生成式人工智能赋能金融学课程教学改革的路径探究

Exploring the Path of Generative Artificial Intelligence-Empowered Teaching Reform in Finance Courses

摘要: 教育数字化背景下，生成式人工智能为金融学课程教学改革提供了新的支持。针对当前金融学课程中知识点碎片化、案例更新滞后、数据训练不足和学生综合分析能力较弱等问题，本文探讨生成式人工智能赋能金融学课程改革的实践路径。研究认为，应坚持“教师主导–学生主体–技术辅助”的原则，构建以智能助教、案例驱动、数据实训和多元评价为核心的教学模式，并将其嵌入课前导学、课堂讨论、课后反馈和课程评价等环节，从而推动金融学课程由知识传授型向能力培养型、问题导向型和数据驱动型转变。

Abstract: Against the background of educational digitalization, generative artificial intelligence provides new support for teaching reform in finance courses. In response to problems such as fragmented knowledge acquisition, delayed case updates, insufficient data training, and weak comprehensive analytical ability among students in financial courses, this paper explores the practical path of applying generative artificial intelligence to finance course reform. The study argues that such reform should follow the principle of “teacher guidance, student-centered learning, and technology support”, and should build a teaching model centered on intelligent assistance, case-based learning, data practice, and diversified assessment. By embedding this model into pre-class guidance, classroom discussion, after-class feedback, and course assessment, finance courses can gradually shift from knowledge transmission toward ability cultivation, problem orientation, and data-driven learning.