This paper proposes a revised approach to the admission process for freshman students entering the minority serving institute, the University of Illinois at Chicago (UIC). The purpose of the revised approach is to better evaluate an extremely diverse population of applicants. The details for the revised approach will be demonstrated through the use of data mining, statistical methods and association rule mining.UIC is located in Chicago, Illinois and enrolls greater than 20,000 students from a wide spectrum of socio-economic neighborhoods. As a minority serving institute, it is of great concern to the University to better assess the capabilities of the diverse population of applicants.
Through this paper, the authors propose a process that integrates the socio-economic background of applicants into its admission process which allows for its applicants to be better evaluated. The proposed process increases the population of students with the potential to succeed, thereby increasing university retention rates. An extensive review on success and retention strategies that benefit not only minorities in Science, Technology, Engineering, and Mathematics but all students is provided. This process better assesses applicants from differing background and has the effect of increasing the population of minority students.In addition to the socio-economic based admission metric for such integration, this paper introduces a methodology and framework for a software to promote the success of students by recommending schedules based on their predicted performance. The types of information used in the development of this metric are available in almost every university or higher education institution. Therefore, the process in developing this metric can be implemented by other higher education institutions in the United States that have the potential to benefit from incorporating socio-economic factors into their admission procedure for applicants.