Personlised Course Recommender (PCR)

E-Learning, which is the phenomenon of learning through the use of online resources, has recently witnessed a significant growth due to the plethora of learning material being made available online. Recommendation systems have been developed to help filter inappropriate or outdated resources and automatically make recommendations based on the learners' current academic level and needs. This research aims to delve further into this developing field and apply Artificial Intelligence and Machine Learning algorithms in order to investigate the benefits of a Personalised Course Recommender (PCR) that generates recommendations based on learner profiling. Moreover, the system will also calculate the predicted success rate of completing each recommended course to further ensure that the learner receives recommendations adequate to their current knowledge and interests as well as to save the learners time, energy and funds if a course is predicted to have a low success rate.