人工智能赋能财经专业大数据编程系列课程教学模式创新实践

Innovative Practice of the AI-Empowered Teaching Model for the Big Data Programming Course Series in Finance and Economics Majors

摘要: 数字经济的深入发展推动财经岗位加速向“财经 + 数据 + 智能”复合形态转型，大数据编程系列课程已成为高职财经专业的核心课程。针对该系列课程教学中存在的学生基础差异显著、教学内容与财经岗位场景脱节、教学手段单一、评价方式滞后等突出问题，本文以广东某高职院校财经学院的教学改革实践为例，构建了AI赋能的“目标–内容–方法–评价”四维重构教学模式：依托AI学情画像实施分层分类教学，借助生成式人工智能重构“财经场景 + 编程技能”模块化课程内容，推行“人机协同”混合式教学与贯穿式项目实训，建立基于学习行为数据的过程性多元评价体系。实践表明，该模式有效激发了学生学习兴趣，显著提升了编程应用能力与数字化职业素养，同时，针对AI代写抄袭、平台投入成本与教师能力建设等现实问题提出了可操作的应对策略，可为同类院校财经专业课程数字化转型提供参考。

Abstract: The in-depth development of the digital economy is accelerating the transformation of finance-related jobs toward a composite form of “finance + data + intelligence”, and the big data programming course series has become a core course of finance and economics majors in higher vocational colleges. In view of the prominent problems existing in the teaching of this course series, such as striking differences in students’ prior learning, disconnection between teaching content and real finance job scenarios, monotonous teaching methods and outdated evaluation approaches, this paper takes the teaching reform practice of the School of Finance and Economics of a higher vocational college in Guangdong as an example to construct an AI-empowered teaching model featuring four-dimensional reconstruction of “objectives-content-methods-evaluation”: implementing tiered and classified teaching based on AI learning profiles; reconstructing modular course content of “finance scenarios + programming skills” with the support of generative artificial intelligence; carrying out human-AI collaborative blended teaching and project-based training running through the whole course series; and establishing a process-oriented and multi-dimensional evaluation system based on learning behavior data. Practice shows that this model has effectively stimulated students’ learning interest and significantly improved their programming application ability and digital vocational competence; it also puts forward operable countermeasures against practical challenges such as AI-assisted plagiarism, cost pressure and teachers’ capacity building, which may provide a reference for the digital transformation of finance and economics courses in similar higher vocational colleges.