Asee peer logo

Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups

Download Paper |

Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Developing Young MINDS in Engineering, Part II

Tagged Division

Minorities in Engineering

Page Count

13

Page Numbers

25.711.1 - 25.711.13

DOI

10.18260/1-2--21468

Permanent URL

https://peer.asee.org/21468

Download Count

233

Request a correction

Paper Authors

biography

Ruba Alkhasawneh Virginia Commonwealth University

visit author page

Ruba Alkhasawneh earned her Ph.D. in engineering from Virginia Commonwealth University in 2011. She received her B.S. and M.S. in computer engineering from Jordan University of Science and Technology and Yarmouk University, respectively. Her research interests in the engineering education field focus on modeling first-year student academic success and retention in STEM disciplines. Also, she has interests in problem-based learning, increasing diversity in STEM fields, and evaluating engineering programs and activities which are designed to improve student learning outcomes.

visit author page

author page

Rosalyn Hobson Hargraves Virginia Commonwealth University

Download Paper |

Abstract

TOPIC: New research and trends related to underrepresented minorities in engineering. Identifying significant features that impact URM students academic success and retention upmost using qualitative methodologies: focus groups Ruba Alkhasanwneh Rosalyn Hobson Virginia Commonwealth University Virginia Commonwealth University alkhasawnera@mymail.vcu.edu rhobson@vcu.eduIncreasing student retention and academic success in STEM disciplines have been amongthe goals of higher education institutions for a long time. Significant efforts have beenmade to predict student retention in higher education and to understand the process ofdropping out of college [1-3] by developing theoretical models of student retention usingassociated factors. Seymour [4] reported that both enrollment and retention rates inSTEM disciplines have declined. More specifically, Tinto [5] reported that freshmen yearhas the highest dropout rate especially in the first six weeks of the first semester.Statistics show that students of color have higher attrition rates compared with othergroups, although this trend has been decreasing over the past twenty years [6-8]. Thesegroups tend to enroll in STEM majors in small numbers and leave in higher numbers [9-10].The purpose of this research is to develop a hybrid framework to model first year studentacademic success and retention for URM comprising African Americans, HispanicAmericans, and Native Americans. This model was built by incorporating quantitative(genetic algorithm) and qualitative (focus groups) results. Obtaining an adequate 1understanding of URM student retention and academic success and modeling theirperformance and retention during freshman year, serves institutions by identifying at-riskstudents in STEM fields. This paper will focus on highlighting the qualitative part of thisresearch.The focus groups participants were former Summer Transition Program (STP) studentsover a three year period of time, 2008-2010. The STP is a residential four week programfor entering URM freshmen targeting fourteen STEM majors including engineering,natural sciences, and mathematical sciences. Focus groups were designed to elicitresponses from participants for identifying factors that affect their retention the most andprovide more knowledge about their first year experiences, academically and socially.The analysis approach used is content analysis which is a very effective method inanalyzing data in textual context. This approach is used to describe, analyze, andsummarize patterns and trends observed from the collected data [11].Major findings of this research were that URM students come to college with high self-motivation and commitment to graduate with a degree in STEM. Once college starts,many factors impact student self-motivation either positively or negatively. Empoweringa student with self-motivation has a great influence on the student’s decision to continuein STEM fields. In addition, high school mathematics and science preparation, race,gender, and freshman year grades are strong predictors of student academic success andretention. Results obtained were comparable with results obtained using the geneticalgorithm, however, it was a challenge to incorporate both results and develop anunderstandable accurate model that utilizes all relevant student features. 2References:[1] V. Tinto, "Dropout from higher education: A theoretical synthesis of recent research," Review of educational research, vol. 45, p. 89, 1975.[2] W. Spady, "Dropouts from higher education: An interdisciplinary review and synthesis," Interchange, vol. 1, pp. 64-85, 1970.[3] J. Bean, "Dropouts and turnover: The synthesis and test of a causal model ofstudent attrition," Research in Higher Education, vol. 12, pp. 155-187, 1980.[4] E. Seymour, "Tracking the processes of change in US undergraduate education in science, mathematics, engineering, and technology," Science Education, vol. 86, pp. 79-105, 2002.[5] V. Tinto, "Stages of student departure: Reflections on the longitudinal characterof student leaving," The Journal of Higher Education, vol. 59, pp. 438-455, 1988.[6] M. Besterfield-Sacre, et al., "Characteristics of Freshman Engineering Students: Models for Determing Student Attrition in Engineering," JOURNAL OF ENGINEERING EDUCATION-WASHINGTON-, vol. 86, pp. 139-150, 1997.[7] T. Mitchell and A. Daniel, "A Year-Long Entry-Level College Course Sequence for Enhancing Engineering Student Success."[8] L. Fleming, et al., "AC 2008-1039: ENGINEERING STUDENTS DEFINE DIVERSITY: AN UNCOMMON THREAD," 2008.[9] J. Urban, et al., "Minority engineering program computer basics with a vision," 2002, pp. S3C1-5.[10] R. Hobson and R. Alkhasawneh, "SUMMER TRANSITION PROGRAM: AMODEL FOR IMPACTING FIRST-YEAR RETENTION RATES FORUNDERREPRESENTED GROUPS," in ASEE conference & exposition, Austin, TX,2009.[11] S. Stemler. (2001, An overview of content analysis. Practical Assessment, Research & Evaluation. Available: http://PAREonline.net/getvn.asp?v=7&n=17 3

Alkhasawneh, R., & Hargraves, R. H. (2012, June), Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21468

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: © 2012 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