Dampak Implementasi Deep Learning dalam Kurikulum Nasional terhadap Kualitas Pembelajaran di Indonesia

Abstract

The rapid advancement of digital transformation in the 21st century has encouraged the integration of artificial intelligence, particularly deep learning, into national education systems. This article examines the impact of implementing deep learning—both as an artificial intelligence–based technology and as a deep learning pedagogical approach—within the Indonesian national curriculum on the quality of learning. Using a qualitative approach based on systematic literature analysis of Scopus-indexed international publications and national education policy review, this study synthesizes global empirical findings and contextualizes them within Indonesia’s educational framework. The analysis indicates that the integration of deep learning technologies enhances personalized learning, adaptive assessment systems, predictive academic analytics, and data-driven instructional decision-making. Simultaneously, deep learning pedagogy strengthens higher-order thinking skills, critical reasoning, collaboration, and meaningful knowledge transfer. However, implementation challenges include digital infrastructure disparities, teacher digital competence gaps, algorithmic bias, ethical concerns, and data privacy issues. This article proposes an integrative conceptual framework combining technological, pedagogical, and policy dimensions to support sustainable curriculum transformation. The study contributes theoretically by bridging artificial intelligence–driven deep learning and pedagogical deep learning within a unified curriculum model tailored to developing-country contexts, particularly Indonesia.