Machine Learning Approach for an Adaptive E-Learning System Based on Kolb Learning Styles

In order to effectively implement adaptive learning within E-learning systems, it is crucial accurately define thelearner's profile that reflects the characteristics necessary for optimal learning. Traditional methods of identifying profiles often relyon questionnaires collect data from learners, which can be time-consuming and result in irrelevant due arbitrary responses.As a solution, we propose an intelligent dynamic model takes into account entire process,from diagnostic assessment knowledge assimilation. Our approach utilizes k-means classification algorithm group learners based on similar characteristics, as defined by KOLB model. To enhance accuracy our model, also incorporate neural networks automatically predict styles using decision tree adaptative pedagogical content learner. By doing so, aim improve overall performance proposed