An Artificial Intelligence algorithm for creating personalized learning journeys for students

With the fast growing information available on the web, students are often greeted with countless learning materials. As such, personalization is an essential strategy for facilitating relevant learning materials to satisfy students’ needs. The scope of this project is to design a recommendation system by using a deep learning process for personalized learning based on a quiz module. At the end of the project, we would be able to determine how students like to learn and to evolve the learning path based on strengths to enhance the learning experiences. Moreover, based on the obtained model, we will provide recommendation and dialogue to support learning. The proposed recommender system is based on hybrid filtering that considers both content-based and collaborative filtering properly. Indeed, the students’ historical data and the information of learning resources are taken into account to design a learning path to the students based on their needs.

Faculty Supervisor:

Michael Chen


Mohammad Reza Peyghami


Stem Minds Corp








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