Adaptive and Intelligent Web-Based Educational Systems

Currently, when aiming at providing learners with opportunities for technology enhanced learning, companies, universities, and other educational institution mainly use so-called learning management systems (LMS). LMSs are Web-based educational systems that aim at supporting teachers and administrators in creating, administering, and managing online courses. These systems provide a great variety of features which can be included in courses such as learning material, quizzes, forums, chats, assignments, wikis, and so on. However, at current stage, such environments provide very little, or in most cases, neither intelligent support nor adaptivity for learners. Adaptive and intelligent Web-based educational systems (AIWES) address this issue and aim at providing learners with an environment that reacts intelligently to the learners' needs and incorporates their individual characteristics and situation by presenting suitable suggestions, information, and learning material in order to make learning more effective and easier for learners. The term adaptive refers to the func-tionality of the system to automatically provide different suggestions, courses, or activities to learners with different characteristics and needs. The term intelligent here means that a system uses artificial intelligence techniques in order to support learners or identify their characteristics, needs, and situation. and De Bra's adaptive hypermedia course (De Bra, 1996). During the last few years, many research works have been carried out in the area of AIWESs and many systems have been developed (Brusilovsky & Peylo, 2003; Sadat & Ghorbani, 2004). While the first AIWESs focused on considering and identifying the knowledge state and progress of students in a course or task, a broader set of characteristics, needs, and states of learners has been investigated and considered in current systems, including, for example, students' learning styles, cognitive abilities, affective states, learning goals, interests, misconceptions, and so on. Systems aim at identifying these characteristics, needs, and states dynamically by observing the students' behaviour, progress, and interaction with the system and applying artificial intelligence techniques in order to fill and update the student model.