Emotions of learners are fundamental and significant in e-learning as they encourage learning. Machine learning models are presented in the literature to look at how emotions may affect e-learning results that are improved and optimized. Nevertheless, the models that have been suggested so far are appropriate for offline mode, whereby data for…

The rapid learning environment transition initiated by the COVID-19 pandemic impacted students' perception of, comfort with, and self-efficacy in the online learning environment. Garrison's Community of Inquiry framework provides a lens for examining students' online learning experiences through three interdependent elements: social presence,…

Personalized computer-based tutoring demands learning systems and applications that identify and keep personal characteristics and features for each individual learner. This is achieved by the technology of student modeling. One prevalent technique of student modeling is stereotypes. Furthermore, individuals differ in how they learn. So, the way…