Integration of Artificial Intelligence in Learning Design: A Systematic Literature Review
Keywords:
ADDIE, Artificial Intelligence, Learning Analytics, Learning Design, PRISMAAbstract
The development of Artificial Intelligence (AI) technology has driven transformation in the learning design process, particularly in the context of 21st-century education, which demands personalization, efficiency, and adaptability. The shift from teacher-centered to student-centered learning further increases the need for responsive and data-driven instructional design. Although the concept of ADDIE-based learning design has been widely discussed, existing studies tend to examine AI applications in isolated stages. However, a comprehensive mapping of AI roles across all ADDIE phases remains underexplored. Therefore, this study aims to analyze the trends, roles, and impacts of AI integration in learning design based on the ADDIE model. This research employs a systematic literature review using the PRISMA approach, drawing from databases such as Scopus, Web of Science, and Google Scholar, covering publications from 2019 to 2024. A total of 27 selected articles were thematically analyzed and narratively synthesized. The findings reveal that AI contributes significantly across all ADDIE phases: from data-driven needs analysis, adaptive learning design, automated content development, the implementation of virtual tutors and chatbots, to predictive evaluation and real-time feedback. AI integration is shown to enhance student engagement, instructional effectiveness, and the quality of pedagogical decision-making. This study highlights the importance of AI literacy among educators and learning designers, as well as the need for supportive policies to ensure sustainable AI implementation in education.
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Copyright (c) 2026 Gusmadila Rahma, Zelhendri Zen, Endrawati Endrawati, Panji Hidayat, Wahyu Zamratul Rizki, Fatma Mutmainah
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