面向《多媒体技术》课程个性化教学的数据挖掘与分析

Data Mining and Analysis for the Personalized Teaching of Multimedia Technology Course

对多媒体技术在线学习平台中积累的大量教学基础数据进行挖掘与分析研究,建立了选课数据仓库雪花模型,通过Apriori算法挖掘出学生所选的各门媒体技术成绩与期末成绩之间的内在联系,利用k-means算法对实施个性化教学以来的所有学生成绩进行聚类分析,并对结果可视化处理,分析各类学生的特点,为改善个性化教学质量提供数据支持和决策参考。

Since personalized teaching has been implemented in multimedia technology teaching in the past five years, a lot of teaching data accumulated from multimedia technology online learning platform. The article introduced data mining and analysis technology to process these data in order to obtain support and decision-making reference for the improvement of the quality of personalized teaching. First, the snowflake model of courses selection for data warehouse was built. Then the Apriori algorithm was used to dig out the inner link between the students' media technology achievements and the final grade. And then cluster analysis with k- means algorithm on all students' scores was conducted. Finally, the calculated results were visualized and analyzed. Practice proved that data mining and analysis technology is a useful tool for quantitative analysis in the teaching.