School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…

To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

We examine the effectiveness of a planning prompt intervention to reduce procrastination on online homework for college students. The intervention asked students to indicate their intention to earn small amounts of extra credit for completing assignments earlier and form a plan to realize their intentions. Students' learning behavior is measured…