Automating a Massive Online Course With Cluster Computing

Author:

Haas Timothy C.1

Affiliation:

1. University of Wisconsin–Milwaukee, USA

Abstract

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%.

Publisher

IGI Global

Reference41 articles.

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4. Social Network Analysis withsna

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