The aim of this paper is to propose a methodology for modeling and implementing algorithms over data from student management systems with RapidMiner. RapidMiner is an environment for business analytics, predictive analytics, data mining, text mining, and machine learning. Traditional educational systems collect a lot of data about students. The collected data can be used to extract information and experiences. The extracted information can help school managers prepare better curriculum and manage the schools in an informed manner. Teachers can have advanced information about student progress and the potential weaknesses in courses. In this paper we describe how tools like RapidMiner can be used to extract information from raw student data. We have used student data from the Macedonian educational system, compared different algorithms and chose the most appropriate for the given model.
Student Analysis, Academic Analytic, Educational Data Mining, RapidMiner.