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

\bibitem{asee_peer_21468}
  Alkhasawneh, R., \& Hargraves, R. H. (2012, June), \emph{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

Ruba Alkhasawneh and Rosalyn Hobson Hargraves.  "Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups".  2012 ASEE Annual Conference & Exposition, San Antonio, Texas, 2012, June.  ASEE Conferences, 2012.  https://strategy.asee.org/21468 Internet.  17 Jul, 2024

\bibitem{asee_peer_21468}
  Ruba Alkhasawneh and Rosalyn Hobson Hargraves.
  "Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups".
  \emph{2012 ASEE Annual Conference \& Exposition, San Antonio, Texas, 2012, June}.
  ASEE Conferences, 2012.
  https://strategy.asee.org/21468 Internet.  17 Jul, 2024

@INPROCEEDINGS{asee_peer_21468
author = "Ruba Alkhasawneh and Rosalyn Hobson Hargraves"
title = "Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups"
booktitle = "2012 ASEE Annual Conference \& Exposition"
year = "2012"
month = "June"
address = "San Antonio, Texas"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/21468}
number = {10.18260/1-2--21468}
}

TY  - CPAPER
AB  - 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
AU  - Ruba Alkhasawneh
AU  - Rosalyn Hobson Hargraves
CY  - San Antonio, Texas
DA  - 2012/06/10
PB  - ASEE Conferences
TI  - Identifying Significant Features that Impact URM Student Academic Success and Retention Upmost Using Qualitative Methodologies: Focus Groups
UR  - https://strategy.asee.org/21468
DO  - 10.18260/1-2--21468
ER  -