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Jurnal Pendidikan Progresif
Published by Universitas Lampung
ISSN : 20879849     EISSN : 25501313     DOI : https://doi.org/10.23960/jpp
Core Subject : Education,
Education
urnal Pendidikan Progresif is an academic journal that published all the studies in the areas of education, learning, teaching, curriculum development, learning environments, teacher education, educational technology, educational developments from various types of research such as surveys, research & development, experimental research, classroom action research, etc. Jurnal Pendidikan Progresif covers all the educational research at the level of primary, secondary, and higher education. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Educational advancements and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Education. Topics of Interest include, but are not limited to, the following Disaster literacy and Risk Management Education Ethnopedagogy-based STEM Education Integrating technology into the curriculum: Challenges & Strategies Collaborative & Interactive Learning Tools for 21st Century learning Learning Analysis Education Management Systems Education Policy and Leadership Business Education Virtual and remote laboratories Pedagogy Enhancement with E-Learning Course Management Systems Teacher Evaluation Curriculum, Research, and Development Web-based tools for education Games and simulations in Education Learning / Teaching Methodologies and Assessment Counselor Education Student Selection Criteria in Interdisciplinary Studies Global Issues in Education and Research Technology Support for Pervasive Learning Artificial Intelligence, Robotics and Human-computer Interaction in Education Mobile/ubiquitous computing in education Web 2.0, Social Networking, Blogs and Wikis Multimedia in Education Educating the educators Professional Development for teachers in ICT
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 1 Documents
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Search results for "Deep Learning Applications in Primary Education" : 1 Documents clear
Deep Learning Applications in Primary Education: A Systematic Literature Review of Emerging Trends, Challenges, and Opportunities Adi Saputra, Ricki Fahma; Ridha, Muhammad; Sulaimon, Jamiu Temitope
Jurnal Pendidikan Progresif Vol 15, No 3 (2025): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v15i3.pp1785-1810

Abstract

Deep Learning Applications in Primary Education: A Systematic Literature Review of Emerging Trends, Challenges, and Opportunities. Objectives: Despite significant advances in healthcare and finance, Deep Learning (DL) remains underutilized in primary education, with only about 12% of AI-related studies focusing on K–6. Given the formative role of early schooling in cognitive and social development, this systematic review analyzed recent empirical studies to identify key trends, challenges, and opportunities in applying DL to primary education. Methods: Following the PRISMA 2020 guidelines, 21 studies published between 2021 and 2025 across 11 countries were analyzed using a structured coding sheet and further examined with bibliometric mapping, Microsoft Excel, and Python-based visualization tools. The review included diverse sources focusing on DL use cases across global primary education systems. Findings: The findings reveal a global increase in DL adoption, led by China and South Korea, with growing contributions from Indonesia, India, and the Philippines. Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), and transformer-based models are among the most commonly applied architectures to tasks such as personalized learning, early detection of learning difficulties, assessment automation, and curriculum development. However, there are still problems in the context of ethical concerns, including data privacy, algorithmic bias, and equity of access. Technical barriers involve dataset complexity, model generalization, and resource limitations, while pedagogical issues center on aligning DL applications with developmental needs and classroom realities. Despite these obstacles, DL demonstrates significant potential to enhance personalization, foster engagement, and support holistic educational outcomes. Conclusion: This review contributes a strategic roadmap for integrating DL in primary education by balancing innovation with pedagogy and ethics. Future research should prioritize cross-disciplinary collaboration, greater geographic diversity, and improvements in scalability and interpretability to ensure DL supports equitable, future-ready learning. Keywords: deep learning, primary education, personalized learning, systematic literature review, educational technology.

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