Generative AI in Education: Opportunities, Challenges, and Future Perspectives

Abstract: Generative Artificial Intelligence (GenAI) is rapidly transforming education by enabling systems to generate text, images, code, feedback, and other learning resources. Large language models have created opportunities for personalized learning, intelligent tutoring, automated feedback, content development, and accessibility. At the same time, GenAI introduces concerns regarding academic integrity, misinformation, bias, privacy, copyright, unequal access, and excessive learner dependence. This paper reviews recent research studies and synthesizes major findings on the educational potential and limitations of GenAI. A comparative literature survey of ten influential studies identifies recurring themes, including personalization, teacher support, assessment redesign, AI literacy, and ethical governance. The review reveals a research gap in long-term empirical evidence, particularly in diverse educational settings and in measuring actual learning outcomes. The paper argues that GenAI should be implemented as a human-centered educational assistant rather than a replacement for teachers. Future directions include multimodal adaptive learning, AI literacy, transparent assessment practices, inclusive access, privacy-preserving systems, and stronger institutional policies.

Keywords: Generative AI, Artificial Intelligence in Education, ChatGPT, Personalized Learning, AI Literacy, Educational Technology, Academic Integrity