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Predicting Undergraduate Retention in STEM Majors Based on Demographics, Math Ability, and Career Development Factors

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Date Issued:
2017
Abstract/Description:
Science, technology, engineering, and math (STEM) fields are currently facing a crisis with respect to filling jobs with qualified workers (NSF, 2013; NAS, 2011). While advancements in these industries have translated into job growth, post-secondary declaration and retention rates within STEM majors lag behind industry needs (Carnevale et al., 2011; Chen, 2013; Koenig et al., 2012). Although researchers previously investigated demographic variables and math-related variables in the context of STEM retention (Beasley (&) Fischer, 2012; CollegeBoard, 2012; Cundiff et al., 2013; Gayles (&) Ampaw, 2014; Le et al., 2014; Nosek (&) Smyth, 2011; Riegle-Crumb (&) King, 2010), the need exists for additional research examining the impact of career-related variables (Belser et al., 2017; Folsom et al., 2004; Parks et al., 2012; Reardon et al., 2015). Additionally, prior STEM retention research primarily focused on students with declared STEM majors, as opposed to undeclared students considering STEM majors. In the present study, the researcher sought to determine the degree to which demographic variables (gender and ethnicity), math ability variables (SAT Math scores and Math Placement Test--Algebra scores), and career development related variables (initial major, STEM course participation, and Career Thoughts Inventory [CTI] change scores) could predict undergraduate retention in STEM for participants in a STEM recruitment and retention program. Using binary logistic regression, the researcher found that initially having a declared STEM major was the best predictor of STEM retention. Higher scores on math variables consistently predicted higher odds of STEM success, and the data revealed higher odds of STEM retention for ethnic minority students. Gender only showed to be a significant predictor of STEM attrition with the undecided students with first-to-third year retention. Finally, larger decreases in CTI scores predicted increased odds of STEM retention. Implications from the findings relate to a variety of professionals from higher education, counseling, and research. The findings provide guidance and new perspectives on variables associated with better rates of STEM retention, and as such, inform STEM initiatives targeting undergraduate STEM recruitment and retention.
Title: Predicting Undergraduate Retention in STEM Majors Based on Demographics, Math Ability, and Career Development Factors.
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Name(s): Belser, Christopher, Author
Shillingford-Butler, Ann, Committee Chair
Van Horn, Stacy, Committee Member
Taylor, Dalena, Committee Member
Daire, Andrew, Committee Member
Witta, Eleanor, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2017
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Science, technology, engineering, and math (STEM) fields are currently facing a crisis with respect to filling jobs with qualified workers (NSF, 2013; NAS, 2011). While advancements in these industries have translated into job growth, post-secondary declaration and retention rates within STEM majors lag behind industry needs (Carnevale et al., 2011; Chen, 2013; Koenig et al., 2012). Although researchers previously investigated demographic variables and math-related variables in the context of STEM retention (Beasley (&) Fischer, 2012; CollegeBoard, 2012; Cundiff et al., 2013; Gayles (&) Ampaw, 2014; Le et al., 2014; Nosek (&) Smyth, 2011; Riegle-Crumb (&) King, 2010), the need exists for additional research examining the impact of career-related variables (Belser et al., 2017; Folsom et al., 2004; Parks et al., 2012; Reardon et al., 2015). Additionally, prior STEM retention research primarily focused on students with declared STEM majors, as opposed to undeclared students considering STEM majors. In the present study, the researcher sought to determine the degree to which demographic variables (gender and ethnicity), math ability variables (SAT Math scores and Math Placement Test--Algebra scores), and career development related variables (initial major, STEM course participation, and Career Thoughts Inventory [CTI] change scores) could predict undergraduate retention in STEM for participants in a STEM recruitment and retention program. Using binary logistic regression, the researcher found that initially having a declared STEM major was the best predictor of STEM retention. Higher scores on math variables consistently predicted higher odds of STEM success, and the data revealed higher odds of STEM retention for ethnic minority students. Gender only showed to be a significant predictor of STEM attrition with the undecided students with first-to-third year retention. Finally, larger decreases in CTI scores predicted increased odds of STEM retention. Implications from the findings relate to a variety of professionals from higher education, counseling, and research. The findings provide guidance and new perspectives on variables associated with better rates of STEM retention, and as such, inform STEM initiatives targeting undergraduate STEM recruitment and retention.
Identifier: CFE0006565 (IID), ucf:51326 (fedora)
Note(s): 2017-05-01
Ph.D.
Education and Human Performance, Dean's Office EDUC
Doctoral
This record was generated from author submitted information.
Subject(s): Career Development -- Undergraduate Retention -- STEM Initiatives -- Academic Persistence -- Logistic Regression
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0006565
Restrictions on Access: public 2017-05-15
Host Institution: UCF

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