A useful prediction variable for student models: cognitive development level

Making a realistic update of a user model based on evidence in the environment is not an easy task, unless a great deal of time with a large variety of users is available. Creating general categories of users that behave in a certain way is important for any kind of user model. To obtain such a broad classification we need to understand general factors that influence user behavior. We describe the use of pretests to measure cognitive development of student users and how this factor is input to a student model. We describe how measures of cognitive ability enhance the predictive power of a student model in an intelligent tutoring system for a population of young (elementary school) students.