大数据驱动的双线融合课程教学质量评价体系构建

Data-driven construction of teaching quality evaluation system for online-offline blended courses

随着政策引导和MOOC课程兴起,双线融合课程成为高校教学实践新常态。文章基于CIPP评价模式,将定量和定性方法相结合,收集政策公告、理论文献、人工智能问答3类文本,通过高频词分析和语义网络图提取双线融合课程质量3级评价指标。接着,利用信效度检验和层次分析法计算指标权重,构建系统的教学质量评价体系。最后,运用多主体问卷和模糊综合评价法,针对线上比重不同的两门课程进行数据对比,提出相应改进策略。

With policy guidance and rise of MOOC courses,online-offline blended courses become the new trend of teaching practices in universities.Based on CIPP evaluation model,this paper combines quantitative and qualitative methods by collecting three types of texts,policy announcement,theoretical literature and AI-enabled Q&A,and extracting three-level quality evaluation indicator of online-offline blended courses through high-frequency word analysis and semantic network graph.Then,using reliability,validity tests and analytic hierarchy process to calculate the weight of indicators,it constructs the teaching quality evaluation system.Finally,multi-subject survey and fuzzy comprehensive evaluation method were adopted to compare the data of two courses with different online proportions,and proposes improvement strategies.