Digital education has gained popularity in the last decade, especially after
the COVID-19 pandemic. With the improving capabilities of large language models
to reason and communicate with users, envisioning intelligent tutoring systems
(ITSs) that can facilitate self-learning is not very far-fetched. One integral
component to fulfill this vision is the ability to give accurate and effective
feedback via hints to scaffold the learning process. In this survey article, we
present a comprehensive review of prior research on hint generation, aiming to
bridge the gap between research in education and cognitive science, and
research in AI and Natural Language Processing. Informed by our findings, we
propose a formal definition of the hint generation task, and discuss the
roadmap of building an effective hint generation system aligned with the formal
definition, including open challenges, future directions and ethical
considerations.

数字教育在近十年来变得越来越流行，尤其是在 COVID-19 大流行之后。本文综述了以往关于提示生成的研究，旨在填补教育和认知科学以及人工智能和自然语言处理研究之间的鸿沟，提出了提示生成任务的形式化定义，并讨论与该定义相一致的有效提示生成系统的构建路线图，包括挑战、未来方向和伦理考虑。