EDUCATIONAL DATA MINING AND ITS USES TO PREDICT THE MOST PROSPEROUS LEARNING ENVIRONMENT

Abstract

The use of technology and data analysis within the classroom has been a resourceful tool in order to collect, study, and compare a student's level of success. With the large amount of regularly collected data from student behaviors, and course structure there is more than enough resources in order to find student success with data analysis. A method of data analysis within a learning environment is called Educational Data Mining (EDM), which has proven to be an emerging trend when it involves the development of exploration techniques and the analysis of educational data. EDM has been able to contribute to the understanding of student behavior, as well as factors that influence both student actions and their success. The study of student success within EDM has focused on student learning patterns, student to teacher culture, and teaching techniques. In this research we will look at uses of technology and data mining in an EDM setting and compare the success of findings. Using past experience of other research we will determine which method would be best in order to look at a learning environment, and try to find which factors will affect a student's academic performance.