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The role of occupational values and social support in career choice

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Title:
The role of occupational values and social support in career choice an emphasis on women in science
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Book
Language:
English
Creator:
Meikle, Heather
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
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Subjects

Subjects / Keywords:
Gender
Decision-making
Vocational development
Stem
Education
Dissertations, Academic -- Psychology -- Masters -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: The purpose of this study was to determine how occupational values and social support for career pursuits influenced career choice, with a specific focus on women in science, technology, engineering, or mathematics (STEM). A sample of 62 college graduates participated in telephone interviews that addressed gender differences in seven occupational values and three sources of social support. Results showed that differences in occupational values differ by both gender and between individuals in STEM and non-STEM careers. The strength of STEM values better predicted a career in STEM than did gender. Finally, women in STEM received the least amount of social support for their career pursuits. These results underscore the need to encourage women's interest in STEM, and develop interventions for career counselors that specifically address the unique needs of women in non-traditional careers.
Thesis:
Thesis (M.A.)--University of South Florida, 2008.
Bibliography:
Includes bibliographical references.
System Details:
Mode of access: World Wide Web.
System Details:
System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Heather Meikle.
General Note:
Title from PDF of title page.
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Document formatted into pages; contains 68 pages.

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University of South Florida
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aleph - 002001179
oclc - 319692184
usfldc doi - E14-SFE0002621
usfldc handle - e14.2621
System ID:
SFS0026938:00001


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ABSTRACT: The purpose of this study was to determine how occupational values and social support for career pursuits influenced career choice, with a specific focus on women in science, technology, engineering, or mathematics (STEM). A sample of 62 college graduates participated in telephone interviews that addressed gender differences in seven occupational values and three sources of social support. Results showed that differences in occupational values differ by both gender and between individuals in STEM and non-STEM careers. The strength of STEM values better predicted a career in STEM than did gender. Finally, women in STEM received the least amount of social support for their career pursuits. These results underscore the need to encourage women's interest in STEM, and develop interventions for career counselors that specifically address the unique needs of women in non-traditional careers.
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The Role of Occupational Values and Support in Career Choice: An Emphasis on Women in Science by Heather Meikle A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts Department of Psychology College of Arts and Sciences University of South Florida Major Professor: Walter Borman, Ph.D. Tammy D. Allen, Ph.D. Douglas Rohrer, Ph.D. Date of Approval: May 1, 2008 Keywords: gender, decision-making, voca tional development, stem, education Copyright 2008 Heather Meikle

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i Table of Contents List of Tables ................................................................................................................ ..... iii Abstract .................................................................................................................. iv Introduction ..............................................................................................................1 Women in science, technology, engineering and mathematics ...............................2 Occupational choice .................................................................................................4 Theories of career choice .......................................................................................10 Brown’s value-based model of career choice ................................................10 The gende r-socialization approach to career choice ......................................11 Occupational values ...............................................................................................13 Social support of career choice ..............................................................................17 Hypotheses .............................................................................................................19 Relationship to the ROLE grant .............................................................................20 Method ........................................................................................................................ .......22 Sample identification .............................................................................................22 Participants .............................................................................................................23 Survey development ...............................................................................................24 Variables ................................................................................................................24 Occupational values ........................................................................................24 Career choice support .....................................................................................25

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ii Field of pursuit .................................................................................................25 Survey Administration ...........................................................................................26 Results ....................................................................................................................... .........28 Discussion .................................................................................................................... ......35 Limitations of the study and imp lications for future research ...............................38 List of References ............................................................................................................ ..41 Appendix A: Careers and Educational Experiences Survey Protocol ..............................45 Appendix B: Westat Ad ministration Report ......................................................................57

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iii List of Tables Table 1. Means and Standard Deviations of Values by Gender and Degree .....................29 Table 2. Means and Standard Deviations of Social Support by Gender and Degree ........30 Table 3. Means, Standard Deviations and Intercorrelations of Sources of Support ..........31 Table 4. Means, Standard Deviations and In tercorrelations of O ccupational Values .......32 Table 5. Regression Analyses of Occupational Values and Gender ..................................34

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iv The role of occupational values and social support in career choice: An emphasis on women in science Heather Meikle ABSTRACT The purpose of this study was to determine how occupational values and social support for career pursuits influenced career choice, with a specific focus on women in science, technology, engineering, or mathem atics (STEM). A sample of 62 college graduates participated in telephone interviews that addressed gender differences in seven occupational values and three sources of soci al support. Results showed that differences in occupational values differ by both gender and between individuals in STEM and nonSTEM careers. The strength of STEM values better predicted a career in STEM than did gender. Finally, women in STEM received th e least amount of soci al support for their career pursuits. These results underscore the need to encourage wo men’s interest in STEM, and develop interventi ons for career counsel ors that specifically address the unique needs of women in non-traditional careers.

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1 Introduction Over the last quarter century, there has been dramatic growth in women’s labor force participation and with it a rise in research focusi ng on women’s career choices and vocational behavior. This expanding body of lite rature reveals a couple of themes about women’s roles in the workforce. Many occupati ons today continue to be sex-stereotyped. Some are commonly characterized as historic ally male dominated, such as electrical engineering, mathematics, and chemistry, wher eas others tend to be viewed as more appropriate for women, like administrative positions and nursing. Ideas about gendertyped occupations can be found in a range of places, from images in textbooks of male scientists to antiquated notions about work expressed by a family member from an older generation. In fact, these occupational stereot ypes are so pervasive in our society that they are even learned by children as young as three years old (Stockard & McGee, 1990). Internalizing these beliefs about gender-typ ed jobs at such a young age makes it that much more difficult to expand a young adult’s vi ew of their own career potential twenty years later. Although there is evidence that these stereo types may be declining among college students (White, Kruczek, Br own, & White, 1989), these out-dated conceptualizations of gender-t yped jobs continue to play an important role in the development of many career pathways. Women tend to gravitate toward occupa tions that provide an opportunity to interact in a social environment and those th at play useful roles in society. This can

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2 include jobs in fields such as healthcare or social serv ices. In fact, when women in traditionally male-dominated fields were asked about their career plans, many reported they were more likely to consider changing to a career in medicine or law because it would allow them to give back to the commun ity in a way that their current field of study would not (Lightbody, Siann, Tait, & Walsh, 1997). Moreover, the occupations held mostly by women (offering the opportunity to gi ve back or to make a contribution) are also often in the service sector. These jobs often provide lower pay, offer little prestige, and require only modest training and educati onal preparation compared to most male dominated occupations (Betz & Fitzgerald, 1987). Women in Science, Technol ogy, Engineering, and Math Although women’s presence in the workfor ce continues to rise, the expansion is unevenly distributed across o ccupations. Women continue to be under-represented in most science-related fields; especially t hose termed the “hard” sciences, such as chemistry and physics. A recent assessment of the science and engineering (S&E) workforce (NSF, 2007) revealed that in 2003, while women made up approximately half of the population and 47% of the college-degr eed workforce, they occupied only 24% of the science and engineering jobs. Within thes e fields, the largest percentage of women can be found in the biological/life sciences (4 3%). Women are well represented in this partly because it serves as a pi peline to careers in the healthcare, an industry that tends to be popular among women. The smallest pe rcentage of women employed in S&E occupations can be found in engineering (1 1%). This is due mostly to the vast overrepresentation of men in th e electrical and mechanical engineering specialties. This under-representation can also be found at the po stsecondary education level in the choice

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3 of college major (Astin, Korn, Sax, & Mahoney, 1994), indicating that these disparities in the workforce are being developed long before entry into the job market occurs. For example, only 14% of female freshman at f our-year institutions reported intentions of majoring in any S&E field, compared to 34% of their male counterpart (NSF, 2007). In 2005, women made up only 17% of all students en rolled in engineering programs at fouryear institutions and received 19% of the bachelor’s degrees awarded for engineering. However, the number of engineering degrees conferred to women has increased by four percentage points in the past fifteen year s, providing evidence that slowly, women’s participation in engi neering is growing. It is vital to attract and maintain women’s interest in science, technology, engineering and mathematics (STEM) education and careers; it is in these fields that there are the fastest growing employment opportunities (NSB, 2003). Employment in STEM fields is projected to increase three times faster than employment in all other occupations by 2010 (Fassinger & Asay, 2006). In fact, the National Science Board (2000) identified the supply of scientists, engi neers, and science teachers as one of the top 10 priorities of the early 21st century. This increase in oppor tunity is coupled with a decreasing number of white men in the STEM workforce, who traditionally have constituted most of the STEM professionals. Th is decrease is partly due to large numbers of retirees and decreased nu mbers of white men currently entering STEM fields. One example of this trend in hiring can be found among academic STEM positions. The percentage of white males hired for these pos itions dropped from 80% in the early 1970s to 40% in 1999. It is reasonable to expect that many of the resulting employment gaps would be filled with women, as their partic ipation in the overall labor force has seen

