CAJ | 학술논문

针对大规模在线公开课程（MOOC）注册学员高退出率和低完成率这一现象，通过数据挖掘的聚类手段，对参入MOOC学员的学习状态变化进行了分析，揭示参与MOOC课程的学员在学习目的上的分集，使MOOC课程发起者能够更好地调整授课内容和课程设置来满足不同学生的需求。
침대대규모재선공개과정（MOOC）주책학원고퇴출솔화저완성솔저일현상，통과수거알굴적취류수단，대삼입MOOC학원적학습상태변화진행료분석，게시삼여MOOC과정적학원재학습목적상적분집，사MOOC과정발기자능구경호지조정수과내용화과정설치래만족불동학생적수구。
The paper focuses on the high dropout rate versus the low completion rate among registered students for Massive Open Online Courses (MOOCs). It employs the clustering technique in data mining to analyze the changing process of participants’ learning motivations and reveal the different types of intentions for taking part in MOOCs, in a bid to help course designers better adjust lectures and curricula to meet the needs of different groups of students.