This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…

Proposes a Web-based model as the infrastructure to store learning logs for analysis in distance education. Describes the method of using query language to retrieve information from a database to construct the data cube. Illustrates data-cube implementation with a group-discussion example. Shows how data-cube technology can solve the recording and…