This paper introduces the study of the learners' behavior on e-learning platform to create profiles that regroup learners according to their behavior on the platform. This system can be used by the learner-agent of an intelligent tutoring system (ITS). Thus, this system will allow us to better understand the learner in a virtual learning environment to improve the learning situation by placing the learner at the center of the learning process

No abstract

This paper presents the detailed results of the study that we performed on our adaptive Learning Management System Manhali. This study was addressed to first year university students in Computer Engineering. The experiment was in the form of an online course intended to analyze and evaluate learner behavior on the e-learning platform and to identify their learning styles according to two learning styles theories: Kolb's theory and Felder's theory. The main objective was to study two important relationships in e-learning systems: The relationship between the behavior of a learner and their academic performance, and the relationship between the gender of the learner and their learning style.

E-learning has become a fundamental part of child education, higher education, and corporate training. In the design of adaptive e-learning environments, it is important to track and analyze learner behavior and preferences, and this is possible by recording their eye movements. Eye tracking is a technology developed to monitor eye movements allowing us to analyze the recorded gaze data. The main goal of this chapter is to determine the potential of eye tracking in the field of e-learning and the various applications of eye movement analysis for e-learning platforms. Results can be used to design an adaptive e-learning environment able to collect, analyze, and understand learner online behavior, preferences, and needs, and then offer an educational content adapted to each learner's needs by generating new customized learning situations.

This paper presents a study performed on the Learning Management System Manhali used to analyze and evaluate the learners' online behavior. This study is addressed to first year students in computer science to study their learning style from behavior data on the e-learning platform, or from other tools to measure learning style such as the ILS questionnaire of Felder and Silverman. The paper also introduces the main components of the learner profile of our e-learning system and the method that we created to evaluate and regroup learners according to their behavior on the platform. General TermsE-Learning; learning management system; online learning platform; virtual learning environment. KeywordsLearner modeling; learner profile; learner behavior; learning style; behavioral analysis system.