【作 者】：
卢国庆， 杨 沁， 贺相春
【关 键 词 】：
生成式人工智能； 智能反馈； 教育评价； 形成性评价； 技术赋能
【栏 目】：
课程与教学
【中文摘要】：
生成式人工智能已经具备与人类进行有意义多轮对话的重要能力。传统高等教育形成性评价在及时性、个性化等方面存在不足。如何利用生成式人工智能优化高等教育评价过程，已经成为教育界共同关注的话题。研究旨在通过生成式人工智能，提供智能反馈，优化形成性评价，提高评价的效率与个性化水平，进而促进学生有效学习的发生。研究利用文献法与归纳法，聚焦形成性评价，在探讨生成式人工智能赋能高等教育形成性评价的基础上，从形成性评价的理念、对象、过程、结果和伦理等方面，探讨生成式人工智能赋能形成性评价的挑战，并提出了生成式人工智能赋能形成性评价的路径以期为生成式人工智能更好地赋能高等教育形成性评价提供借鉴和参考。
【英文摘要】：
Generative artificial intelligence (GAI) has already acquired the important ability to engage in meaningful multi-round dialogues with humans. Traditional formative assessment in higher education is deficient in timeliness and personalization. How to use generative artificial intelligence to optimize the assessment process in higher education has become a common concern in education sector. This study aimed to provide intelligent feedback through generative artificial intelligence to optimize formative assessment and increase the efficiency and personalization of assessment, which could in turn promote effective learning. Using literature research method and inductive method, this study focused on formative assessment. On the basis of exploring GAI-empowered formative assessment in higher education, this study explores the challenges of GAI-empowered formative assessment in terms of the concept, object, process, result and ethics. It also proposes the pathway for GAI-empowered formative assessment. This study provides references and insights for better GAI-empowered formative assessment in higher education.