Transformasi Pembelajaran Bahasa Indonesia di Sekolah Dasar melalui Pendekatan Deep Learning - Asrin Asrin Nasution; Arafatul Soraya; Syafri Martabe Rizka Nasution; Nur Hakimah (Fakultas Ilmu Tarbiyah dan Keguruan UIN Sumatera Utara, 2025)
This article explores the transformation of Indonesian language learning in elementary schools through the application of deep learning approaches. The study employs a Systematic Literature Review (SLR) of relevant articles indexed in Scopus, Web of Science, and national accredited publications between 2015 and 2025. Findings indicate that deep learning technologies, particularly Natural Language Processing (NLP), speech recognition, intelligent tutoring systems, and automated essay scoring, have significant potential to enhance students’ reading, writing, and speaking skills. These technologies provide adaptive learning, instant feedback, and personalized material recommendations. Nonetheless, implementation challenges remain, including limited infrastructure, teachers’ digital competence, and ethical concerns regarding data use. The study concludes that integrating deep learning can serve as an effective strategy to improve elementary students’ literacy, provided that teacher readiness, digital infrastructure, and supportive educational policies are ensured.