人工智能工具在金融数据分析课程中的规范化融入路径研究

Study on the Standardized Integration Path of Artificial Intelligence Tools in the Financial Data Analysis Course

摘要: 生成式人工智能工具的快速普及正在重塑金融数据分析课程的教学生态，但工具使用的失范现象也随之显现，亟须系统性的规范化融入路径。本研究以高职金融数据分析课程为对象，剖析人工智能工具融入教学过程的现状与典型失范问题，提出“目标锚定、场景适配、过程规约、评价约束”的规范化融入框架，并从教学目标重构、内容场景设计、使用规则制定、评价体系改革四个维度构建实施路径。实践表明，规范化融入能够在发挥人工智能工具增效赋能作用的同时，有效防范能力替代、认知惰化与学术失范风险，为同类课程的数字化改革提供可借鉴的经验。

Abstract: The rapid popularization of generative artificial intelligence tools is reshaping the teaching ecology of financial data analysis courses, but the phenomenon of tool misuse is also accompanying it. Clearly, there is an urgent need for a systematic and standardized integration path. This study focuses on the financial data analysis course in vocational colleges and analyzes the integration of artificial intelligence tools. The current situation and typical misconduct issues in the teaching process, proposing a standardized integration framework of “target anchoring, scenario adaptation, process specification, and evaluation constraints” construct an implementation path from four dimensions: reconstruction of teaching objectives, design of content scenarios, formulation of usage rules, and reform of evaluation systems. Practice has shown that the integration of standardization can effectively prevent capability substitution, cognitive inertia, and academic loss while leveraging the efficiency and empowerment of artificial intelligence tools to provide valuable experience for the digital reform of similar courses through risk assessment.