A MOOC Video Viewing Behavior Analysis Algorithm

Yong Luo, Guochang Zhou, Jianping Li and Xiao Xiao

Mathematical Problems in Engineering, 2018, vol. 2018, 1-7

Abstract:

MOOCs (massive open online courses) are developing rapidly, but they also face many problems. As the MOOC’s most important resource, the course videos have a very important influence on the learning. This article defines the ratio ( ), which reflects the popularity of the video. By analyzing the relationship between the video length, release time, and , we found a significant negative linear correlation between video length and and video release time and . However, when the number of videos is less than the threshold, the release time has less influence on . This paper presents a video viewing behavior analysis algorithm based on multiple linear regression. The residual independence test proved that the algorithm has a good approximation to the data. It can predict the popularity of similar course videos to help producers optimize video design.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7560805

DOI: 10.1155/2018/7560805

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