| Summary: | 碩士 === 中華大學 === 資訊管理學系 === 107 === In order to improve teaching effectiveness, Chung Hua University develops new teaching approaches and introduces auxiliary tools to enhance students' learning performance simultaneously. However, the learning information distributes in big data sets. Without data analytics, those reforms and innovations usually are under or over estimation. This research proposes a visual analytics on Gaussian distribution. It can display students’ learning patterns thus providing discoveries for teaching strategies and self-exam for both teachers and students.
The techniques in clustering analytics redisplays Gaussian distribution into clusters. It provides information to enhance the learning performance of individual classes, the effective analysis of teaching strategies, the curriculum planning of departments, etc. Students, teachers, and administrators can objectively get insight of practical situations and make adjustments to enhance effectiveness.
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