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4 dramatic increases. Therefore, we are faced w ith the need to enhance student interest and retention in STEM programs, and to guide more of our newly graduated workforce, especially women, towards those fields. Increa sing women’s participation in these fields can promote a healthy economy by ensuri ng a diverse and well-qualified STEM workforce. Considering the unique experiences of women in contemporary society, the study of women’s careers deserves special attention. Hi storically, much of women’s career behavior has been interpreted using an ar guably male perspective (Gallos, 1989; Powell & Mainiero, 1992). For example, many theori es of career choice and development are based on masculine models of identity formation (Brown & Brooks, 1990). There is much debate over the issue of describing a nd interpreting women’s career behavior using a male framework, as these models may not accurately reflect the processes that women undertake to select and bu ild their career. Fo r example, Gutek and Larwood (1987) believe that current theories of careers and career development do not fit the experiences of women due to the vast differences in socialization, opportuniti es and barriers women currently face in society. However, others believe that women and men share a very similar career development pr ocess (Fitzgerald & Crites, 1980). Although an agreement has yet to be reached on the efficacy of applyi ng traditional theories of career choice and development to women, they continue to pr ovide a necessary framework for examining individuals’ careers. Occupational Choice There are four themes of occupational choi ce that can help explain the processes underlying how people select an occupation. Car eer choice can be characterized as 1) a

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5 matching process, 2) a developmental proces s, 3) a decision-making task, and 4) and a product of social and cultur al influences (Greenhaus, Callanan, & Godshalk, 2000). The first way to conceptualize career choice is by viewing it as a matching process. Individuals each have their own unique set of needs, abil ities and interests. According to the matching explanation, an i ndividual assesses these needs, abilities and interests, develops one or more career goals, collects information about potential occupations, and decides on one they feel to be compatible. While this is rarely carried out in such an orderly manner, the process of reflecting on abilities and interests before selecting an occupation can be a valuable exercise. Proponents of the occupational choice as matching process include John Holland and Donald Super. Holland’s work center s around the idea th at people have a combination of six basic traits which can be matched to occupations based on their associated personality characteristics (Ho lland, 1966). Individuals’ personality can be classified as Realistic, Inve stigative, Artistic, Social, Enterprising, and Conventional. Each of these personality types can be ch aracterized by a common set of interests and preferences. For example, Investigative pe rsonalities are thought to be analytical, cautious and independent, and are suited to occupations such as an economist or engineer. Enterprising personalities tend to be ambitious, energetic and self-assured, and excel in careers such as real estate sales or law. Like people, occupational environments can also be classified into the same six categories. Holland believed that people will search for and select an occupation th at matches their personality type. Super’s work also represents the oc cupational choice as a matching process. Super (1963) believed that a ke y variable in selecting an occupation was the individual’s

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6 self concept, or the combination of attri butes they possess, in cluding their abilities, interests and needs. Occupations are chosen based in part by how we ll they fit into the individual’s self-concept. For example, a st udent who believes he is to be understanding, empathetic and patient may select a career as a social worker, an occupation which would require the same set of attributes. The second way to conceptualize occ upational choice is as a developmental process, one that occurs over a life span. In fact, an occupational decision can be thought of as a long series of small decisions, all of which steer the indivi dual towards one career or another. Many small decisions can help shap e the interests and skills of an individual. Consider the potential engineer who makes th e decision to enter a science fair in middle school, who joins the physics club in high school, and who works summers at a civil engineering firm. Each of these small decisi ons allowed the exploration of new ideas and challenges, and helped build the foundation of knowledge and confidence needed to select a career in engineering. In this ex ample, the process started during middle school, but these developmental experiences can start at any time. It takes time and experience for talents and interests to emerge. Potential occupations are pursued and replaced as new information becomes available and skills are honed. In this way, career choice is essentially a gradual, unfolding process. Super describes this process as occurring in five stages: growth, exploration, establishment, maintenance, and disengagement (Super, Savickas & Super, 1996). The growth stage, ge nerally experienced during the time before adolescence, is marked by concern for the future, increasing personal control over one’s own life, placing value on scholastic achie vement, and developing good work habits. The next stage is exploration, beginning in adolescence and c ontinuing into early adulthood.

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7 During this time, individuals begin to formulate their self-concept and develop a vocational identity. An occupation or field of study is selected and the appropriate educational and vocational choices are implem ented. The exploration stage is of most relevance to the current study, as it is during this time that i ndividuals begin to crystallize their occupational values, incor porate their skills and abilitie s into a self-concept (such as the development of mathematics self-effi cacy), and make choices that build the foundation of their occupational future (suc h as choosing to enter an engineering program). The establishment phase occurs after exploration. Establishment is characterized by assimilating the orga nizational culture, exhibiting acceptable performance, and developing healthy relationships with co-workers. This is also the time during which advancement is a priorit y. Individuals generally experience the establishment phase from young adulthood to mi d-life. Approaching the next phase of career development can prompt an individual to re-evaluate their career choices (a common catalyst for the ubiquitous mid-life crisis ). If an individual is content to stay on their current path, they enter the maintenan ce phase. During this period energy is focused on updating skills and finding innovative ways to complete routine tasks. However, if individuals change organizati ons, occupations or fields, they must cycle through the exploration and establishmen t phase once again. As time in the workforce comes to a close, individuals enter the disengagement phase. During this time, responsibilities begin to wind down, and there is an emphasis on delegating tasks, mentoring others, and planning for (and ultimately beginning) retirement. The third way to conceptualize occupati onal choice is as a de cision-making task. Assuming that there are multiple career opti ons for any one individual, how does one

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8 choose from among these alternatives, and wh at are the psychologi cal processes that guide these decisions? Most ideas about car eer decision making are based on a trade-off model of decision theory, such as Vroom’s ( 1964) expectancy theory. Expectancy theory characterizes decision-making (including those decisions related to career choice) as a rational process by which a course of action is chosen based on the expected rewards and consequences. To succeed, one must have a cl ear set of desired outcomes specified in advance, and determine which outcomes or rewards are the most highly valued. An example of these expected rewards might include being cha llenged by the job and providing a sense of adventure. Then, poten tial occupations are considered and the likelihood that they will provi de the aforementioned rewards is determined. This information is combined with the likelihood th at each job is actually attainable, and a decision is made. The final choice is predicte d to be one that maximizes the expected rewards while also qualifies as an attainable career goal. For example, the individual who wants to be challenged and adventurous may choo se not to pursue a career in the FBI, a highly coveted position with fe w openings, but decide to work with the local police force instead, where there are more positions available. However, a drawback to this, as well as the matching explanation, is that decisions ma de about careers are ra rely carried out in such a rational, calculated manner. The last theme of occupational choice acknowledges that fact that there are external forces influencing an individual’s decision, and addresses the impact of these social and cultural forces. After all, career choices are not made in a vacuum! Behavior is thought of as a function of the person and the environmen t, and career decisions are no exception. Most of the research on career de velopment focuses on th e individual as the

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9 active agent in the development of career pl ans, as evidenced by the emphasis placed on goal setting, developing an awareness of skills and interests, and information seeking (Greenhaus, et. al., 200). However, as the choice-is-developmental discussion indicated, the environment a person is surrounded by can significantly shape the available options, as well as the way values and interests ar e formed. A person’s environment can include past influences, such as family of origin, pl ace of residence or soci al class, and present influences, like the current poli tical, social, and cultural climat e. Each of these factors can influence individuals’ world view and how th ey define their place in it. For example, growing up the child of an accountant is likely to expose one to a di fferent lifestyle and set of role models than growing up the ch ild of a policeman. Th e accountant’s child may grow up to value a career with a stable r outine whereas the policeman’s child may grow up wanting a new and exciting challenge each day. Scientists may encourage their children to pursue a life of education a nd learning, while entrepreneurs encourage competition and success. Parents who lived during the depression may teach their child to value job security above all else. In e ach of these family environments, many opportunities are present for these messages abou t careers and values to be internalized by the children. These messages can shape th e way various careers are considered and decided upon. However, the immediate family e nvironment is not the only force at play. The larger social and politic al environment influences th e way in which we consider different careers. For example, the economy can promote the growth of certain industries. Technological advances have spurred an infl ux of new jobs, and widened the range of opportunities for people with technical backgrounds. Our cultural environment reinforces certain work values and legitimizes certain career aspirations, in cluding the persisting

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10 ideas about gender-appropr iate career choices. While it is important that the role of environmental influences on career choice is recognized, the ability of an individual to weigh options and select an appropriate career should not be underemphasized. Essentially, the process of car eer choice, like many behavior s, can be thought of as the interaction of a person and his or her environment. Each of these themes of occupational c hoice can help to explain the processes by which these decisions are made, yet no one theme can solely account for the entire process. In reality, there are forces at work from each of the above themes that work together to guide and shape the choice process. Theories of Career Choice There are several theories that specifica lly consider the centrality of occupational values to the process of selecting a career. Brown’s valued-based model of career choice The origin of this model began with a desire to identify the factors that le ad to satisfying career choices. After a review of the literature on major models of caree r decision-making and their efficacy, Brown (1995) determined that most successful models expect outcomes to be the primary basis of motivation in the decision-ma king process. The central role of values as a motivation for decision-making has been well-su pported (Vroom, 1964; Janis & Mann, 1977; Feather, 1992). Brown took this one step furt her by questioning how individuals decided upon which outcomes were most important. Fo r Brown, the answer had its basis in values. Values are cognitive structures that allow individuals to meet their needs in socially acceptable ways. They serve as st andards for behavior and provide the basis on which to understand behavior. For example, an individual who values altruism can easily

