Analyzing Student Behavior in Online Programming Courses
Rather than maintaining the classic teaching approach,a growing number of schools use the blended learning system in higher education.The traditional method of teaching focuses on the result of studentsprogress.However,many student activities are recorded by an online programming learning platform at present.In this paper,we focus on student behavior when completing an online open-ended programming task.First.we conduct statistical analysis to examine student behavior on the basis of test times and completed time.By combining these two factors,we then classify student behavior into four types by using k-means algorithm.The results are useful for teachers to enhance their understanding of student learning and for students to know their learning style in depth.The findings are also valuable to re-design the learning platform.
educational data mining learning analysis student behavior online programming blended learning environment
Xinyu You Bohong Liu Menghua Cao Tao Wang Yue Yu Gang Yin
Computer Science College,National University of Defense Technology,Changsha,China
国际会议
深圳
英文
48-56
2018-05-26(万方平台首次上网日期,不代表论文的发表时间)