Damaryana Nurhani
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Deep Learning dalam Kurikulum Bahasa Mandarin: Peluang & Tantangan Berdasarkan Teori Pendidikan Amira Khoirunnisa; Damaryana Nurhani; Hanifah Ummu Ammaroh; Sarah Febri Cantikaarini; Zanira Nazmi Sihombing; Augia Pramesthi
Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan  Vol. 3 No. 3 (2025): Juli: Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pragmatik.v3i3.1845

Abstract

Mandarin has emerged as a strategically vital global language after English, thus making it essential in the world of education. In this context, the deep learning approach is considered relevant to encourage deep understanding and applicative language skills. This study examines deep learning-based Mandarin language development, focusing on its opportunities and challenges based on relevant 21st century learning theories. Using a qualitative descriptive method through library research, data was collected from various academic sources including books, journal articles, and magazines relevant to the topic. The results show that deep learning can transform the learning process to be more applicative, in line with constructivist theory that emphasizes active and deep learning. Although challenges such as rigid curricula exist, this approach offers opportunities to enhance student engagement and comprehensive language skills. Deep learning has potential to strengthen contextual Mandarin learning, though its success depends on curriculum readiness and technological support.