Intelligent Agents to Improve Adaptivity in A Web-Based Learning Environment

Abstract

This chapter focuses on the use of intelligent agents in on-line learning environments in which educational organizations can equip students with lifelong learning skills for today’s society. In this scenario, and for this case, a web agent can be thought of as a software package with the potential to improve the guidance provided to the user through personalized contents considering learning styles and cognitive states. Agents proposed here, will provide the students with personal assistants than can help them to carry out learning activities according to their learning styles and knowledge level. The student’s progress is tracked and his/her motivation during learning is also taken into consideration. The agent’s environment is built by means of a multiagent architecture (MASPLANG) designed to support adaptivity (adaptive presentation and adaptive navigation) in a hypermedia education system (USD) used for distance learning on the web. A distinguished feature of the proposed approach is the ability to build a hybrid student model beginning with a student stereotype model which considers the student’s learning style and it is gradually modified as the overlay model is built from information acquired from the student’s interaction (subjective likes) within the learning environment.