Transformasi Pembelajaran Jarak Jauh di Era Generative AI: Systematic Literature Review
Abstract
Perkembangan Artificial Intelligence (AI) telah membawa perubahan signifikan dalam sistem pembelajaran jarak jauh di perguruan tinggi, khususnya pascapandemi COVID-19 yang mempercepat transformasi digital pendidikan. Penelitian ini bertujuan untuk menganalisis tren penggunaan AI dalam pembelajaran jarak jauh, mengidentifikasi tantangan implementasinya, serta mendeskripsikan peluang pemanfaatannya bagi dosen di perguruan tinggi. Penelitian menggunakan metode Systematic Literature Review (SLR) dengan pendekatan PRISMA yang meliputi tahapan identifikasi, screening, eligibility, dan included studies. Sumber data diperoleh dari berbagai database ilmiah seperti Scopus, Google Scholar, ERIC, ScienceDirect, dan SpringerLink dengan rentang publikasi tahun 2020–2026. Berdasarkan proses seleksi, diperoleh 20 artikel ilmiah yang relevan dan dianalisis menggunakan teknik thematic analysis. Hasil penelitian menunjukkan bahwa tren penggunaan AI dalam pembelajaran jarak jauh didominasi oleh pemanfaatan generative AI, adaptive learning, learning analytics, chatbot, dan automated assessment. AI terbukti mampu meningkatkan efisiensi pembelajaran, personalisasi pengalaman belajar mahasiswa, serta mendukung pengelolaan pembelajaran berbasis data. Namun demikian, implementasi AI juga menghadapi berbagai tantangan seperti masalah etika akademik, plagiarisme, rendahnya literasi AI dosen, keterbatasan infrastruktur teknologi, serta isu privasi dan keamanan data. Di sisi lain, AI memberikan peluang besar bagi dosen untuk mengembangkan model pembelajaran inovatif berbasis human-AI collaboration. Penelitian ini menyimpulkan bahwa pemanfaatan AI dalam pembelajaran jarak jauh perlu didukung oleh kebijakan institusi, penguatan kompetensi digital dosen, dan regulasi etika penggunaan AI agar implementasinya dapat berjalan secara efektif, humanis, dan berkelanjutan dalam pendidikan tinggi.
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