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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.
Enhancing Science Learning through the Development of Animation Video Media Based on Bruner's Cognitive Theory Using Canva for Students Eliza Novita; Abna Hidayati; Darmansyah Darmansyah; Ridwan Ridwan
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13270

Abstract

This study aims to develop animated video learning media based on Bruner’s cognitive theory to enhance the science learning process of third-grade students at SDN 18 Koto Tinggi, focusing on the topics of energy sources and energy transformations. Animated videos are used to present abstract concepts through clear visual representations, enabling learning activities that are more engaging and interactive for students. The study applied a research and development approach using the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation, to ensure that the developed media is valid, practical, and effective. The validity of the media was examined through expert validation involving media experts, content experts, and language experts, and the results indicated that the media was highly feasible and appropriate for achieving the intended learning objectives. Effectiveness testing was conducted using pre-test and post-test instruments, which showed a significant improvement in students’ learning outcomes with an N-Gain score of 0.71. In addition, student and teacher responses demonstrated that the animated video media was very practical, easy to use, attractive, and effective when implemented in classroom learning. Overall, this study contributes to literature on technology-based learning media in Indonesia and supports animated videos for elementary science