A Quantitative Longitudinal Study Using Astin's I-E-O Model to Predict College STEM versus Non-STEM Major Choice among Women

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Title: A Quantitative Longitudinal Study Using Astin's I-E-O Model to Predict College STEM versus Non-STEM Major Choice among Women
Language: English
Authors: Berchiolli, Patricia
Source: ProQuest LLC. 2019Ph.D. Dissertation, Florida Atlantic University.
Availability: ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Peer Reviewed: N
Page Count: 123
Publication Date: 2019
Document Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education
Postsecondary Education
High Schools
Secondary Education
Descriptors: Majors (Students), Gender Differences, STEM Education, College Freshmen, College Seniors, Decision Making, Females, Student Characteristics, Background, Student Experience, Predictor Variables, Student Satisfaction, Courses, College Science, College Mathematics, Grade Point Average, High School Students, Scores, Problem Solving, Mathematics Skills, Student Research, College Entrance Examinations
Assessment and Survey Identifiers: SAT (College Admission Test)
Abstract: This quantitative longitudinal study sought to highlight the difference between the proportion of men and women who planned to pursue a STEM major in the fields of mathematics, natural sciences, engineering, and computer and information sciences as freshmen, as well as to determine the proportion of men and women who changed their major choice by their senior year. In addition, the researcher sought to identify women students" unique background characteristics and college experiences that have taken place over the course of their undergraduate college career that may have predicted their declared major choice (STEM versus non-STEM) as seniors. A review of the literature, along with Astin"s Involvement Theory, encouraged the hypothesis that college experiences influence women"s college major choice: STEM versus non-STEM. Secondary data obtained from the Cooperative Institutional Research Program at the higher Education Research Institute was used. The sample was delimitated to include only full-time undergraduate students who were graduating in 2012 or 2013. Five research questions were addressed in this study. Astin"s (1993) Input-Environment-Outcome Model was used as a conceptual framework. Descriptive (frequencies and percentages) and inferential (chi-square test and discriminant analysis) statistics were used to analyze the data. The results found a statistically significant difference between the proportion of men and women who planned to pursue a STEM major as freshmen as well as the proportion of men and women who changed their major choice from STEM to non-STEM. Discriminant analysis was used to predict group membership of STEM versus non-STEM major choice among women. It was found that many variables had an impact on predicting STEM group membership among women: satisfaction with college math and science courses, high school GPA, SAT score, high self-ratings of problem-solving skills and mathematical ability, and participating in undergraduate research. There were also variables that had a greater ability of predicting non-STEM group membership. The findings from this study will hopefully inform policy and practice. Implications for policy, practice, and future research are included. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
Abstractor: As Provided
Entry Date: 2020
Access URL: https://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:13810706
Accession Number: ED601738
Database: ERIC
FullText Text:
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PubType: Dissertation/ Thesis
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  Data: A Quantitative Longitudinal Study Using Astin's I-E-O Model to Predict College STEM versus Non-STEM Major Choice among Women
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  Data: This quantitative longitudinal study sought to highlight the difference between the proportion of men and women who planned to pursue a STEM major in the fields of mathematics, natural sciences, engineering, and computer and information sciences as freshmen, as well as to determine the proportion of men and women who changed their major choice by their senior year. In addition, the researcher sought to identify women students" unique background characteristics and college experiences that have taken place over the course of their undergraduate college career that may have predicted their declared major choice (STEM versus non-STEM) as seniors. A review of the literature, along with Astin"s Involvement Theory, encouraged the hypothesis that college experiences influence women"s college major choice: STEM versus non-STEM. Secondary data obtained from the Cooperative Institutional Research Program at the higher Education Research Institute was used. The sample was delimitated to include only full-time undergraduate students who were graduating in 2012 or 2013. Five research questions were addressed in this study. Astin"s (1993) Input-Environment-Outcome Model was used as a conceptual framework. Descriptive (frequencies and percentages) and inferential (chi-square test and discriminant analysis) statistics were used to analyze the data. The results found a statistically significant difference between the proportion of men and women who planned to pursue a STEM major as freshmen as well as the proportion of men and women who changed their major choice from STEM to non-STEM. Discriminant analysis was used to predict group membership of STEM versus non-STEM major choice among women. It was found that many variables had an impact on predicting STEM group membership among women: satisfaction with college math and science courses, high school GPA, SAT score, high self-ratings of problem-solving skills and mathematical ability, and participating in undergraduate research. There were also variables that had a greater ability of predicting non-STEM group membership. The findings from this study will hopefully inform policy and practice. Implications for policy, practice, and future research are included. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 123
    Subjects:
      – SubjectFull: Majors (Students)
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: STEM Education
        Type: general
      – SubjectFull: College Freshmen
        Type: general
      – SubjectFull: College Seniors
        Type: general
      – SubjectFull: Decision Making
        Type: general
      – SubjectFull: Females
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Background
        Type: general
      – SubjectFull: Student Experience
        Type: general
      – SubjectFull: Predictor Variables
        Type: general
      – SubjectFull: Student Satisfaction
        Type: general
      – SubjectFull: Courses
        Type: general
      – SubjectFull: College Science
        Type: general
      – SubjectFull: College Mathematics
        Type: general
      – SubjectFull: Grade Point Average
        Type: general
      – SubjectFull: High School Students
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Problem Solving
        Type: general
      – SubjectFull: Mathematics Skills
        Type: general
      – SubjectFull: Student Research
        Type: general
      – SubjectFull: College Entrance Examinations
        Type: general
      – SubjectFull: SAT (College Admission Test)
        Type: general
    Titles:
      – TitleFull: A Quantitative Longitudinal Study Using Astin's I-E-O Model to Predict College STEM versus Non-STEM Major Choice among Women
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              Y: 2019
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