Computerized Adaptive Testing in Computer Assisted Learning?

A major goal in computerized learning systems is to optimize learning, while in computerized adaptive tests (CAT) efficient measurement of the proficiency of students is the main focus. There seems to be a common interest to integrate computerized adaptive item selection in learning systems and testing. Item selection is a well founded building block of CAT. However, there are a number of problems that prevent the application of a standard approach, based on item response theory, of computerized adaptive item selection to learning systems. In this work attention will be paid to three unresolved points: item banking, item selection, and choice of IRT model. All problems will be discussed, and an approach to automated item bank generation is presented. Finally some recommendations are given.