Adaptative Instructional Planning Using Workflow and Genetic Algorithms

Many systems of distance learning do not consider the particular characteristics of the student and the same pedagogical strategies and content sequences are used for every student. But, the course can be customized by the introduction of adaptability in these systems. In order to develop adaptative systems of distance learning, it is necessary to consider the problems: instructional planning and the student model. The first problem allows to generate a specific sequence of content for each student and the second one provides the necessary information to cope with adaptivity.Planning techniques in artificial intelligence have been successfully used for determining the sequence of instructional actions. The workflow technology has been used for the management of these systems. Then, this paper presents an adaptative instructional planning and a student model based on theories of cognitive levels and learning styles.