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11 explain why it is important to donate time a nd money to help other people in need. Values are generally stable, exist beyond specific situations, a nd are influenced by socialization processes. Values, like interests, are developed as a re sult of the interaction between inherited characteristics and pers onal experience. The results of one study (Keller, Bouchard, Arvey, Segal & Dawis, 1992) suggest that 40 perc ent of the variance in the development of work values can be attributed to genetic influences, and the remaining 60 percent is related to environmental influences. The basic proposition of Brown’s value-base d model is that each person develops a relatively small number of values, and these va lues are prioritized in his or her personal values system. The values having the highest pr iority are the most important determinants for career choices, in that a choice will be made to maximize the satisfaction of high priority values, or minimize the conflict between highly pr ioritized values and career choice, if no ideal option is av ailable. Similar to Keller, et al. (1992), Brown believes that values are acquired through the combination of value-loaded information provided by the environment and inherited characteristics of the individual. Fi nally, Brown’s model recognizes that a range of opportunities and social environments are available to individuals based on their gender, cultura l background, and socioeconomic level, and predicts that this disparity in environment w ill lead to differences in values between men and women, both within and acr oss cultural subgroups. The gender-socialization approach to career choice This model of career development picks up where Brown left off, and asserts that wo men bring different values and traits to their work roles than men do. This approach, however, focuses mainly on earlier gender training as the differentiat ing factor in the development of values

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12 (O’Connell & Betz, 1996). These values and traits shape subsequent work-related interests, career decisions, and behaviors. With in this model, predictions are made as to which specific values will be prioritized by men and women, a topi c that Brown does not address. Proponents of this approach belie ve that men are socialized to be more aggressive and to exhibit a competitive interpersonal style, whereas women are taught to be less aggressive and to show a more rela tionship-oriented interpersonal style. This differential socialization starts at an earl y age as young girls ar e encouraged to be reserved and polite, while boys’ aggressive or rowdy behavior is often rewarded (Eisenhart, 1996). These influences are pe rvasive and can impact a child long into adulthood. They come from a range of sour ces, including family, peers and within the school system. Continued encouragement to participate primarily in gender-appropriate activities may reduce the opportuni ty and desire to branch out and participate in nontraditional experiences. This lack of opportunity and exposure can dampen a young woman’s interest in traditionally male subj ects. By the time students select high school coursework and college majors, they have al ready been subjected to these socialization pressures for many years, and their effects ha ve been imprinted onto student’s behaviors and values. Exposure to a lifetime of pr imarily gender-appropriate activities and experiences will shape an individual’s distinct set of interests, skills and values to reflect that environment, just as a childhood fille d with non-traditional activities would. These interests and values are later translated into the selection of a college major or a career that provides the opportunity to refine and e nhance that set of traits. For example, the woman who excelled at developing relationships as child may select a major in the social sciences and pursue a career in social work; the woman who worked summers at an

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13 electronics shop may register for courses in physics and pursue a career as an electrical engineer. If women in college are making traditionally female career plans, it is in part because their parents, their schools, and their so ciety have taught them to believe that in those fields they are most likely to succeed and find happiness. It is apparent that social influences play a large role in the career choice behaviors of women, whether it is through the estab lishment of gender-appropriate norms and values, gender segregation in the workforce, or barriers to educational achievement. The present research focuses on the role that occ upational values and suppor t from others play in career choice, particularly for women who have chosen STEM careers. It is important to develop and support women’s in terest in STEM so they ca n contribute in a wider range of fields, and promote a healthy, diverse workforce. Occupational Values Occupational values (often referred to as work values) refer to what a person wants out of work in general and what spec ific components of a job are important to attaining satisfaction (Duffy & Sedlacek, 2007) Occupational values, along with interests and preferences, are relatively stable charac teristics based on affective judgments about life events (Dawis, 1991). Although these cons tructs are similar and have overlapping qualities, a distinction should be made between interests a nd values. Interests tend to refer to the like or dislike of activities, whereas values refer to an evaluation of the importance of characteristics in a work envi ronment (Sager, 1999). Values serve as a standard for behavior, which also distingui shes them from inte rests (Brown, 1996). Career choice and satisfac tion are generally thought to be a function of ability and motivation; values being a large precurso r of motivation (Vroom, 1964; Janis & Mann,

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14 1977; Feather, 1992; Dawis, 1991; Brown, 1995). In general, occupational values have been shown to predict career choice, and the congruence between values and work environment has been shown to significantly predict job satisfacti on and job performance (Guastello, Rieke & Guas tello, 1992; Knoop, 1994; Schulen berg, Vondracek & Kim, 1993). For example, Judge and Betz (1992) investigated the proposition that the acceptance of job offers would be related to the candidates’ values and their perceptions of the values likely to be satisfied by th e job. Their hypothesis was supported with one exception: agreement between the degree of honesty expected on the job and the individuals’ honesty value did not seem to influence the acceptance process. Ben-Shem and Avi-Itzhak (1991) studied the relationshi p between work values and career choices and their results also supported the proposition that, when there are options available that will satisfy highly prioritized values, those opt ions are selected. Another study sought to examine the work values of a small populati on of students enrolled in mortuary science programs (Shaw & Duys, 2005). The dominant work values expressed by these students were, in order of importance, economic s ecurity, achievement, personal development, ability utilization a nd economic rewards. Determining the values typical of indivi duals in specific occupations is a worthy endeavor as this information can help guide ca reer counselors in an effort to successfully match people with occupations in which they are likely to be satisfied and successful. In fact, one of the many goals of the Occupati onal Information Network, or O*NET was to document and organize the work characteristic s typical of a wide range of occupations. This allows researchers, organizations, and job seekers to examine the match between an

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15 individual’s occupational values and the occupations that offer an opportunity to satisfy those values (Sager, 1999). It is useful to categorize these occupa tional values by common themes so a better understanding of how they intera ct with career choice is possi ble. Early research divided occupational values into four cat egories: extrinsic, intrinsic, social, and prestige. Extrinsic values refer to an importance placed on ma king money and having job security, whereas intrinsic values refer to an importance plac ed on autonomy and interest. Social values include a desire to work with people and make a contribution to society. Prestige refers to a desire for an occupation that is respected in society (Duffy & Sedlacek, 2007). Within these broad categories, there are several specific work values that commonly appear in the literature. One featur e of the O*NET is the application of 21 job reinforcers from the Minnesota Importanc e Questionnaire (MIQ; Dawis & Lofquist, 1984) to specific occupations. These 21 job re inforcers were factor analyzed and six common work values were revealed. These were achievement (the importance of an environment that encourages accomplishm ent), comfort (the importance of an environment that is comfortable and not st ressful), status (the importance of an environment that provides recognition and pr estige), altruism (the importance of an environment that fosters harmony and service to others), safety (the importance of an environment that is predictable and stab le), and autonomy (the importance of an environment that stimulates initiative (Sag er, 1999)). Proponents of the gender-socia lization approach to caree r choice, one which takes into account the importance of social influen ce on career attitudes, have a broader list of occupational values, selected for their predicted gender differences. Under this

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16 framework, the most relevant to the current study, there are nine commonly identified occupational values. These nine values are job security, occupational skills, opportunity to help people, income benefits, working w ith people, opportunity to work independently, advancement into administration, and freedom from supervision. Reca ll that advocates of this approach believe that women bring different values and traits to their work roles than men because of their earlier gender “training” or socializ ation. Men are thought to be socialized to be more aggressive and to exhibit a competitive style, whereas women are taught to suppress aggression and develop a relationship-oriented style (Statham, 1987). Using this framework, each of these commonl y identified occupational values can be considered male-oriented (competitive or dominance values) or female-oriented (interpersonal values). Betz and O’Connell (1989) examined this proposed gender categorization of work values by conducting a meta-analysis of 22 value studies to compare the values of men and women in the same field. They obtained gender differences in the pattern predicted by th e gender-socialization approach. Men reported placing greater emphasis on the values relate d to competition and dominance and women reported valuing those related to social relationships. Men were more concerned than women about income, job security, and a dvancement; they wanted to avoid being supervised and to work independently and we re more likely to seek self-employment and to value the opportunity to exercise leader ship. Women more than men were concerned with finding a job that allowed them to di splay their esteemed occupational skills and wanted to help people and work with people. There were a total of 22 studies included in the analysis, and the gender-socialization appr oach correctly predic ted the direction of mean gender differences in 90% of the individual value comparisons.

