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Relevance and Impact of Generative AI in Vocational Instructional Material Design: A Systematic Literature Review

Relevance and Impact of Generative AI in Vocational Instructional Material Design: A Systematic Literature Review

Fadhli Ranuharja, Ganefri , Fahmi Rizal, D. Langeveldt, Rachid Ejjami, Á. Torres-Toukoumidis, N. Jalinus, Dr. William Castillo-González

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2025-01-01
JournalArticleReview

Abstract

This study examines the relevance and impact of Generative Artificial Intelligence (GenAI) in the design of instructional materials for vocational education through a systematic literature review following the PRISMA guidelines. The review draws from reputable databases, including Scopus, Web of Science (WoS), and ERIC, to identify peer-reviewed articles published between 2019 and 2024. After applying inclusion and exclusion criteria, 28 eligible articles were analyzed. The findings highlight that GenAI significantly enhances instructional material design by supporting personalized learning, automating content creation, and improving accessibility. It enables the development of adaptive and high-quality resources tailored to diverse learner needs in vocational education. Furthermore, the study visualizes research trends using bibliometric analysis, providing insights into the evolution and distribution of GenAI-related research across time, regions, and themes. However, challenges such as the need for digital competency development among educators, ethical concerns regarding bias and content quality, and the potential over-reliance on AI tools are identified. This study underscores the importance of balancing AI-driven innovation with human-centered instructional design to ensure effective and sustainable educational practices. Practical recommendations include targeted professional development programs and ethical frameworks to guide the integration of GenAI into vocational education