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FACTORS INFLUENCING FEMALE PERSISTENCE IN STEM MAJORS AND CAREERS

FACTORS INFLUENCING FEMALE PERSISTENCE IN STEM MAJORS AND CAREERS. PHYLLIS BERNICE OPARE OLD DOMINION UNIVERSITY – VIRGINIA. Research Questions. What social factors cause women in STEM majors to switch to other majors?

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FACTORS INFLUENCING FEMALE PERSISTENCE IN STEM MAJORS AND CAREERS

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  1. FACTORS INFLUENCING FEMALE PERSISTENCE IN STEM MAJORS AND CAREERS PHYLLIS BERNICE OPARE OLD DOMINION UNIVERSITY – VIRGINIA

  2. Research Questions • What social factors cause women in STEM majors to switch to other majors? • What academic factors cause women in STEM majors to switch to other majors? • What factors enable some women to persist and progress in STEM majors and careers when many others do not?

  3. Background and significance The number of women graduating with a BS in STEM is increasing. Generally women earn more than half of all the BS degrees awarded, but less than 40% in the physical sciences in the U.S. The numbers vary drastically from one field to another and from institution to institution. • In the year 2000 women represented: • 18% of graduates in engineering • 37% in the physical sciences, • 34% of mathematical/computer science graduates, and • 26% of chemistry graduates.

  4. Women in STEM positions Women held only • 9% of engineering positions, • 22% of physical science positions and about • 20% of all science, math and engineering positions in the U.S.

  5. Women in STEM faculty positions • In 2003 women held about 28% of all full-time science and engineering faculty positions — representing 18% of full professors, 31% of associate professors and 40% of assistant professors. • Again there are drastic variation in the percentages depending on the type of institution and the ranking level of the institution. • In the top 50 STEM departments (NSF) the percentage of female full professors ranged from 3% to 15%, well below the national averages (Nelson, 2007).

  6. The Problem Is Not Simply The Pipeline • Women earned more than 30% of doctorates in the social sciences, and 20% in the life sciences, but made up only 15.4% and 14.8% of full professors in those fields respectively” (Beyond Bias and Barriers, 2006, p.2).

  7. Another study found that; • 94% of full professors in science and engineering were white; 90% were male, • 91% of the full professors at research universities were white; 75% were male, • 87% of the full-time faculty members in the United States were white; 64% were male, • Only 5% of the full professors in the U.S. were black, Hispanic, or Native American, and • The gap between the percentage of tenured men and the percentage of tenured women had not changed in 30 years (Trower, & Chait, 2002, p. 34)

  8. Reasons for female underrepresentation in STEM • SOCIAL FACTORS • Biological differences between males and females, particularly brain sizes, • The image of STEM subjects as being masculine concerned with things rather than people, particularly engineering, computing and physics.

  9. The stress and isolation of being in a minority. • Negative attitudes of male peers, lecturers and other staff, as well as family and friends. • Concerns about combining a science, engineering, and technology career with having a family

  10. Girls’ poor attitudes toward STEM courses, • Their lack of positive experiences with STEM in childhood, • The lack of role models, in the form of female scientists and engineers,

  11. ACADEMIC FACTORS • Narrow course content, • Didactic teaching approaches, • Lack of opportunities for cooperative or interactive learning, • Emphasis on individual competition, • Girls’ lack of academic preparation for STEM,

  12. Irrelevant science curricula, • Unfavorable STEM pedagogy, • Inadequate counseling and advising, and • Cultural pressures • (Blickenstaff, 2005; Campbell, 1992; Cronin & Roger, 1999, p. 3; Murphy, 2007).

  13. Some of these have been proven unfounded, particularly concerning the differences in male and female brain sizes. • Studies of brain structure and function, of hormonal modulation of performance, of human cognitive development, and of human evolution provide no significant evidence for biological differences between men and women in performing science and mathematics that can account for the lower representation of women in these fields. The dramatic increase in the number of women science and engineering PhDs over the last 30 years clearly refutes long-standing myths that women innately or inherently lack the qualities needed for success; obviously, no changes in innate abilities could occur in so short a time (Beyond Bias, 2005. p. 214-215).

