A novel disengagement detection strategy for online learning using quasi framework

The online learning gains more popularity in recent days; its key success is delivering content over internet and can be accessed by students from anywhere and anytime. In general, attraction is the quality of arousing interest. Similarly, motivation is the other hand to support for learning. Since, the online learning has less control over students compared to the conventional teaching method. Therefore engagement of student gets more importance on online learning. Most of the learning systems stores learners activities in log files and their profile related informations in database. Usually log file analysis alone could not have enough data to find out disengagement. Thus we integrate the log file information with database and develop a novel disengagement detection strategy using quasi framework. This study result reveals that quasi framework is effective in term of quality compared to previous proposals.