Research on AIGC-Driven Teaching Reform of Python Financial Fundamentals Course in Higher Vocational Colleges

Abstract

With the acceleration of digital transformation of vocational education, artificial intelligence generated content (AIGC) technology provides a new opportunity for the reform of higher vocational classroom teaching. Taking the core course "Python Financial Fundamentals" of senior big data and accounting majors as an example, this study discusses in depth the practical path of AIGC-driven course teaching reform in response to the problems of traditional single teaching method, insufficient integration of financial scenarios and programming, and lopsided teaching evaluation that exist in the current teaching. The study proposes: using text, image and video AIGC tools to develop intelligent teaching resources, reduce the burden on teachers and enrich the form of content; constructing an intelligent learning analysis and question-answering system to provide personalized learning support and real-time feedback; relying on intelligent learning platforms to create virtual financial scenarios to support project-based learning and full-process practice; and using AIGC to realize intelligent teaching evaluation based on learning process data and open tasks. The study shows that AIGC can effectively improve teaching quality and students' practical ability. At the same time, the study also points out and proposes strategies to cope with the challenges of ethical risks of the technology, to improve teachers' ability to apply AIGC, and to prevent students' over-dependence. This study provides new ideas for the teaching reform of higher vocational education and the cultivation of compound financial talents.