Learning trend has been shifted from a conventional way to a digital way in the form of E-learning, but it faces a high dropout ratio. Lack of engagement is one of the primary factors reported for this issue as the same type of course content is presented to learners despite their different background, knowledge and learning styles. Different…

Academic emotions of learners are important for academic achievement. For the online learning platform, it is of great value to gain insight into the academic emotion of the course in appropriate time interval from the platform. We crawled a large number of student comment texts from MOOC, and used deep learning algorithms (BERT models) to perform…

Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…

Predicting student performance in Massive Open Online Courses (MOOCs) is important to aid in retention efforts. Researchers have demonstrated that video watching features can be used to accurately predict student test performance on video quizzes employing neural networks to predict video test grades from viewing behavior including video searching…

Massive open online courses (MOOCs) provide learners with high-quality learning resources, but learners drop out frequently. Learners' concerns (e.g. the topics in course content or logistics) and cognitive engagement patterns (e.g. "tentative" or "certain") are considered the essential factors affecting learners' course…