Implementasi Pendekatan Pembelajaran Deep Learning pada Mata Pelajaran IPA dalam Kurikulum Merdeka

Penulis

  • Ammy Fidyanti Universitas Negeri Jakarta
  • Rugaiyah Universitas Negeri Jakarta
  • Masduki Universitas Negeri Jakarta

DOI:

https://doi.org/10.47467/reslaj.v7i10.8989

Abstrak

This study examines the implementation of the deep learning approach in science subjects in the context of the Independent Curriculum in Indonesia. The background of the study shows that the Indonesian education system faces challenges in improving the quality of meaningful learning and developing 21st century skills. The purpose of the study is to analyze the concepts, principles, and strategies for implementing deep learning in science learning and evaluate their suitability with the Independent Curriculum. The method used is a systematic literature study of scientific literature from reputable international journals for the period 2020-2025. The results of the study show that deep learning in education emphasizes in-depth conceptual understanding, active student involvement, and the development of high-level thinking skills. The implementation of deep learning is in line with the principles of the Independent Curriculum which emphasize meaningful learning, differentiation, and the development of Pancasila student profiles. The conclusion of the study shows that the integration of the deep learning approach can improve the effectiveness of science learning in the Independent Curriculum through problem-based learning strategies, collaborative projects, and the use of adaptive learning technology. The implications of this study are important for the development of education policies and science learning practices in Indonesia.

Unduhan

Data unduhan belum tersedia.

Diterbitkan

2025-10-03

Cara Mengutip

Ammy Fidyanti, Rugaiyah, & Masduki. (2025). Implementasi Pendekatan Pembelajaran Deep Learning pada Mata Pelajaran IPA dalam Kurikulum Merdeka. Reslaj: Religion Education Social Laa Roiba Journal, 7(10), 2828 –. https://doi.org/10.47467/reslaj.v7i10.8989

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