No abstract

The majority of adaptive and intelligent tutoring systems (AITS) are dedicated to a specific domain, allowing them to offer accurate models of the domain and the learner. The analysis produced from traces left by the users is didactically very precise and specific to the domain in question. It allows one to guide the learner in case of difficulty and to offer her/him some support. This paper's objective was to develop an (AITS), adapted for letting the learners work in several disciplinary fields of the University of the Annaba. In this context, its constraint is threefold: to represent knowledge relative to several disciplinary domains, to propose interactive activities to the learners based on multiple intelligences, and finally, to be able to support student guidance in her/his course by proposing her/him relevant support activities when she/he meets difficulties. The proposed system covers all important properties such as hypertext component, adaptive sequencing, problem-solving support, intelligent solution analysis and adaptive presentation while available systems have only some of them. Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Procedure remediation-activity; Given: A current activity, L learner; Result: A* new activity; Begin Case the evaluation result of Failure: { Call Strategy-concepts-candidates; If the determined new activity A* is not found then Call Strategy-concepts-precedence; If the determined new activity A* is not found then Call change-presentation; } Success: { Call Strategy-concepts-candidates; If the determined new activity A* is not found then Call Strategy-concepts-sufficiency;If the determined new activity A* is not found then the system will provide the teacher through teaching space to support the learner in difficulty choosing another activity. } End

No abstract

No abstract

Personalized feedback strategies is a powerful method that expert humans apply when helping learners to optimize their learning. Thus, research on feedback strategies tailoring feedback according to important factors of the learning process has been recognized as a promising issue in the field of adaptive e-learning systems. Our paper seeks to contribute to this area of research by addressing the following aspects: First, to investigate how learners' feedback and learners' multiple intelligences relate to learning outcomes. Second, to explore the influence of the feedback strategies on students' behavior.

No abstract

No abstract

No abstract