论文标题
揭示隐藏模式：一项关于MOOC学生分析亚群的比较研究
Revealing the Hidden Patterns: A Comparative Study on Profiling Subpopulations of MOOC Students
论文作者
论文摘要
大规模开放的在线课程（MOOC）表现出显着的学生。复杂的“大数据”从MOOC平台的出现是一个充满挑战而有意义的机会，可以深入了解学生如何参与MOOC。过去的研究主要研究整体行为，可能错过了与学生多样性有关的模式。使用FutureLearn提供的MOOC的大数据集，我们深入研究了一种通过机器学习和统计建模来研究隐藏模式的新方法。在本文中，我们报告了学生活动的聚类分析以及对MOOC学生亚群之间行为模式和人口统计模式的比较分析。我们的方法可以更深入地了解MOOC学生的行为和成就。我们的发现可能用于设计适应性策略，以增强MOOC的体验
Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of students. The advent of complex "big data" from MOOC platforms is a challenging yet rewarding opportunity to deeply understand how students are engaged in MOOCs. Past research, looking mainly into overall behavior, may have missed patterns related to student diversity. Using a large dataset from a MOOC offered by FutureLearn, we delve into a new way of investigating hidden patterns through both machine learning and statistical modelling. In this paper, we report on clustering analysis of student activities and comparative analysis on both behavioral patterns and demographical patterns between student subpopulations in the MOOC. Our approach allows for a deeper understanding of how MOOC students behave and achieve. Our findings may be used to design adaptive strategies towards an enhanced MOOC experience
