Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

A concern of computer-based learning system design is how to accommodate learners' individual differences during learning activities. Previous research suggests that adaptive e-learning systems can effectively address such individual differences and, consequently, they enable more directed tutoring via computer-assisted instruction. In this paper,…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…