A MOOC Video Viewing Behavior Analysis Algorithm

Abstract EN

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 R (R=Average viewing duration/Video length), which reflects the popularity of the video.

By analyzing the relationship between the video length, release time, and R, we found a significant negative linear correlation between video length and R and video release time and R.

However, when the number of videos is less than the threshold, the release time has less influence on R.

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.