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17 Based on this body of research, it is r easonable to predict that men and women develop different occupational values, and that these differences arise in part from early socialization to gender norms. Furthermore, th ese differences in valu es will play a large role in leading men and women down distinct career paths. Social Support of Career Choice What do you want to be when you grow up? The decision concerning what to do with your professional life can be a daunting one. It is a decision that will, in part, define you as a person and your place in societ y, in many cases can lead to a lifelong commitment, and can impact every other aspect of your life. It is only logical that a decision that large is often made with th e guidance of a support system. Most people require some encouragement and support during the process of choosing an occupation or a career path. This is especially true for women who are pursuing or considering a career in a non-traditional field such as STEM. In traditionally male dominated fields where there are few established women, aspiri ng young women must look elsewhere for guidance and advice about what opportunities are available to them. Often parents, guidance counselors and peers fill this ga p by providing resources about careers and offering encouragement and support. In fact, when asked about the sources of influence on their career choices, over a quarter of young women enrolled in a STEM preparation program reported peers were their greatest sour ce of information and influence (Madill, Montgomerie & Stewin, 2000). Family member s, guidance counselors and teachers also ranked highly in helping shape career interests. In a recent qualitative study, undergraduate women in science majors freque ntly reported that support from family and friends played a large role in influenci ng their choice of majo r (Madill, Ciccocioppo,

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18 Stewin, Armour & Montgomerie, 2004). Fa mily members, especially parents and siblings, were looked to for guidance and of ten provided a model for the students’ own interests and career choices. One individual reported feeling assured she could succeed in engineering because both her brother and sister had already excelled in their respective engineering programs. Studies have repeatedly shown the significant influence that parental support has on women’s selection of non-traditional caree rs (Auster & Auster, 1981, Fitzpatrick & Silverman, 1989). However, not everyone has a supportive ne twork of family, friends and teachers to help guide them. In some instances, wo men who express interest in non-traditional fields may be discouraged by the inherent diffi culties that come with being one of the few women in a historically male dominated en vironment. Early research has shown that female managers in MBA programs receive less career-counseling from their professors than do their male counterparts (Gordon & St rober, 1978). It has been suggested that school and career counselors may still be pr oviding little support and encouragement to women who may want to consider nontraditio nal occupations, may be misinformed about opportunities for women, and may hold their own biases against women who intend to pursue non-traditional careers (Keierleber & Hansen, 1992). It is evident that support from family, fr iends, and teachers can play a large role in the career choice process, a nd the importance of these fact ors is clearly evident among women considering non-traditional careers and programs of study. When social influence is positive, it can support persistence toward a career goal; when ne gative, it can thwart an individual’s exposure to new ideas and activities.

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19 Hypotheses Based on this body of literature a nd grounded in the gender-socialization approach to work orientation, the present research seeks to better understand how two factors, occupational values and social suppor t, effect women’s career decisions. Several hypotheses are put forth below to examine the relationships that exist between these two factors, gender, and career choice. Hypothesis 1 : Consistent with the gender-sociali zation approach to career choice, men and women will differ significantly in the importance of certain central work-related values. (a) Specifically, men place greater importance than women on the occupational values related to dominance, including a high salary, job security, leadership and independence. (b): Women place greater impor tance than men on the occupational values related to relationships, incl uding helping others, relations hips with co-workers, and maintaining work-life balance. It is arguable that STEM occupations ha ve a unique set of rewards and foster a certain set of values. People choose STEM careers in part to fulfill or express their workrelated values. Hypothesis 2 : Individuals in STEM and non-STEM fields differ significantly in the importance of some central work-related va lues (high salary, job security, leadership, independence, relationships with co-worke rs, helping others, work-life balance). Hypothesis 3 : Because STEM careers are a nontraditional choice for women, the amount of support they receive for pursui ng a career in STEM will differ from the support others receive. (a) Women pursuing STEM careers will report having received less career choice support than women pursuing non-STEM car eers. (b): Women

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20 pursuing STEM careers will report less career choice support than men pursuing STEM careers. Hypothesis 4 : The extent to which an individu al has STEM-oriented occupational values (i.e., values similar to other persons in STEM careers) will account for differences in career choice beyond the effects of gender. Hypothesis 5 : Among STEM women, there will be an inverse relationship between having STEM-oriented occupational valu es and receiving care er choice support. That is, women with strong STEM related valu es will require less social support in order to successfully pursue STEM careers. Relationship to the ROLE Grant The Careers and Educational Experiences Su rvey, which is a retrospective survey designed for telephone administration, was developed for use in a multi-year project funded by the National Science Foundation, entitled "Understa nding Factors that Sustain Science, Technology, Engineering, and Ma thematics Career Pathways" (award #0337543). The goal of this project was to develop a thorough understanding of how students’ careers in scien ce, technology, engineering and mathematics (STEM) are sustained or inhibited duri ng secondary and post-seconda ry school. This research endeavor included two interrelated studies, the cohort study of STEM career outcomes and the retrospective survey of career attitudes and behaviors The cohort study used information collected and maintained by the Florida Department of Education (DOE) to examine the career pathways of several cohorts of Florida high school and college graduates. Th e aim of this facet of the project was to understand demographic and structural variab les associated with outcomes related to

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21 STEM careers. The retrospective survey allo wed a more in-depth examination of the social and psychological factors associated with STEM career choice and supplemented the archival data in order to provide a richer understanding of career choice.

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22 Method Sample Identification The Florida DOE maintains student-tracki ng databases that provide an excellent resource for the current study. The Flor ida Education and Training Placement Information Program (FETPIP) database track s student outcomes after high school and college for all Florida public high school a nd college graduates. FETPIP collects data annually, and has been tracki ng all high school graduating cohorts since 1991. FETPIP records contain important information related to student's outcomes, such as students’ further education, placement and employment, and military enlistments. This data set is the only one of its kind in the nation. The pos t-secondary education information is less complete for earlier FETPIP cohorts. For r ecent cohorts, college degree status and major is available for all high school graduates, ev en those who attend college out of state. Because the FETPIP database contains information on hundreds of thousands of students, a sub-sample was identified for pa rticipation in the retrospective survey. Two cohorts of graduates were select ed to participate, the first having graduated from a public Florida university in 1997 and the second having graduated in 2003. Relatively recent cohorts of graduates were select ed so that respondents would be better able to remember and report their experiences in high school a nd college, and their career decision making process. However, individuals who graduate d very recently were not included because they would not have had time to obtain work experience and settle into a career. These

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23 two cohorts were expected to have had time to obtain a moderate amount of work experience while still able to reflect on school experiences. Because STEM majors are only a small portion of all college graduates, and women a small portion of STEM majors, wo men with STEM majors were over-sampled in order to ensure an adequate representati on of the population of in terest in the final sample. An individual is considered to have earned a STEM degree if they majored in any of the engineering subfield s, computer science, mathema tics or the physical sciences. Those students who graduated w ith a degree in anything other than a STEM major were classified as non-STEM. Limited information was provided by the Fl orida DOE to assist in the location of the selected individuals. This information incl uded name, gender, race, date and city/state of graduation. With this information, tele phone numbers and in some cases addresses were obtained using several web-based sear ch programs (such as privateeye.com). Participants There were approximately 3,200 names of Florida college graduates originally selected from the FETPIP database. Valid contact information was gathered for 812 persons, and of that group, 62 individuals were successfully cont acted and agree to complete the survey. The final sample of 62 participants was evenly divided by gender. Due to the over-sampling of STEM graduates, 74% of the sample had chosen careers in STEM (n=26 men, 20 women) and 26% we re non-STEM (n=5 men, 11 women). Respondents received their degrees betw een the years 1970 to 2003, with the most common graduation years being 1996 (24% n=15), 1997 (20%, n=13) and 2003 (23%, n=14). This bimodal distribution reflects the purposeful sampling of two distinct cohorts

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24 of graduates. As for the current employment status of the sample, 84% were currently working (n=52) and 21% were attending school (n=13). Survey Development The goal of the survey development was to create an instrument to address a wide range of topics related to STEM career c hoice as well as topics that cut across disciplinary boundaries. In order to create a su rvey that represented multiple disciplines and ideologies, research on career de cision-making and outcomes conducted by anthropologists, sociologists and psychol ogists was considered. These perspectives involve different theoretical foundations (p erson-centered on the psychological side, structural/organizational from the sociological perspective and cultural from the anthropological perspective) and different research methods However, when integrated, they provide complementary sources of information on career decision-making and STEM careers. Topics addressed in the survey included work centrality and values, social support, obstacles and barrier s to educational attainment, role models, academic engagement, and participation in STEM-orien ted leisure activities. The focus of the current study, however, was limited to those questions focused on occupational values and social support as they rela te to women’s STEM career choi ces (for a complete list of items included on the su rvey, see Appendix A). Variables Occupational values Seven occupational values were identified for the purposes of this study and included in the survey. These were dr awn primarily from the gendersocialization framework and specifically th e work of Betz and O’Connell (1989) on gender differences in occupational values. The values included are helping others,

