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All Journal Produktif : Jurnal Ilmiah Pendidikan Teknologi Informasi Jurnal PGSD: Jurnal Ilmiah Pendidikan Guru Sekolah Dasar Indonesian Journal of Primary Education Jurnal Kesehatan Budi Luhur: Jurnal Ilmu-Ilmu Kesehatan Masyarakat, Keperawatan, dan Kebidanan Sehat Masada Bima Abdi: Jurnal Pengabdian Masyarakat ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Co-Value : Jurnal Ekonomi, Koperasi & Kewirausahaan Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Media Informasi International Transactions on Artificial Intelligence (ITALIC)
NURAENI, RANI
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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SWOT Analysis of AI-Based Learning Recommendation Systems for Student Engagement Nuraeni, Rani; Hardini, Marviola; Parker, Jonathan; Ilham, Muhammad Ghifari
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.894

Abstract

This study presents a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) of AI-based learning recommendation systems for students. These innovative systems hold significant potential in supporting Sustainable Development Goal (SDG) 4 Quality Education by personalizing learning pathways, enhancing access to resources, and boosting student engagement. Their primary strengths include increased learning efficiency, adaptive content delivery, and instant feedback mechanisms. Nevertheless, weaknesses such as potential algorithmic bias, data privacy concerns, and over reliance on technology warrant careful consideration. Emerging opportunities encompass expanding educational access for underserved populations, facilitating lifelong learning, and integrating diverse educational platforms. However, threats like the digital divide and the need for robust ethical guidelines must be addressed to ensure equitable access. This analysis underscores the necessity of a balanced approach in developing and deploying these AI systems, maximizing their educational benefits while mitigating risks to achieve more inclusive and equitable quality education for all. Quantitatively, the synthesis of reviewed studies reveals that adaptive AI-based recommendation systems improve student engagement by up to 18% and content relevancy by approximately 22% compared to conventional systems. Moreover, the SWOT analysis indicates that the strength to threat ratio (S/T) exceeds 2.1, implying that institutional readiness and technological innovation significantly outweigh identified implementation risks. These findings confirm the robust potential of AI-LRS in higher education.
Co-Authors Adini, Syaukia Agustina, ⁠⁠Friska Alwin, Cindi Anita, Tiurida Lily Ardian, Muhamad Azmi, Ridha Cecep Riki Djuaeriah, Ryka Ekasari, Revalina Fadillah, ⁠Tsabbit M Fadillatunnisa , Syifa Gandhi, Iswara Ginayah, Gina Hakim, Sofwan Mahmudil Halim, Cecep Abdul Hanifah, Hani Hasanah, Hana Nur Ilham, Muhammad Ghifari Indra Hastuti, Indra Iriani, Oktarina Sri Lesmana, Rosa Marviola Hardini Maulidia, Eka Putri Mudakir, Ubaedillah Natalia, Ester Ananda Nur, Lutfi Nurazizah, Eka Pahmi, Syifa Nurul Parker, Jonathan Putri, Dewi Andina Qurotul Aini Rahayu, Rina Nur Rizky Ridwan Rodriguez, Anthony Romansyah, Roni Rosyid, Dede Abdul Sianturi, Risbon Sihotang, Sondang Visiana Sima Mulyadi, Sima Siti Mutmainah Sofia Februanti, Sofia Sulidar Fitri Susanti, Dyeri Syarip Hidayat Triwidiyantari, Dyah Tua, Maruli Untung Rahardja Yulianti, Reva