MOOC

Modeling MOOC Dropouts

In this project, we model MOOC dropouts using user activity data. We have several rounds of feature engineering and generate features like activity counts, percentage of visited course objects, and session counts to model this problem. We apply logistic regression, support vector machine, gradient boosting decision trees, AdaBoost, and random forest to this classification problem. Our best mode...

Dropout: MOOC Participants’ Perspective

Massive Open Online Courses (MOOCs) open up learning opportunities to a large number of people. A small percentage (around 10%) of the large numbers of participants enrolling in MOOCs manage to ?nish the course by completing all parts. The term ‘dropout’ is commonly used to refer to ‘all who failed to complete’ a course, and is used in relation to MOOCs. Due to the nature of MOOCs, with student...

The Post-MOOC World

We’ve become so accustomed to the cycle of hype that we apply it to every new innovation without thinking. We expect all new technologies to be swept upward on a wave of emotion, only to fall to earth when the hype wears o . By reducing innovation to a stereotype, we overlook the new ideas that each innovation can bring. A recent swing in the cycle of hype began in 2011, when massive open onlin...

Describing MOOC-based Hybrid initiatives: The H-MOOC Framework

Several studies have described different hybrid initiatives to integrate MOOCs into traditional higher education. Most of these studies have partially documented students’ perception on hybrid initiatives, measuring course satisfaction among other metrics. Few researchers have reported institutional efforts implied in implementing hybrid initiatives and their benefits from a curriculum perspect...

an Investigation of Factors Affecting Utilization of MOOC from the perspective of R MOOC learners