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25 income, autonomy, job security, relationships with co-workers, lead ership and work-life balance. Respondents were asked to rate how important each value was to them when choosing a career on a five-point Likert -type scale (1-very unimportant; 5-very important). Career choice support Three survey questions addr essed the issue of social support for career pursuits: one each for the influence of (1) family, (2) peers, and (3) teachers or counselors respectively. An exampl e of a support question is “To what extent did your family members encourage you to pursue your career choice?” Respondents were asked to indicate the le vel of encouragement they rece ived on a five-point Likerttype scale (1 strongly disc ouraged; 5 strongly encouraged ). Responses to each of the three support questions were summed to obt ain an overall support score, ranging from 3 (highly discouraged) to 15 (highly encouraged). Field of pursuit This variable represents an i ndividual’s career choice, but is limited to the field in which their occupati on and/or college degr ee lies. Respondents were asked to describe their occupation as they would to a layperson. If they were currently enrolled in school, they reported the program of study, degree type, and school in which they were enrolled. These res ponses were coded into STEM or non-STEM fields by the researcher and a second gra duate student. Agreement on STEM or nonSTEM occupation type and program of study was 100% between the two coders. Because approximately one quarter of the sample had recently graduated (2003), there is the potential for some respondents to be in their firs t jobs, jobs that may not be representative of the careers th ey intend to pursue (e.g., their first job out after graduation is in retail or customer service but thei r degree is in Chemistry). For this reason,

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26 respondents were also asked how well their current occupa tion fit into their chosen career. Individuals who reported a strong fit between their current occupation and career plans were directed to refer to their current occupation in answeri ng the survey questions about career choice. Individuals who reported a weak fit or no fit were directed to think about their college major when answering su rvey questions about career choice. Of the 62 participants, 42 reported a satisfactory f it between occupation and career. There were no significant differences between these two gr oups of participants on key study variables (gender, occupational values and career ch oice support) so they were pooled for the subsequent analyses. Survey Administration Participants were located, contacted and surveyed by Westat. This organization was contracted to conduct the data collection over the telephone as part of the parent grant to this study, and has a l ong history in conducting social science research. Prior to data collection, Westat collaborate d with the first author to re fine the survey protocol for clarity. A team of Westat interviewers was fa miliarized with the survey and attended a four-hour training session which was tailored to the specific n eeds of the study and supervised by the first author. Data colle ction began November 10, 2006 and continued through January 31, 2007. Westat interviewers began with a list of approximately 800 valid names and telephone numbers, and attempted to contact each participant up to 34 times to maximize the final number of responde nts. Each interviewer followed a scripted introduction which included the rights of the respondent to skip questions or to discontinue the survey at any time (for the full introduction and surv ey instructions, see Appendix A). When the data collection peri od was over, data preparation staff key

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27 entered all the collected data. Each case wa s entered twice to ensure accuracy. Westat examined response frequencies to ensure th at skip patterns were properly followed and all missing data was properly accounted for (f or a complete review of the Westat data collection process, see Appendix B).

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28 Results To test the first hypothesis that the m ean importance of each value will differ between men and women, each value was comp ared individually between the groups using an independent samples t-test. Means a nd standard deviations of the importance of each value by gender are detailed in Table 1. Five of the seven occupational values differed significantly between men and wo men. Men placed more importance than women on salary, t (60)=2.37, p <.05; and independence, t (60)=5.84, p <.05. Women more than men valued helping others, t (60)=-4.33, p <.05; work-life balance, t (60)=-3.13, p <.05 and relationships with co-workers, t (60)=-3.27, p <.05. There were no significant gender differences in the importance placed on leader ship and job security. These results provide support for hypothesis one. The second hypothesis addressed the same mean value differences, but between STEM and non-STEM individuals instead of by gender. Each value was compared individually between the groups using an independent samples t-test. Means and standard deviations for the importance of each value by STEM/non-STEM are detailed in Table 1.

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29 Table 1 Means and Standard Deviations of Values by Gender and Degree Occupational Value Gender Degree Men Women STEM Non-STEM M SD M SD M SD M SD Salary 4.45 .51 4.00 .63 4.24 .77 4.19 .83 Job security 4.71 .46 4.42 .67 4.65 .53 4.31 .70 Leadership 4.00 .93 3.58 .96 4.00 .82 3.19 1.11 Independence 4.81 .41 3.94 .73 4.50 .69 4.00 .73 Relationships w coworkers 3.83 .90 4.52 .72 4.04 .89 4.56 .73 Work-life balance 4.29 .82 4.84 .52 4.46 .81 4.88 .34 Helping others 3.55 1.03 4.48 .63 3.83 .85 4.56 1.09 Five of the seven occupational values differe d significantly by fi eld. STEM individuals placed more importance on independence than non-STEM individuals, t (60)=2.46, p <.05; on leadership, t (60)=3.12, p <.05; and on job security, t (60)=2.03, p <.05. Conversely, non-STEM respondents more than their STEM counterparts valued helping others, t (60)=-2.74, p <.05; and relationships with co-workers, t (60)=-2.09, p <.05.There was no significant difference between groups in the impo rtance of work-life balance or salary by career field. These results provi de support for hypothesis two. Hypothesis three compares women in STEM with their female non-STEM counterparts, as well as their male STEM c ounterparts on the variable of career choice support. As described in the Methods section, the three suppo rt items (referencing family, peers and teachers) were summed to generate a support scale to be used in these analyses. Group differences in support were calculated with a series of independent samples t-tests.

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30 Women reported a significantly lower overa ll level of encouragement for pursing a STEM career than women pursuing a non-STEM, t (29)=-5.41, p <.05. Women pursuing careers in STEM also reported significantly lo wer levels of encouragement than did men pursuing a career in STEM, t (44)=4.99, p <.05. Means and standard deviations for social support by gender and field are in Table 2. These results provide full support for hypothesis three. Table 2 Means and Standard Deviations of Social Support by Gender and Degree Source of Support Gender Degree Men Women STEM Non-STEM M SD M SD M SD M SD Family support 4.10 .83 4.13 1.03 4.04 .99 4.31 .70 Peer support 3.74 .73 3.74 .93 3.59 .83 4.19 .66 School support 3.68 .75 3.81 .79 3.65 .77 4.00 .73 Although no predictions were made about specific sources of support, the relationship between these three sources of support were examined. There was a significant positive correlation between s upport received from friends and family ( r =.274, p <.05) and friends and school personnel ( r =.616, p <.05). There was no relationship between the amount of support between family and school personnel. Correlational data for social support are in Tables 3.

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31 Table 3 Means, standard deviations, and intercorrelations of sources of support. Source of Support Mean S.D. N 1 2 3 4 1. Support from family 4.11 .93 62 1 2. Support from friends 3.74 .83 62 .274* 1 3. Support from school 3.74 .77 62 .134 .616** 1 4. Social Support Scale 11.19 2.02 62 .516** .679** .553** 1 *Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). Hypothesis four examined the extent to which differences in career choice could be accounted for by gender and occupational va lues. Specifically the question addressed was whether values would improve the pred iction of STEM career choice after gender was taken into account. To test this hypothesi s, a values index was first computed to create one continuous variable to take into account all relevant occupational values simultaneously. Correlational data for occupa tional values are presented in Table 4.

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32 Table 4 Means, standard deviation, and intercorrelations of occupational values Occupational Values Mean S.D. N 1 2 3 1. Gender 62 1 -.293* -.248 2. Value: salary 4.22 .78 62 -.293* 1 .146 3. Value: job security 4.56 .59 62 -.248 .146 1 4. Value: leadership 3.79 .96 62 -.220 .108 .212 5. Value: independence 4.37 .73 62 -.602** .023 .229 6. Value: relationships with coworkers 4.18 .88 62 .389** -.228 -.038 7. Value: helping others 4.02 .97 62 .488** -.092 .013 8. Value: work-life balance 4.56 .74 62 .374** -.169 -.104 9. STEM Value Scale .82 .43 62 -.483** .157 .389** *. Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). Table 4 (continued) Means, standard deviation, and intercorrelations of occupational values Occupational Values 4 5 6 7 8 9 1. Gender -.220 -.602** .389** .488** .374** -.483** 2. Value: salary .108 .023 -.228 -.092 -.169 .157 3. Value: job security .212 .229 -.038 -.104 -.104 .389** 4. Value: leadership 1 .370** -.208 -.279* -.177 .791** 5. Value: independence .370** 1 -.309* -.288* -.243 .444** 6. Value: relationships with coworkers -.208 -.309 1 .518** .323* -.436** 7. Value: helping others -.279* -.288* .518** 1 .309* -.749** 8. Value: work-life balance -.177 -.243 .323* .309* 1 -.312* 9. STEM Value Scale .791** .444** -.436** -.749** -.312* 1 *. Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

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33 This values index represented the degree to which an individu al possesses STEMoriented values (that is, values similar to those reported by those in STEM careers on average), and was calculated by regressing all significant values (determined in hypothesis two) on career choice. These valu es were independence, leadership, job security, helping others, and relationshi ps with co-workers. Independence and relationships with co-workers were subsequently removed from the analysis due to their low beta weights. Due to the low sample size, the alpha level for the regression analyses only was raised to 0.10. All other analyses were conducted using an alpha level of 0.05. The resulting model was significant ( r = .237, p <.05) and the equation for calculating the STEM-oriented values score was 0.256 (leadership) + 0.203 (j ob security) – 0.267 (helping others). The score on this value in dex can be interpreted as representing the extent to which an individual possesses t ypically STEM-oriented occupational values, with higher values indicating a grea ter degree of STEM-oriented values. This values index was then used to test the hypothesis that possessing STEMoriented values will improve prediction of career choice after gender is taken into account. Gender was regressed on career choice, and the resul ting model was significant ( r2= .049, p <.05). However, when the STEM values index was entered into the model, r2 rose sharply to .232, p <.05, and gender was no longer a si gnificant predictor of career choice, = -.015. Additionally, these two variables ha ve a strong inverse relationship with one another ( r = -.483. p <.05). Data for this analysis are in Table 5. These results provide full support for hypothesis four.

