Predicting student's performance using Data Mining Techniques from Big Data Technology in Cloud Computing

Over the past few years the higher education sector has expanded rapidly. Several new universities have arisen from both the public and private sectors that deliver a range of courses for undergraduate and postgraduate students. University education enrolment rates have also risen but not so much as the number of higher establishments is rising. This is a challenge for today's education system and this gap needs to be discussed and presented adequately to the learning community. The quantity of data stored in an educational database is rapidly increasing. Such databases provide secret information to enhance the performance of students. Morocco's success in higher education is a tipping point for all students in universities. Many considerations affect this academic success. On the one hand, using data mining techniques from big data technology aimed to resolve the questions of predictions of not just the students but also about other especially in the education fields, and on the other hand, Cloud computing offers fundamental support for solving the problems of shared computing resources, such networking, storage, computing, and analytical software. The objective of this paper is to develop an approach of utilizing data mining methods from big data technology in cloud computing to predict student performance. It may bring the impacts and profits to educators, students, and educational establishments.