<![CDATA[This study adopts a systematic review approach to explore the applications and implications of generative AI technology in education. Quantitative and qualitative methods were used to understand how generative AI has been utilized across various educational contexts, including science education, arts and design, and higher education. The systematic review emphasizes the use of generative AI to personalize learning experiences, create interactive content, and provide adaptive assessments that enhance student engagement and learning effectiveness. An analysis of 713 reviewed journals reveals that most studies focus on using AI in higher education and science education, highlighting the benefits and challenges of integrating this technology. The findings indicate that generative AI holds significant potential to advance personalized learning, facilitate the creation of rich and dynamic content, and offer more adaptive and responsive assessment tools tailored to individual learners’ needs. Nevertheless, this review also identifies several critical concerns associated with the application of generative AI in education, particularly regarding ethical issues, data privacy, and academic integrity. These challenges necessitate the development of clear and comprehensive policies and frameworks. This study underscores the importance of evidence-based approaches to evaluate the effectiveness of generative AI in educational settings. It advocates for more research to understand the social and moral impacts of generative AI applications and to ensure that integrity and privacy principles are not compromised.]]>
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