A course recommendation system based on grades

Abstract

The online courses are playing a crucial role in developing new skills in learners and in the education system. Now a days a massive number of online courses and certifications are available over the internet from universities as open learning platforms. As there is no in-person consultation with any expert, the learners may opt for irrelevant courses inadvertently and may not be able to analyze their own suitability and adaptability of the courses which will west learners time and resources. This paper proposes a machine learning approach to recommend suitable courses to learners based on their learning history and past performance. The framework first classifies a new learner based on their past performance using the k-means clustering algorithm. Collaborative filtering will be applied in the cluster to recommend a few suitable courses. Further, based on an online test the adaptability of the learner will be tested to the customized recommended courses according to learners needs. The framework will provide a personalized environment of study to each learner.