A Teaching Quality Evaluation System of Massive Open Online Courses Based on Big Data Analysis

Zhifang Wang, Jia Liu

Abstract


Massive open online courses (MOOC) transcends the time and space limits of traditional classroom teaching, and promotes the sharing of teaching resources. However, the effect of this emerging teaching mode is yet to be determined. In this paper, the big data analysis is introduced to evaluate the MOOC teaching quality. Taking several online courses as an example, a video player was de-signed to compute the learning time using the Hadoop platform. On this basis, the author constructed a teaching quality evaluation platform. In addition, the learning cost coefficient was calculated by the naive Bayesian model, and the evaluation results were analysed in details. The research findings shed practical new light on the evaluation of MOOC teaching quality.

Keywords


big data; cloud computing; massive open online courses (MOOC); teaching quality evaluation system

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Copyright (c) 2019 Zhifang Wang, Jia Liu


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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