A Social Profile-Based Recommendation Architecture for E-Learning Systems

The increased reliance of education institutions on e-learning systems to provide learning and teaching activities and resources has prompted a need for innovative strategies that deliver effective learning to students. One approach being considered involves enhancing personalized learning experiences through the implementation of personalized learning paths. Personalized learning paths have proven highly beneficial for students; however, they are predominantly guided by learning objectives rather than the unique attributes of each student. Additionally, the inflexibility observed in e-learning systems poses a challenge in integrating customization options. This paper proposes an architecture for a recommendation system that creates personalized learning paths from a student's profile. The resulting architecture enhances an e-learning system's personalization by using external student data to create a more comprehensive student profile, thereby improving the system’s ability to generate learning paths and deliver technology-enhanced learning experiences.