数智赋能课程质量建设提升路径与模式创新研究——以《证券投资学》为例

Research on the Enhancement Path and Model Innovation of Course Quality Construction Empowered by Digital Intelligence—A Case Study of the “Securities Investment” Course

摘要: 在数字经济与金融科技深度融合的背景下，传统商科课程面临教学内容滞后、教学模式单一、评价体系片面及教学资源静态化等多重挑战。本研究以金融学核心课程《证券投资学》为实践载体，旨在系统探讨数智技术赋能课程质量建设的系统性路径与整体性模式创新。通过构建“内容–教学–评价–管理”四位一体的数智化课程建设新范式，本研究提出并实践了以“诊断–设计–开发–实施–评估–推广”为核心的课程数智化升级闭环路径。研究实践表明，该模式通过“沉浸式–交互式–探究式”教学模式的深度应用与全过程多元智能评价体系的构建，有效提升了课程的高阶性、创新性与挑战度，显著增强了学生的数据素养、实战能力与综合职业素养。本研究成果为应用型文科课程的系统性数智化转型提供了兼具理论支撑与实践验证、可复制、可推广的解决方案。

Abstract: Against the backdrop of the deep integration of the digital economy and financial technology, traditional business courses face multiple challenges, such as outdated teaching content, singular teaching models, one-sided evaluation systems, and static teaching resources. This study takes the core finance course “Securities Investment” as a practical vehicle, aiming to systematically explore the systemic pathways and holistic model innovation for course quality construction empowered by digital intelligence technologies. By constructing a new paradigm for digitally intelligent course construction that integrates “content-teaching-evaluation-management” into a cohesive whole, this study proposes and implements a closed-loop path for course digital intelligence upgrading centered on “diagnosis-design-development-implementation-evaluation-promotion”. Practice has shown that this model, through the deep application of the “immersive, interactive, inquiry-based” teaching mode and the construction of a whole-process, multi-dimensional, and intelligent evaluation system, effectively enhances the course’s advanced nature, innovation, and challenge level, significantly improving students’ data literacy, practical ability, and comprehensive professional competence. The research outcomes provide a theoretically supported and practically verified, replicable, and scalable solution for the systematic digital-intelligent transformation of applied liberal arts courses.