Pdf Towards An Adaptive E Learning System Based On Deep Learner Profile Machine Learning

(PDF) Towards An Adaptive E-Learning System Based On Deep Learner Profile, Machine Learning ...

(PDF) Towards An Adaptive E-Learning System Based On Deep Learner Profile, Machine Learning ... In this paper, we proposed an intelligent adaptive e learning system, based on machine learning and reinforcement learning. The proposed system uses machine learning and reinforcement learning algorithms to recommending a list of the most appropriate learning objects for learners according to their deep profile.

(PDF) Towards An Adaptive E-learning System Based On Individualized Paths In A Competency-based ...

(PDF) Towards An Adaptive E-learning System Based On Individualized Paths In A Competency-based ... Our contribution in this area of research is the development of an adaptive e learning system that can generate learning paths adapted to the profile of the learner. With the increase of the internet, e learning adaptation and recommnadation system has become a new trend in learning. in contrast to traditional learning (all. A design of an adaptative e learning system based on a multi agent approach and reinforcement learning is presented and the main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the q learning algorithm. Our contribution in this area of research is the development of an adaptive e learning system that can generate learning paths adapted to the profile of the learner.

(PDF) Towards Adaptive E-learning: Technological Challenges And Enabling Technologies

(PDF) Towards Adaptive E-learning: Technological Challenges And Enabling Technologies A design of an adaptative e learning system based on a multi agent approach and reinforcement learning is presented and the main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the q learning algorithm. Our contribution in this area of research is the development of an adaptive e learning system that can generate learning paths adapted to the profile of the learner. The author discusses creating an adaptive e learning model implemented in moodle lms, adapting content, format, and pedagogy based on a micro adaptive approach considering prior knowledge and learning styles. The objectives of this system are the creation of a deep profile of a given learner, via the implementation of k means and linear regression, and the recommendation of adaptive learning paths according to this deep profile, by implementing the q learning algorithm. This chapter introduces systems that use learner profile information to provide adaptive and personalized learning in real time. four major directions of adaptivity are discussed, namely adaptivity based on learning styles, cognitive abilities, affective states, and context and situation.

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