The development of Generative Artificial Intelligence (Generative AI) presents both new opportunities and challenges in the field of education. This technology has the potential to transform learning practices, assessment, and knowledge management. However, its adoption process is not linear and is influenced by pedagogical, social, ethical, and institutional factors. This study aims to analyze the adoption of Generative AI in education using the Diffusion of Innovation Theory framework. The research method employed is a Systematic Literature Review (SLR) of 27 reputable national and international journal articles published between 2022 and 2024. The literature selection process followed the PRISMA guidelines, consisting of identification, screening, eligibility, and inclusion stages. The findings indicate that Generative AI offers relative advantages in supporting personalized learning, improving learning efficiency, and expanding access to learning resources. However, complexity of use, compatibility issues with academic integrity values, and concerns regarding ethics and data privacy are major barriers to adoption. The successful utilization of Generative AI in education requires innovation diffusion strategies supported by institutional policies, enhancement of digital literacy, and reinforcement of educational and cultural values.
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