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34 Table 5 Regression analyses for occupational values and gender. R2 R2 B Model 1 .049* Gender .221* Model 2 .232* .183* Gender -.015 STEM Values -.488* *Correlation is significant at the 0.10 level (2-tailed). The fifth and final hypothesis predic ted a negative relationship between the degree to which an individual possesses ST EM-oriented values a nd the level of career choice support they received from family, fr iends and school personnel. This analysis was limited only to STEM women; men and non-STEM women were excluded from the sample (n=20). To test this hypothesis, the STEM-oriented values index (calculated in hypothesis four) was correlated with the ca reer choice support index (calculated for hypothesis three) using the Pearson correla tion. A moderate, negative relationship was found, r = -0.441, p <.05. A separate correlation wa s conducted for men, although no prediction was made about its directionalit y. No significant relationship between STEMoriented values and career choice support was found. These results provide support for hypothesis five.

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35 Discussion Value differences between men and women were significant and in the expected direction. Men valued salary and independe nce more highly than women, and women valued helping others, maintaining a healt hy work-life balance, and developing healthy relationships with colleagues. There were no si gnificant differences in the priority placed on leadership and job security. However, the mean differences in these values indicated that men tended to place a slightly higher value on both leadersh ip and job security. These results support the predic tions of Brown’s value-based model of career choice, in that gender differences were found in the importance placed on di fferent occupational values. This pattern of results also suppor ts the gender-socialization model of career choice. Men are expected to show preference for competitive or dominance-oriented values, whereas women are predicted to c hoose interpersonal-oriented values. The current results indicate men placed importanc e on salary and independence, which are associated with the dominance-orientation. Women valued helping others, maintaining work-life balance and developing relationships with co-workers, all of which can be considered to have an interpersonal-orientat ion. These results are al so congruent with the work values meta-analysis conduc ted by Betz and O’Connell (1989). In addition to the gender differences in occupational values, differences between those in STEM and non-STEM were examine d. Individuals in STEM fields valued independence, leadership and job security significantly more than individuals in nonSTEM fields. Those in non-STEM fields valued helping others and re lationships with co-

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36 workers significantly more than their S TEM counterparts. There was no significant difference between groups in the importance of work-life balance or salary by career field. However, the mean differences suggest that individuals in STEM value salary slightly more than non-STEM individuals a nd work-life balance sl ightly less than nonSTEM individuals. There was no prediction made as to the direction of these mean value differences. However, the fact that diffe rences do occur between STEM and non-STEM fields supports the research by Ben-Shem and Avi-Itzhak (1991), who believe that certain occupations will satisfy the values of an individua l better than others, and that it is mainly due to this satisfaction of values that a career choice is based. The pattern of value differences by ge nder is similar to, but does not mirror, the differences found between STEM and non-STEM individuals. Because of the vast overrepresentation of men in STEM a logical assumption would be that male values should parallel STEM values, but this is not th e case. Independence wa s valued significantly higher by both men and STEM individuals, but th e similarity ends th ere. Individuals in STEM also place a significantly higher value on leadership and job security, values that did not distinguish between genders. Men al so highly valued salary, which did not discriminate between STEM and non-STEM. The results for hypothesis four showed that while gender could significantly account for STEM vs. non-STEM career choice, the addition of the STEM values score rendered gender an insignificant predictor of STEM vs. non-STEM career choice. Moreover, the strength of STEM values ac counted for approximately a quarter of the variability in career choice, a nd allowed for better prediction of choosing a STEM career. These results suggest that people with more tr aditionally STEM values are more likely to

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37 choose STEM careers regardless of gende r. This underscores the importance of influences other than gender on career choice. It is not gend er, but these value differences which are often associated with gender, that help drive care er decisions. While individuals are not in contro l of their gender, a variety of outside influences and environmental conditions interact with gende r to shape the development of occupational values (Keller, et al., 1992; Brown, 1995) These results strengthen the need for continuing study of the under-represe ntation of women in STEM. With regard to social support for care er decisions, results showed that women pursuing STEM careers received significantl y less support for their career pursuits than their female non-STEM counterparts receiv ed for pursuing non-STEM careers. In addition, STEM women also received less overa ll social support for their STEM career aspirations than did men for pursuing STEM careers. A closer look at the different sources of support revealed a positive relationship between the amount of support received from friends and family, as well as a positive relationship between that of friends and school personnel. Overall, thes e results indicate that women who pursue nontraditional careers may be doing so without the support and guidance of friends, family, or the educational system. These results co incide with early evidence that women in STEM are not being supported to the extent that their male counterparts are, such as reports of MBA students receiving differen tial treatment (Gordon & Strober, 1987), and it seems that the potentially misinformed sc hool counselors may still be falling victim to traditional gender biases and providing antiquated career advice (Keierleber & Hansen, 1992). Encouraging women to enter non-traditio nal career fields such as STEM is increasing as a national priority, as ev idenced by the National Science Foundations

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38 mission to ensure a diverse, well-qualified STEM workforce (www.nsf.gov). If cultivating a diverse workforce and encour aging more women into STEM is truly a priority, then the messages that are being se nt to young women need to reflect that. In order to further the in vestigation of this differen tial support given to women, the relationship between support and occupationa l values was considered specifically for women in STEM fields. Women who scored high on STEM values received less social support than women who possess mainly non-S TEM values. Overall, both values and support appear to be important in women’s c hoice of a STEM career, and their influences are somewhat complementary. For women, having more traditionally STEM values may at least partially compensate for a lack of STEM career support. It is possible that, for women, developing a strong set of STEM values may buffer the negative impact of never having received adequate social support, and th ese values will bolster the ability to persist in a STEM field. Limitations of the study and imp lications for fu ture research There is an ongoing effort to further our understanding of why women choose to enter non-traditional career fields. This st udy provides the foundation to continue this investigation, with a specific focus on the importance of developing occupational values, and identifying and maintaining a healt hy support system of friends, family, and educators. The next steps in this pur suit should reflect di verse methodology and incorporate multiple disciplines. Because occupational values have been shown to strongly influence career deci sions, a more detailed examination of these values is warranted. Longitudinal research could addr ess the effects of socialization on the development of values, and identify successful strategies for fostering the development of

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39 these values. For example, if the relationshi p between the socializa tion of women and the development of their occupational values were examined, that would allow the design of interventions to positively socialize young women to the benefits of non-traditional careers. In addition, by sampling cohorts of high school and college students in a longitudinal design, it would be possible to gather real-tim e information about the type and amount of support being offered before, dur ing, and after a career choice is decided upon, and measure the development of their occu pational values as the mature during the educational process. Research in career choice can also be nefit from the application of qualitative methods. Collecting life histor ies or conducting unstructured interviews can reveal a wealth of information that would not otherwis e be available, and allows for an in-depth examination of individuals as they navigate their career decisions. Fu rthermore, with the changing landscape of the workforce and the em ergence of the protean career, traditional topics such as career choi ce are becoming increasingly co mplex, and new and innovative methods are needed to fully examine thes e changes (Lee, Mitchell & Sablynski, 1999). Qualitative methodology can serve to fill in the gaps in our knowledge base as the concept of a career continues to develop. Future research in this area should incl ude larger samples of college graduates. The current sample was limited in size a nd had an uneven dist ribution of women by occupation; there were very few non-STEM women due to the vigorous over-sampling of STEM graduates. Additional pa rticipants and a more curren t cohort of coll ege graduates would add to the generalizability of the conc lusions that were reached, and allow for a more complex investigation of the relationshi ps between these variables. By including

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40 more recent cohorts of students, issues re lated to memory, such as the ability of participants to recall past events a nd decisions can also be improved. Finally, more robust measures of occ upational values should be included. The current survey was limited to one item per value, which constrains the ability to determine the reliability of the items. More detailed scales of occupational values will allow for a more reliable assessment of STEM women. Ultimately, the goal of understanding barriers to women’s STEM wo rkforce participation is to use this knowledge to guide the design of interventions that organizations can implement in the recruitment, retention, and a dvancement of women, and that career counselors can use to help women engage in more vigorous and e ffective investigation of a STEM career.

