ITE Technical Report
Online ISSN : 2424-1970
Print ISSN : 1342-6893
ISSN-L : 1342-6893
41.05 Multi-media Storage(MMS)/Consumer Electronics(CE)/Human Information(HI)/Media Engineering(ME)/Artistic Image Technology(AIT)
Session ID : MMS2017-18
Conference information

Predicting View and Exit Rates on MOOC
*Yusuke FUKUSHIMAToshihiko YAMASAKIKiyoharu AIZAWAKenshiro MORIKensho SUZUKI
Author information
Keywords: e-learning, MOOC, regression
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract

While massive open online courses (MOOC) have gained increasing popularity in recent years, predict- ing the number of students who attend and leave from classes is an important task to analyze their interests. In this paper, we proposed a method to predict the number of views and dropout rates. The effect of each factor, such as broadcasting dates and contents of classes, was also investigated to reveal the components that are significant to prediction. We tested our method using a collection of 2,327 lecture videos broadcasted in Schoo.

Content from these authors
© 2017 The Institute of Image Information and Television Engineers
Previous article Next article
feedback
Top