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p-Index From 2021 - 2026
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All Journal Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Qomah, Ashri Nafiah Nur Isti
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Computer Science & IT Engineering Medicine & Pharmacology Social Sciences Other

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Deep Learning in Education: A Systematic Literature Review on Its Applications and Challenges Qomah, Ashri Nafiah Nur Isti; Wachidi, W; Maksum, Muh. Nur Rochim; Rifai, Alfan; Anggraini, Fadhilla Nangroe
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2025: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

This research aims to provide a systematic review of the application of deep learning technology in education and the challenges faced in its implementation. With the increasing adoption of artificial intelligence (AI) technology in education, especially in personalized learning, this research is important to understand the potential and barriers that affect the successful implementation of this technology. The main objective of this study is to identify the application of deep learning in education, evaluate the challenges faced, and assess its impact on the quality of learning in the formal and non-formal sectors.The method used is a systematic literature review by following the PRISMA 2020 guidelines. Relevant articles were selected from various academic databases published between 2020 and 2026. After screening, 13 articles that met the inclusion criteria were analyzed using narrative synthesis and thematic analysis approaches. The results show that deep learning can improve learning personalization, provide faster feedback, and increase student engagement. However, the main challenges faced are the limitations of technology infrastructure, unrepresentative data quality, and the difficulty of educators in integrating this technology. Issues related to data privacy and technology access gaps are also significant obstacles. This study recommends the need for policies that support more equitable access to technology, educator training, and increased transparency in the use of deep learning models.
Co-Authors Anggraini, Fadhilla Nangroe Muh Nur Rochim Maksum Rifai, Alfan Wachidi, W