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41 List of References Astin, A., Korn, W., Sax, L., & Mahoney, K. (1994). The American freshman: National norms for fall 1994. Los Angeles: Higher Educa tion Research Institute, University of California, Los Angeles. Auster, C. & Auster, D. (1981). Factors in fluencing women’s choice of nontraditional careers: The role of family, peers, and counselors. Vocational Guidance Quarterly, 29, 253-263. Ben-Shem, I. & Avi-Itzhak, T. (1991). On work values and career choice in freshman students: The case of helpi ng vs. other professions. Journal of Vocational Behavior, 39 369-379. Betz, N., & Fitzgerald, L. (1987). The career psychology of women San Diego, CA: Academic Press. Betz, M. & O’Connell, L. 1989. Work orientatio ns of males and females: Exploring the gender socialization approach. Sociological Inquiry, 59 318-330. Brown, D. (1995). A values-based mode l for facilitating career transitions. Career Development Quarterly, 44, 4-11. Brown, D. (1996) Brown’s values-based, holistic model of career and life-role choices and satisfaction. In D. Brown and L. Brooks, (Eds.), Career Choice and Development (3rd ed., pp. 337-372). San Francisco, CA: Jossey-Bass Pubishers. Brown, D., & Brooks, L. (1990). Career choice and development: Applying contemporary theories to practice (2nd ed.). San Francisco, CA: Jossey-Bass. Brown, D., & Crace, R. (1996). Values in life role choices and outcomes: A conceptual model. The Career Development Quarterly, 44, 211-223. Dawis, R. (1991). Vocational interests, values and preferences. In M. Dunnette & L. Hough (Eds.), Handbook of Industrial Organizational Psychology (Vol. 2, pp. 833-871). Palo Alto, CA: Consulting Psychologists Press. Dawis, R. & Lofquist, L. (1984). A psychological theory of work adjustment. Minneapolis: of Minnesota Press. Duffy, R., & Sedlacek, W. (2007). The work va lues of first-year college students: Exploring group differences. The Career Development Quarterly, 55, 359-364.

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42 Eisenhart, M. (1996). Contemporary college wome n’s career plans. In P. Dubeck & K. Borman (Eds.), Women and Work: A Handbook (pp. 232-235). New York, NY: Garland Publishing, Inc. Fassinger, R & Asay, P. (2006). Career couns eling for women in science, technology, engineering, and mathematics (STEM) fiel ds. In B. Walsh & M. Heppner (Eds.), Handbook of Career Counseling for Women (2nd ed., pp. x). Mahwah, NJ: Lawrence Erlbaum Associates, Publishers. Feather, N. (1992). Values, vale nces, expectations, and actions. Journal of Social Issues,48, 109-124. Fitzgerald, L., & Crites, J. (1980). Toward a career psycholo gy of women: What do we know? What do we need to know? Journal of Counseling Psychology, 27, 44-62. Fitzpatrick, J & Silverman, T. (1989). Women’s se lection of careers in engineering: Do traditional nontraditional differences still exist? Journal of Vocational Behavior, 34, 266-278. Gallos, J. (1989). Exploring women’s devel opment: Implications for career theory, practice, and research. In M. Art hur, D. Hall, & B. Lawrence (Eds.), Handbook of Career Theory (pp 110-132). New York, NY: Ca mbridge University Press Gordon, F. & Strober, M. (1978). Initial obs ervations on a pioneer cohort: 1974 women MBAs. Sloan Management Review, 19 15-23. Greenhaus, J., Callanan, G., & Godshalk, V. (2000). Career Management (3rd ed.). Orlando, FL: The Dryden Press. Guastello, S., Rieke, M., & Guastello, D. ( 1992). A study of cynicism, personality, and work values. Journal of Psychology: Inte rdisciplinary and Applied, 126 37-48. Gutek, B., & Larwood, L. (1987). Working to wards a theory of women’s career development. In B. Gutek & L. Larwood (Eds.), Women’s Career Development (pp. 170-183). Thousand Oaks, CA : Sage Publications, Inc. Holland, J. (1966). The psychology of vocational choice : A theory of personality types and model environments Oxford, England: Blaisdell. Janis, I. & Mann, L. (1977). A psychological analysis of con flict, choice and commitment. New York: Free Press. Judge, T. & Bretz, R. (1992). Effects of work values on job choice decisions. Journal of Applied Psychology, 77, 261-271.

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43 Keierleber, D., & Hansen, L. (1992). A coming of age: Addr essing the career development needs of adult students in University settings. In D. Lea, & Z. Leibowitz (Eds.), Adult Career Development (pp. 312-339). Alexandr ia, VA: National Career Development Association. Knoop, R. (1994). Work values and job satisfaction. Journal of Psychology: Interdisciplinary and Applied, 128 683-690. Lee, T., Mitchell, T., & Sablynski, C. (1999). Qualitative research in organizational and vocational psychology, 1979-1999. Journal of Vocational Behavior, 55, 161-187. Lightbody, P., Siann, G., Tait, L., & Walsh, D. (1997). A fulfilling career? Factors which influence women’s choice of profession. Educational Studies, 23, 25-37. Madill, H., Montgomerie, T., & Stewin, L. ( 2000). Young women's work values and role salience in grade 11: Are ther e changes three years later? The Career Development Quarterly, 49 16-28. Madill, H., Ciccocioppo, A., Stewin, L., Arm our, M. & Montgomerie, T. (2004). The potential to develop a career in science: Young wo men's issues and their implications for careers guidance initiatives. International Journal for the Advancement of Counseling, 26, 1-19. National Science Board. (2000). Science and engineering indicators. Arlington, VA. National Science Foundation, Division of Science Resources Statistics, Women, Minorities, and Persons with Disabilit ies in Science and Engineering: 2007 NSF 07-315 (Arlington,VA; February 2007). O’Connell, L., & Betz, M. (1996). Gender differences in work interests. In P. Dubeck & K. Borman (Eds.), Women and Work: A Handbook New York, NY: Garland Publishing, Inc. Powell, G., & Mainiero, L. (1992). Cross-curren ts in the river of tim e: Conceptualizing the complexities of women’s careers. Journal of Management, 18, 215-237. Sager, C. (1999). Occupational interests and values. In N. Peterson, M. Mumford, W. Borman, P. Jeanneret & E. Fleishman (Eds.), An Occupational System for the 21st Century: The Development of O*NET. Washington, DC: American Psychological Association. Schulenberg, J., Vondracek, F., & Kim, J. (1993). Career certainty and short-term changes in work values during adolescence. Career Development Quarterly, 41, 268-284.

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44 Shaw, T. & Duys, D. (2005). Work valu es of mortuary science students. Career Development Quarterly, 53 348-352. Statham, A. (1987). The gender model revisited: Differences in the management styles of men and women. Sex Roles 16, 409–429. Stockard, J., & McGee, J. (1990). Children’s occupational preferences: The influence of sex and perceptions of o ccupational characteristics. Journal of Vocational Behavior, 36, 287-303. Super, D. (1957). The Psychology of Careers. New York: Harper & Row. Super, D., Savickas, M., & Super, C. (1996) The life-span, life-space approach to careers. In D. Brown and Brooks, L. (Eds.), Career Choice and Development (3rd ed., pp. 337-372). San Francisco, CA : Jossey-Bass Pubishers. Vroom, V. (1964). Work and Motivation. New York: Wiley. White, M., Kruczek, T., Brown, M., & White, G. (1989). Occupationa l sex stereotypes among college students. Journal of Vocational Behavior, 34, 289-298.

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45 Appendix A: Careers and Educational Experiences Survey Protocol

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46 Appendix A CAREERS IN SCIENCE (8271) QUESTIONNAIRE ID: | | | | | INTRODUCTION: Hello, may I speak with [ RESPONDENT NAME ]? [ IF NOT AVAILABLE, ASK ] : When would be a good time to reach [ RESPONDENT ]? RECORD BEST DAY AND TIME ON CALL RECORD. IF SOMEONE OTHER THAN RESPONDENT ASKS REASON FOR CALL: My name is [ INTERVIEWER NAME ]. I'm calling from Westat, a survey research company located in Rockville, Maryland. We ar e conducting a study for a research team at the University of South Florida about the career choices of college graduates. IF RESPONDENT IS AVAILABLE: Hello, my name is [INTERVIEWER NAME] and I’m calling from Westat, a survey research company in Rockville, Maryland. We are conducting a study for a research team at the University of South Florida. The purpose of the research is to find out more about what influences the career choices of college graduates. You were carefully selected to participate in this study because of the unique insight you can provide to us. INFORMED CONSENT: In order to protect your confidentiality, ther e are some things I have to tell you before the interview begins. First, your participation in the interview is voluntary and poses no risk to you. You may refuse to answer any questi on. You may stop your participation at any time. If you agree to participate, all of your responses will be kept confidential, and no one outside of the research team will have access to your responses. Should you have any questions about this interview or your rights as a participant, please feel free to contact Heather Meikle, the University of South Florida project director, 813-974-4082. This is not a toll-free call. This interview should take approximately 20 minutes. CONSENT: May I continue with the interview? a. YES ……………………………………………….01 b. NO ……………………………………………….02 [ THANK AND END ] c. CB ………………………………………………..03 [ SCHEDULE CB ] Q1. First, I’d like to check some information with you. According to our records, you earned a bachelor's degree from a public institution. Is that correct?

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47 Appendix A (Continued) a. YES ....................................................................................... 01 b. NO .......................................................................................... 02 c. REFUSED .............................................................................. 98 d. DON’T KNOW ........................................................................ 99 Q2. What degree did you earn? [SPECIFY]: ______________________________________________________ Q3. From what school did you earn the degree? [SPECIFY]: ______________________________________________________ Q4. In what program was the degree earned? [SPECIFY]: ______________________________________________________ Q5. In what year was the degree earned? [SPECIFY]: ______________________________________________________ Q6. Have you earned any other post-secondary degrees, such as a master’s degree or other graduate degree? a. YES ........................................................................................ 01 b. NO .......................................................................................... 02 [GO TO Q9] c. REFUSED .............................................................................. 98 [GO TO Q9] d. DON’T KNOW ........................................................................ 99 [GO TO Q9] Q7. What are they? [SPECIFY]: ______________________________________________________ Q8. From what school did you earn {it/them} ? [SPECIFY]: ______________________________________________________ Q9. Are you currently enrolled in school?

