生成式人工智能背景下新商科课程教学体系创新研究

Innovation in the Teaching System of New Business Education in the Context of Generative Artificial Intelligence

摘要: 生成式人工智能已进入本科商科课程的多个环节，学生在资料检索、案例分析、市场调研和课程报告写作中使用人工智能的情况日益普遍。对于新商科建设而言，这一变化不仅意味着教学工具更新，也使传统课程中以成果文本判断学习质量的方式面临挑战。已有研究表明，生成式人工智能有助于提高信息获取、数据处理、个性化学习和过程性反馈的效率，但效率提升并不必然带来高阶认知能力、商业判断能力和真实问题解决能力的提升。本文在分析生成式人工智能嵌入新商科课程现实影响的基础上，提出从课程目标、课程内容、教学过程和评价方式四个方面优化教学体系。研究认为，生成式人工智能背景下新商科课程改革的重点，是围绕人工智能素养、商业问题解决能力和过程性评价重新设计课程体系，使人工智能应用能够支持学生的问题建构、证据判断和商业分析能力培养。

Abstract: Generative artificial intelligence has been increasingly integrated into multiple aspects of undergraduate business education. Students now commonly use AI tools for information retrieval, case analysis, market research, and course report writing. For the development of New Business Education, this shift represents not merely an update of teaching tools, but also a challenge to the traditional approach of evaluating learning quality primarily through final written outputs. Existing studies suggest that generative artificial intelligence can improve the efficiency of information acquisition, data processing, personalized learning, and formative feedback. However, greater efficiency does not necessarily lead to the development of higher-order cognitive abilities, business judgment, or the capacity to solve real-world problems. Based on an analysis of the practical implications of embedding generative artificial intelligence into New Business courses, this paper proposes optimizing the teaching system from four dimensions: course objectives, course content, teaching processes, and assessment methods. The study argues that, in the context of generative artificial intelligence, the reform of New Business courses should focus on redesigning the curriculum around AI literacy, business problem-solving competence, and process-oriented assessment, so that the use of artificial intelligence can effectively support students’ development of problem construction, evidence evaluation, and business analysis capabilities.