A machine learning approach to student modelling

This paper describes an application of established machine learning principles to student modelling. Unlike previous machine learning based approaches to student modelling, the new approach is based on attributevalue machine learning. In contrast to many previous approaches it is not necessary for the lesson author to identify all forms of error that may be detected. Rather, the lesson author need only identify the relevant attributes both of the tasks to be performed by the student and of the student’s actions. The values of these attributes are automatically processed by the student modeler to produce the student model.