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All Journal International Journal of Evaluation and Research in Education (IJERE) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Varidika Al Ishlah Jurnal Pendidikan Jurnal Basicedu International Journal of Educational Dynamics (IJEDS) EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Penelitian IPTEKS JTEIN: Jurnal Teknik Elektro Indonesia Marketing Management Studies Jurnal Basicedu
Ridwan Ridwan
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Bibliometric and Systematic Review of AI-Assisted Adaptive Learning Applications in Vocational Education (2018-2023) Harleni Harleni; M. Giatman; Nurhasan Syah; Ganefri Ganefri; Nizwardi Jalinus; Ridwan Ridwan; Krismadinata Krismadinata
AL-ISHLAH: Jurnal Pendidikan Vol 17, No 4 (2025): DECEMBER 2025
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v17i4.8019

Abstract

The integration of Artificial Intelligence (AI) into adaptive learning systems has gained traction in vocational education due to its potential to personalize instruction and enhance competency-based learning. However, research on this intersection remains fragmented, particularly in the context of vocational education and training (TVET). This study conducts a Systematic Literature Review (SLR) using the PRISMA protocol, combined with bibliometric analysis using VOSviewer, to map research trends on AI-assisted adaptive learning in vocational education from 2018 to 2023. Data were sourced from Scopus, Semantic Scholar, and Google Scholar, resulting in 41 eligible articles. The findings reveal a sharp increase in publications after 2020, reflecting growing interest in AI-driven innovations, particularly during the COVID-19 pandemic. Bibliometric mapping identified three dominant thematic clusters: AI-enabled personalization, competency-based vocational education, and pedagogical innovation. Geographically, most research originates from technologically advanced countries such as the United States, India, and the United Kingdom. The study highlights the strategic role of AI-assisted adaptive learning in supporting individualized pathways and skills alignment in vocational education. It also identifies gaps in longitudinal evaluation, pedagogical integration, and research representation from developing regions. These insights provide practical implications for policymakers, educators, and curriculum developers aiming to modernize vocational training systems through AI.
Co-Authors Abdullah, MT, Dr. Rijal Afzalur Syaref Andrian Andrian Ani Kariyati Ayu Mustika Sari Bulkia Rahim Dicky Nofriansyah Fetri Yeni J Ganefri . Gesit Thabrani Harleni, Harleni Hastuti Hastuti Indrati Kusumaningrum Krismadinata Krismadinata, Krismadinata Maisyarah Purnama Sari Nizwardi Jalinus Nurhasan Syah Putri Ani Syaflan Sandi Harta Putra Widiarti R Maya Yanto, Doni Tri Putra Yudha Aditya Fiandra