Integrasi Problem-Based Learning dan Deep Learning dalam Pembelajaran Fisika : Sintesis Naratif terhadap Temuan Penelitian

Abstrak

Physics learning requires strategies that move students beyond memorization toward conceptual understanding, problem solving, reflection, and the application of knowledge to real situations. Problem-Based Learning (PBL) places authentic problems at the center of learning, while the deep learning approach emphasizes conscious, meaningful, and joyful learning. This article presents a narrative synthesis of recent studies that explicitly integrate PBL with a deep learning approach in physics education or relevant science contexts. The studies were purposively selected based on their thematic relevance, publication period, availability of research methods and findings, and explicit integration of PBL and deep learning. Data were extracted according to the research objectives, educational level, research design, learning context, learning outcomes, and main findings. The synthesis indicates a positive pattern in which the integration of PBL and deep learning can support learning outcomes, problem-solving abilities, critical and creative thinking, scientific reasoning, science process skills, computational thinking, literacy, learning engagement, and classroom interaction. The integration can also be strengthened through simulations, STEM-EDP, local wisdom contexts, and learning resources designed to encourage reflection and meaningful learning. The findings suggest that successful integration depends not only on the instructional model but also on the characteristics of the learning material, the context of the problem, the design of learning activities, and the quality of classroom interaction. Therefore, integrating PBL and deep learning has strong potential to support physics learning that is more active, meaningful, reflective, and oriented toward problem solving