  14. The report Beyond Bias and Barriers also found that: • Women have the ability and drive to succeed in science and engineering, • Women who are interested in science and engineering careers are lost at every educational transition, • Women are very likely to face discrimination in every field of science and engineering

  15. A substantial body of evidence establishes that most people—men and women—hold implicit biases, • Evaluation criteria contain arbitrary and subjective components that disadvantage women, Academic organizational structures and rules contribute significantly to the underuse of women in academic science and engineering, and • The consequences of not acting will be detrimental to the nation’s competitiveness (Beyond Bias, 2007, p. 2-4).

  16. PILOT STUDY Methodology The foundational paradigm social constructivism and the theoretical tradition Grounded Theory was used in the study (Patton, 2002; Strauss & Corbin, 1998). • The study sought to; • Gather knowledge about an existing phenomenon • Uncover factors jointly between researcher and participants. • Give females in STEM voice to express how they conceptualize factors that has helped them to succeed and persist.

  17. Sample • 6 female graduate students enrolled in the following STEM majors were purposefully selected; physics, chemistry, computer engineering, mechanical engineering, and electrical engineering.

  18. Instrument and Data Analysis • An interview guide was generated with open ended questions that encouraged participants to talk about their experiences. • All participants were interviewed, while 4 took part in a focus group discussion. • These sessions were tape recorded.

  19. After the audio files were transcribed an open coding approach was used to identify themes in the responses. • This process was repeated for each individual interview and focus group report. • In vivo codes and selective sampling of the transcripts were conducted until saturation was attained.

  20. Limitation of Method • Small sample size from one institution limits the generalizabilty of findings • Self selected sample may be significantly different from non-participants • There is always the likelihood that participants will give socially acceptable responses in interview and focus group discussions.

  21. Factors • Self-efficacy • a person’s knowledge of self, and ability to make personal decisions and stand by them, as well as the ability to have clear goals in life. • Or a person’s beliefs in their ability to perform successfully in a given task or behavior (Bandura, 1989). • Science-efficacy • an individual’s affinity for science and science related subjects, as well as the achievement in science. • Parental/family support • Active parental support was cited by most participants as being important in their decision to chose a STEM major.

  22. Faculty and collegiate support • Enabling academic environment • Honor and prestige associated with STEM • In some cultures certain professions have more prestige and so families in the higher socioeconomic stratum tend to want their children to take up those professions. • Patriotism • Choosing a course of study because it will be beneficial to one’s country or society.

  23. References • Bandura, A. (1989). Social cognitive theory. In R. Vasta (Ed.), Annals of child development. Six theories of child development, 6, 1-60. • Blickenstaff, J. C. (2005). Women and science careers: Leaky pipeline or gender filter? Gender and Education, 17(4), 369-386. • Campbell, P. S. J. (1997). Uniformed but interested: Findings of a national survey on gender equity in preservice teacher education. Journal of Teacher Education, 48(1), 69-75. • Cronin, C., & Roger, A. (1999). Theorizing progress: Women in science, engineering, and technology in higher education. Journal of Research in Science Teaching, 36(6), 637-661. • Murphy, M. C., Steele, C. M., & Gross, J. J. (2007). Signaling Threat: How Situational Cues Affect Women in Math, Science, and Engineering Settings. Psychological Science, 18 (10), 879-885. • National Academies Committee on Science, Engineering, and Public Policy, Committee on Maximizing the Potential of Women in Academic Science and Engineering (2007). Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering, Washington, DC: National Academies Press • Nelson, D. J. (2007). A National Analysis of Diversity in Science and Engineering Faculties at Research Universities. • Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage Publication. • Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Thousand Oaks, CA: Sage Publication. • Trower, C. A., & Chait, R. P. (2002). Faculty Diversity. Harvard Magazine

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