A systematic and bibliometric review of artificial intelligence in sustainable education: Current trends and future research directions

• A comprehensive review of 600 papers reveals AI's impact on diverse educational settings. • The study uncovers key trends in AI, emphasizing personalized and sustainable learning. • In-depth analysis identifies gaps in AI research, suggesting future directions. • AI's ethical implications in education are critically examined for fair and secure use. • Bibliometric review offers a global perspective on AI's growing role in education. This study aims to comprehensively analyze the use of Artificial Intelligence in Education (AIED), encompassing its applications, challenges, gaps in research, and future research directions. The research involves examining a wide range of studies published over the last five years and categorizing the literature into nine distinct categories, which are connections to existing educational theories, AI in Early and K-12 education, AI and ethics in education, AI techniques and applications, Artificial Intelligence (AI) and sustainable education, AI in higher education, AI in language and English as a Foreign Language (EFL) education, AI and Large Language Models (LLM), and AI in specific educational fields. The findings reveal significant trends, including the increasing integration of AI in personalized learning, ethical concerns, and the necessity for AI literacy among educators and students. The study also underscores gaps in current research, particularly in the areas of ethical implications and the scalability of AI solutions. The results suggest that while AI has the potential to enhance educational practices, further research is crucial to address the challenges and ensure the ethical and equitable implementation of AIED.