Contextualizing Deep Learning in Arabic Language Education: Insights from Fullan’s Framework and Indonesia’s DIKDASMEN (Basic and Secondary Education) Policy

Rahmat Satria Dinata, Ifkar Rasyid, Ilya Husna, Ahmad Nur Mizan, Aifanisa Rahman, Putri Amelia

Abstract


This article examines the integration of four key components of Deep Learning as outlined by Indonesia’s Directorate General of Primary and Secondary Education (DIKDASMEN)—namely graduate profile dimensions, learning principles, learning experiences, and learning framework—with Michael Fullan’s Deep Learning Framework, in the context of Arabic language education in madrasahs and schools. Using a qualitative approach through critical literature review of policy documents and contemporary learning theories, the study finds that both frameworks align in promoting reflective, contextual, and transformative learning. The spiritual and character dimensions in the graduate profile can be contextualized through the principles of mindful, meaningful, and joyful learning, and further strengthened by the development of global competencies such as communication, collaboration, and creativity. Learning experiences and instructional designs based on projects, technology, and partnerships support a more dynamic and functional approach to Arabic language learning. The novelty of this study lies in the integration of local values and global competencies into an adaptive Arabic language curriculum responsive to the challenges of the modern era. It is recommended that Arabic language education be redesigned with a project-based, reflective, and cross-contextual approach to foster meaningful language skills and strong character development.

Keywords: Deep learning, Arabic language education, madrasah, Michael Fullan, Indonesian education policy


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References


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DOI: https://doi.org/10.15548/imlah.v7i1.12364

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