skills. STEAM promotes interdisciplinary, project-based learning rooted in real-world contexts, while the SOLO Taxonomy provides a structured progression of cognitive complexity from surface learning to extended abstraction. Findings suggest that the integration of these approaches enhances meaningful engagement, supports creativity, and improves students’ problem-solving abilities. This framework offers both theoretical and practical guidance for teachers in designing adaptive, transformative mathematics instruction aligned with 21st-century learning demands.
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