摘要： 针对高校计算机基础类课程学生基础差异大、实践监督难、师生互动效率低等教学痛点，探索数据驱动的混合式教学优化路径。以《计算机知识及应用初步》为对象，构建基于雨课堂平台的“线上预习-线下研讨-云端实践”三位一体混合式教学模式。引入数据治理体系，通过ETL技术(数据抽取-转换-加载)标准化采集数据，形成“数据采集-治理-分析-应用-反馈”的教学优化闭环。问卷调查与梯度分析结果显示，该模式显著提升了学生课堂参与度、知识内化率及实践能力。研究表明，多维交互与数据驱动的教学闭环可为同类课程改革提供有效借鉴。

中图分类号：TP391.1文献标志码：ADOI:10.19358/j.issn.2097-1788.2026.07.007
中文引用格式：刘佳祎，魏智程，唐瑞.数据治理赋能计算机基础混合教学［J］.网络安全与数据治理，2026，45（7）：47-54.
英文引用格式：Liu Jiayi, Wei Zhicheng, Tang Rui. Data governance empowering blended teaching of computer fundamentals［J］.Cyber Security and Data Governance，2026，45（7）：47-54.

Data governance empowering blended teaching of computer fundamentals

Abstract： To address critical pedagogical challenges in fundamental computer science courses—such as significant disparities in student proficiency, difficulties in supervising practical exercises, and low efficiency in teacherstudent interaction—this study explores a data-driven optimization pathway for blended learning. Focusing on the course "Introduction to Computer Knowledge and Application", we construct a "threeinone" blended teaching model comprising "online preview, offline seminar, and cloud-based practice" based on the Rain Classroom platform. A data governance framework is introduced, utilizing ETL (Extract, Transform, Load) technology for standardized data collection to establish a closedloop mechanism for teaching optimization: data collectiongovernanceanalysisapplicationfeedback. Results from questionnaire surveys and gradient analysis indicate that this model significantly enhances student engagement, knowledge internalization, and practical skills. The findings suggest that a multidimensional interactive and datadriven teaching loop offers a valuable reference for reforming similar courses.

Key words : Rain Classroom platform; blended learning; fundamental computer courses; data governance; data-driven