Understanding Information Bias: The Perspective of Online Review Component: An Abstract

Author(s):  
Qiong Jia ◽  
Yue Guo ◽  
Stuart Barnes
2007 ◽  
Author(s):  
Gabriella Pravettoni ◽  
Claudio Lucchiari ◽  
Salvatore Nuccio Leotta ◽  
Gianluca Vago

Author(s):  
Bing Wu

AbstractAlthough some studies have explored massive open online courses (MOOCs) discussion forums and MOOC online reviews separately, studies of both aspects are insufficient. Based on the theory of self-determination, this paper proposes research hypotheses that MOOC learning progress has a direct impact on MOOC online reviews and an indirect influence on MOOC online reviews through social interactions in discussion forums, as well. Coursera the largest MOOC platform, is selected as the empirical research object, and data from learners who participated in the MOOC discussion forum and provided MOOC online reviews from August 2016 to December 2019 are obtained from the most popular course, “Machine Learning”. After processing, data from 4376 learners are obtained. Then, according to research hypotheses, multi regression models are constructed accordingly. The results show that the length of MOOC online review text is affected by the MOOC learning progress, the number of discussion forum posts, the number of follow, the online review sentiment and MOOC rating. This study highlights the main factors that affect MOOC online reviews. As a result, some suggestions are put forward for the construction of MOOC.


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