【摘要】 在数字化学习深度融合高等教育的背景下，高校线上教学质量监控面临监控体系碎片化、评价标准单一化、数据分析浅层化三大核心问题。为此，本文以数据驱动决策理论、全面质量管理理论、建构主义学习理论为支撑，结合人工智能与信息工程学院教学特色，构建“三级督查—多维评价—数据赋能”三位一体的线上教学质量监控创新模式。通过我院试点实践，结合图表量化分析验证：该模式使计算机类课程线上教学的“代码提交率”从65%提升至92%、“实验报告优秀率”从58%提升至76%,有效优化信息流通效率、提升教学适配性、促进教师专业发展，为高等教育线上教学质量保障提供可复制的实践方案，助力教育数字化转型与教学理念革新。更多还原

【Abstract】 In the context of the deep integration of digital learning in higher education, the monitoring of online teaching quality in universities faces three core problems of fragmented monitoring systems, standardized evaluation criteria, and superficial data analysis.Therefore, this article, supported by data-driven decision-making theory, total quality management theory, and constructivist learning theory, integrates the pedagogical characteristics of the College of Artificial Intelligence and Information Engineering to construct a tripartite innovative model of online teaching quality monitoring, namely“three-level inspection-multidimensional evaluation-data empowerment”.Through pilot practices in our college, combined with quantitative analysis through charts, it is verified that this model has improved the“code submission rate”in computer science courses from 65% to 92% and the“excellent rate of lab reports”from 58% to 76%.It effectively optimizes information flow efficiency, enhances teaching adaptability, promotes professional development of teachers, and provides replicable practical solutions for quality assurance in online higher education teaching, thus assisting in the digital transformation of education and the innovation of teaching concepts.更多还原