Personalized learning paths Recommendation based on Learner Personas
This research presents a method to form personalized learning paths based on learner personas to save learning time and improve learning achievements by providing learners with the most appropriate learning sequence and precise resources.
Abstract
With the rapid development of information and technology, internet learning resources, especially online learning platforms explosive developed in recent years. The problem of information overload and learning disorientation is particularly outstanding. Studies on personalized learning paths recommendation are important for the development of online learning. This research presents a method to form personalized learning paths based on learner personas. Learner personas are constructed based on their different characteristics. Based on the learner personas, and combined collaborative filter recommendation algorithm, the personalized learning paths consist of the path of the learning cells sequence network. Personalized learning paths will save learning time and improve learning achievements by providing learners with the most appropriate learning sequence and precise resources.