An Affective Model for Personalized Learning in Adaptive Educational Hypermedia Systems

The educational process is a complicated interaction between the teacher, the student and the environment where it takes place. It is important for a successful educational transaction for the teacher to recognize the learning and emotional needs of his student and to adapt the teaching and his behavior accordingly. In this poster we present an affective model, which augments an Adaptive Educational Hypermedia System (AEHS), with affective dimensions. This model correlates the individual preferences of a student with his personality and his emotional states. For this purpose, the model recognizes these affective factors and adapts accordingly its teaching and pedagogical strategy. The AEHS are intelligent systems that improve student’s performance by adapting their operation according to the student’s needs and interests supporting them with the appropriate learning strategy. An AEHS interacts dynamically with the student, using adaptation techniques like adaptability and adaptivity [3] and uses the student model, the domain knowledge, and the teaching model to achieve the adaptation of the system via the adaptive engine [2]. Thereby, an AEHS determines the educational content and the teaching process in a way that appertains the teaching in a real classroom. In a live educational process, the teacher takes into consideration the emotional state of his student by motivating him effectively in order to achieve the desirable learning goals. Many researchers have demonstrated the pedagogical value of emotions and the personality of the student and they have incorporated this perception in their educational systems [1], [4], [6]. Our proposed model is being realized by a module called Affective Module (AM), which interacts with an AEHS.