The Integration of Deep Learning and Problem-Based Learning to Enhance Critical Thinking in Elementary Science Education
DOI:
10.29303/jppipa.v12i2.13673Published:
2026-02-25Downloads
Abstract
This study investigates the integration of a Deep Learning approach with the Problem-Based Learning (PBL) model to enhance critical thinking and conceptual understanding in Grade 6 science learning. A qualitative descriptive design was employed involving one teacher and 23 students at SDI Tirtayasa. Data were collected through classroom observations, semi-structured interviews, and document analysis, and analyzed using Miles and Huberman’s interactive model. The findings reveal that the integration of Deep Learning principles—namely, meaningful, mindful, and joyful learning—with structured PBL phases significantly increased students’ engagement, collaborative inquiry, and conceptual connection to real-life contexts, particularly in the topic of the human movement system. Students demonstrated improved questioning skills, argumentation, and reflective thinking. The teacher’s facilitative role was crucial in scaffolding deeper inquiry and metacognitive processes. Despite limitations in time allocation and laboratory facilities, adaptive strategies enabled effective implementation. This study contributes empirically by demonstrating how the synergy between Deep Learning and PBL can operationalize student-centered science learning in elementary settings. The findings support the sustainable implementation of integrative pedagogical models to promote higher-order thinking in primary science education.
Keywords:
Critical thinking Deep learning Elementary science Problem based learning Student engagementReferences
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