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Beyond Grade Point Average and Standardized Testing: Incorporating a Socio-Economic Factor in Admissions to Support Minority Success

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2018

Conference Session

Minorities in Engineering Division Technical Session 8

Tagged Division

Minorities in Engineering

Tagged Topic

Diversity

Page Count

15

Permanent URL

https://peer.asee.org/27657

Download Count

33

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Paper Authors

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Houshang Darabi University of Illinois, Chicago

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Dr. Houshang Darabi is an Associate Professor of Industrial and Systems Engineering in the Department of Mechanical and Industrial Engineering (MIE) at the University of Illinois at Chicago (UIC). Dr. Darabi has been the Director of Undergraduate Studies in the Department of MIE since 2007. He has also served on the College of Engineering (COE) Educational Policy Committee since 2007. Dr. Darabi is the recipient of multiple teaching and advising awards including the COE Excellence in Teaching Award (2008, 2014), UIC Teaching Recognitions Award (2011), and the COE Best Advisor Award (2009, 2010, 2013). Dr. Darabi has been the Technical Chair for the UIC Annual Engineering Expo for the past 5 years. The Annual Engineering Expo is a COE’s flagship event where all senior students showcase their Design projects and products. More than 600 participants from public, industry and academia attend this event annually.

Dr. Darabi is an ABET IDEAL Scholar and has led the MIE Department ABET team in two successful accreditations (2008 and 2014) of Mechanical Engineering and Industrial Engineering programs. Dr. Darabi has been the lead developer of several educational software systems as well as the author of multiple educational reports and papers. Some of these products/reports have already been launched/completed and are now in use. Others are in their development stages. Dr. Darabi’s research group uses Big Data, process mining, data mining, Operations Research, high performance computing, and visualization techniques to achieve its research and educational goals.

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Elnaz Douzali University of Illinois, Chicago

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Elnaz Douzali is a graduate student and researcher at the University of Illinois at Chicago. She is a part of the Mechanical and Industrial Engineering Department and will receive her Masters of Science degree in Industrial Engineering in May 2018. Her research interests include Educational Data Mining, Process Mining, and Healthcare.

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Samuel Thomas Harford PROMINENT Labs UIC

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Samuel Harford is a graduate research assistant at the University of Illinois at Chicago's Mechanical and Industrial Engineering Department. He received his BSIE in May 2016 from UIC and is currently pursuing his MS. Since 2015 he has done multiple projects in education data mining, some in collaboration with the Dean of Engineering. His research interests include healthcare and education data mining.

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Peter C. Nelson University of Illinois, Chicago

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Peter Nelson was appointed Dean of the University of Illinois at Chicago’s (UIC) College of Engineering in July of 2008. Prior to assuming his deanship, Professor Nelson was head of the UIC Department of Computer Science. In 1991, Professor Nelson founded UIC's Artificial Intelligence Laboratory, which specializes in applied intelligence systems projects in fields such as transportation, manufacturing, bioinformatics and e-mail spam countermeasures. Professor Nelson has published over 80 scientific peer reviewed papers and has been the principal investigator on over $30 million in research grants and contracts on issues of importance such as computer-enhanced transportation systems, manufacturing, design optimization and bioinformatics. These projects have been funded by organizations such as the National Institutes of Health, the National Science Foundation, the National Academy of Sciences, the U.S. Department of Transportation and Motorola. In 1994-95, his laboratory, sponsored by the Illinois Department of Transportation, developed the first real-time traffic congestion map on the World Wide Web, which now receives over 100 million hits per year. Professor Nelson is also currently serving as principal dean for the UIC Innovation Center, a collaborative effort between the UIC Colleges of Architecture, Design and the Arts; Business Administration; Medicine and Engineering.

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Fazle Shahnawaz Muhibul Karim University of Illinois, Chicago

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Fazle Karim is an aspiring data scientist who is completing his PhD in the Mechanical and Industrial Engineering department at University of Illinois at Chicago. He received his BSIE in 2012 from the University of Illinois at Urbana Champaign. He is currently the lead data scientist at PROMINENT lab, the leading process mining research facility at the university. He has taught courses in Probability & Statistic in Engineering, Work Productivity Analysis, Quality Control & Reliability, and Safety Engineering. His research interest includes education data mining, health care data mining, and time series analysis.

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Abstract

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.

Darabi, H., & Douzali, E., & Harford, S. T., & Nelson, P. C., & Karim, F. S. M. (2017, June), Beyond Grade Point Average and Standardized Testing: Incorporating a Socio-Economic Factor in Admissions to Support Minority Success Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/27657

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2017 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015