E-learning has become a reality which it is impossible to ignore now, especially in this break out of worldwide pandemic. The need to know about its concerns, related concepts, types, algorithms, skills, tools, implementation, deployment and evaluation have motivated many researchers. it also seems reasonable to expect that researchers will rate the computer as the greatest invention in human history in terms of facilitating global communication. E-learning assessment is process of assessing teaching and learning activities in the e-learning system. This paper hovers around the review of literatures on e – learning assessment with clustering method. Assessment is one of the integral parts of the educational system all over the world and it plays a vital role in students’ learning progress. This is achieved through different means of assessments which will be added together to achieve effective results in student learning progress. However, it has been observed that students who have undergone e-learning programme just read for grade at the end of the semester thereby lacking learning progress monitoring during the course of study. Most under-graduate and post-graduate modules are fully online but only few numbers of continuous assessment tests (cats) are delivered online. E-learning assessment is a means of assessing students’ learning outcomes in e-learning system and most existing systems are based on summative assessment which assess students only at the end of the semester but this assessment system uses clustering method of data mining and formative assessment mechanism, this will significantly improve students’ learning experiences and achievements. This constructive criticism and insight can be used to create an action plan that moves forward the ability to modify learning behaviors and achieve their learning goals.