We discuss the implications of generative AI on education across four critical sections: the historical development of AI in education, its contemporary applications in learning, societal repercussions, and strategic recommendations for researchers. We propose ways in which generative AI can transform the educational landscape, primarily via its ability to conduct assessment of complex cognitive performances and create personalized content. We also address the challenges of effective educational tool deployment, data bias, design transparency, and accurate output verification. Acknowledging the societal impact, we emphasize the need for updating curricula, redefining communicative trust, and adjusting to transformed social norms. We end by outlining the ways in which educational stakeholders can actively engage with generative AI, develop fluency with its capacities and limitations, and apply these insights to steer educational practices in a rapidly advancing digital landscape.

翻译：本文从四个关键部分探讨了生成式人工智能对教育的影响：人工智能在教育领域的历史发展、其在学习中的当代应用、社会影响以及对研究者的战略建议。我们提出了生成式人工智能能够通过评估复杂认知表现和创建个性化内容来改变教育格局的方式。同时讨论了有效教育工具部署、数据偏差、设计透明度和准确输出验证等挑战。在承认社会影响的基础上，我们强调需要更新课程体系、重新定义沟通信任以及适应转变的社会规范。最后，我们概述了教育利益相关者如何积极参与生成式人工智能、培养对其能力与局限性的理解，并将这些见解应用于指导快速发展的数字环境中的教育实践。