Intelligent student profiling for predicting e-Assessment outcomes

The main objective of this paper is introducing intelligence in the e-Learning and e-Assessment processes. Therefore, we present an existing adaptive e-Learning and e-Assessment strategies, verify them with machine learning (ML) algorithms, build students Profile and eventually, we present our new model that will be able to estimate the final result of the overall students' work during the semester, taking into account all the learning objectives that the students have passed. Thus, our idea is creating an intelligent agent that will simulate the behavior of a real professor as much as possible.