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Automating a Massive Online Course with Cluster Computing

机译:使用集群计算自动化大规模在线课程

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Before massive numbers of students can take online courses for college credit, the challenges of providing tutoring support, answers to student-posed questions, and the control of cheating will need to be addressed. These challenges are taken up here by developing an online course delivery system that runs in a cluster computing environment and is designed to support the delivery of a course having 10K or more students. This delivery system enhances synchronous and asynchronous lectures, provides an online intelligent tutoring system, and detects plagiarism. The free software system is shown to provide fast response times when run on a mid-range cluster computer. The system's automatic plagiarism detection system is shown to be able to detect multiple authors of course assignments when used to analyze the work of actual online students. Use of this system on a large scale would allow most colleges to reduce their faculty size by 20 to 40%.
机译:在大量学生可以选择在线课程以获得大学学分之前,必须解决提供辅导支持,回答学生提出的问题以及控制作弊的挑战。通过开发在集群计算环境中运行的在线课程交付系统来应对这些挑战,该系统旨在支持提供一万或更多学生的课程。该交付系统增强了同步和异步授课的能力,提供了在线智能辅导系统,并发现了抄袭行为。当在中型群集计算机上运行时,该自由软件系统显示出提供快速的响应时间。该系统的自动抄袭检测系统在用于分析实际在线学生的工作时,能够检测课程任务的多个作者。大规模使用该系统将使大多数大学将其教员规模减少20%至40%。

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