A Recommender Engine for Advanced Personalized Feedback in e-Learning Environments

The paper presents an educational recommender engine, which is fired by the feedback module of an e-assessment application for the project management domain. The recommendations consist in web pages related to the knowledge gaps of the students who took an e-test. The authors argue that using a recommender engine within the e-assessment would increase the formative values of the e-assessment, transforming it into an innovative educational instrument, which gives the students the opportunity to take control of their own learning and actively participate in the learning process. A short evaluation of the utility of the recommendations is also provided.