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48 Appendix A (Continued) a. YES ........................................................................................... 01 b. NO ............................................................................................. 02 [GO TO Q13] c. REFUSED ................................................................................. 98 [GO TO Q13] d. DON’T KNOW ........................................................................... 99 [GO TO Q13] Q10. What is the name of the school? [SPECIFY]: ______________________________________________________ Q11. What degree are you working towards? [SPECIFY]: ______________________________________________________ Q12. Are you enrolled full-time or part-time? [SPECIFY]: ______________________________________________________ Q13. Are you currently employed? a. YES ........................................................................................... 01 b. NO ............................................................................................. 02 [GO TO Q18 INTRO] c. REFUSED ................................................................................. 98 [GO TO Q18 INTRO] d. DON’T KNOW ........................................................................... 99 [GO TO Q18 INTRO] Q14. Are you employed full-time or part-time? a. FULL-TIME ................................................................................ 01 b. PART-TIME ............................................................................... 02 c. REFUSED ................................................................................. 98 d. DON’T KNOW ........................................................................... 99 Q15. What is your occupation? Please describe your job as you would to a layperson. [SPECIFY]: ______________________________________________________

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49 Appendix A (Continued) Q16 INTRO: Now I would like to ask you a few questions about your attitudes towards your job. Q16. Overall, how satisfied are you with y our current job? Would you say you are… a. Very satisfied, ............................................................................ 01 b. Somewhat satisfied, .................................................................. 02 c. Neither satisfied nor dissatisfied, ............................................... 03 d. Somewhat dissatisfied, or .......................................................... 04 e. Very dissatisfied? ...................................................................... 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q17. How important is your job to who you are? Would you say it is… a. Very important, .......................................................................... 01 b. Somewhat important, ................................................................. 02 c. Neither important nor unimportant, ............................................ 03 d. Somewhat unimportant, or ........................................................ 04 e. Very unimportant? ..................................................................... 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99

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50 Appendix A (Continued) Q18 INTRO: I am going to read a list of factors someone might consider in choosing a career. Please tell me whether each factor is very important, somewhat important, neither important nor unimportant, somewhat unimportant, or very unimportant. How important to you in choosing a career is…… Very Import ant Somew hat Importa nt Neither Importan t Nor Unimpor tant Somewh at Unimpor tant Very Unim porta nt RF D K Q1 Helping others? .......... 01 02 03 04 05 98 9 9 Q1 A challenging or intellectually stimulating environment ? .................... 01 02 03 04 05 98 9 9 Q2 0. (How important to you in choosing a career is) A high salary? ... 01 02 03 04 05 98 9 9 Q2 1. Independenc e? .................. 01 02 03 04 05 98 9 9 Q2 2. Recognition? . 01 02 03 04 05 98 9 9 Q2 3. Job security? . 01 02 03 04 05 98 9 9 Q2 4. Adventure? .... 01 02 03 04 05 98 9 9 Q2 5. (How important to you in choosing a career is) Interpersonal relations with coworkers? .... 01 02 03 04 05 98 9 9 Q2 6. Leadership opprotunities ? .................... 01 02 03 04 05 98 9 9

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51 Q2 7. The ability to balance your job and family responsibiliti es? ................ 01 02 03 04 05 98 9 9 Q28 INTRO: Next I have some questions about the pursuit of your career goals. [IF Q13 = NO, GO TO Q29 AND USE “C OLLEGE MAJOR” IN Q29 THROUGH Q48 AND Q52 THROUGH Q60] Q28. Consider your career goals, and the job you would ultimately like to hold. How does your current occupation fit on the pat h to achieving this goal? Would you say… a. You are in your goal career already, ......................................... 01 b. It fits very well, ........................................................................... 02 c. It fits somewhat well, ................................................................. 03 d. It does not fit very well, or .......................................................... 04 e. It does not fit at all? ................................................................... 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 [IF Q28 = A, B, OR C, USE “CURRENT CAREER” IN SUBSEQUENT QUESTIONS. IF Q28 = D OR E, OR IF Q13 = B, USE “COLLEGE MAJOR.” THIS APPLIES TO Q29 THROUGH Q48 AND Q52 THROUGH Q60] Q29. When you decided on your {college major/current career}, how accurate was your expectation of what would be invo lved? Would you say your expectation was… a. Very accurate, ........................................................................... 01 b. Somewhat accurate, .................................................................. 02 c. Neither accurate nor inaccurate, ............................................... 03 d. Somewhat inaccurate, or ........................................................... 04 e. Very inaccurate? ........................................................................ 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q30. To what extent did your parent s or immediate family members encourage you to pursue your {college major/current career}? Did they…

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52 Appendix A (Continued) a. Encourage you a lot, .................................................................. 01 b. Encourage you somewhat, ........................................................ 02 c. Neither encourage nor discourage you, .................................... 03 d. Discourage you somewhat, or ................................................... 04 e. Discourage you a lot? ................................................................ 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q31. To what extent did your peers encourage you to pursue your {college major/current career}? Did they… a. Encourage you a lot, .................................................................. 01 b. Encourage you somewhat, ........................................................ 02 c. Neither encourage nor discourage you, .................................... 03 d. Discourage you somewhat, or ................................................... 04 e. Discourage you a lot? ................................................................ 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q32. To what extent did your teachers or other school personnel encourage you to pursue your {college major/current career}? Did they… a. Encourage you a lot, .................................................................. 01 b. Encourage you somewhat, ........................................................ 02 c. Neither encourage nor discourage you, .................................... 03 d. Discourage you somewhat, or ................................................... 04 e. Discourage you a lot? ................................................................ 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ................................................................................. 99

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53 Appendix A (Continued) Q33 INTRO: These next questions are about things that may have affected you as you pursued your {college major/current career} First, I am going to read a list of obstacles that you may have faced. Yes No RF DK Q33. Did you experience financial constraints? ........01 02 98 99 Q34. (Did you experience ) A lack of social support? ...........................................................01 02 98 99 Q35. (Did you experience ) Work that was too challenging? .....................................................01 02 98 99 Q36. (Did you experience) A lack of the guidance and information you needed to progress? 01 02 98 99 Q37. (Did you experience ) Discrimination based on your race? ...................................................01 02 98 99 Q38. (Did you experience ) Discrimination based on your gender? ...............................................01 02 98 99 Q39. [College Major Only] (Did you experience ) Not enough time to go to class? ......................01 02 98 99 Q40. Where there other obstacles you faced in pursuing your {college major/current career}? [SPECIFY]: ______________________________________________________ Q41 INTRO: The next questions are about the kinds of support you may have received in pursuing your {college major/current career}? Yes No RF DK Q41. Did you receive financial support from public sponsors such as grants or scholarships? ........ 01 02 98 99 Q42. Did you receive financial support from private sponsors such as family members? .................. 01 02 98 99 Q43. Did you receive social support and encouragement? ...............................................01 02 98 99 Q44. Did you receive support such as formal mentoring or apprenticeships? .......................... 01 02 98 99 Q45. Did you participate in study groups or receive academic assistance? ...................................... 01 02 98 99 Q46. Did you receive academic or career counseling? .......................................................01 02 98 99 Q47. Did you receive other kinds of support while pursing your {college major/current career}?

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54 Appendix A (Continued) [SPECIFY]: ______________________________________________________ Q48. People can be important examples and pr ovide inspiration in career decisions. How important were role models and mentors in your choice of {college major/current career}? Were they… a. Very important, .......................................................................... 01 b. Somewhat important, ................................................................. 02 c. Neither important nor unimportant, ............................................ 03 d. Somewhat unimportant, ............................................................. 04 e. Very unimportant, or .................................................................. 05 f. Did you not have a role model or mentor? ................................ 06 [GO TO Q50] g. REFUSED ................................................................................. 98 [GO TO Q50 h. DON’T KNOW ........................................................................... 99 [GO TO Q50 Q49. What was your relationship to this role model or mentor? Were they… a. A member of your family, ........................................................... 01 b. A peer, ....................................................................................... 02 c. A teacher or guidance counselor, .............................................. 03 d. A member of your community, ................................................... 04 e. Someone in a formal mentoring program, ................................. 05 f. Someone famous, or ................................................................. 06 g. Someone else? .......................................................................... 07 [SOMEONE ELSE SPECIFY]: ____________________________ h. REFUSED ................................................................................. 98 i. DON’T KNOW ........................................................................... 99 Q50. How would you describe your science classes in high school? Were they a. Highly engaging, ........................................................................ 01 b. Somewhat engaging, ................................................................. 02 c. Neither engaging nor boring, ..................................................... 03 d. Somewhat boring, or ................................................................. 04 e. Extremely boring? ...................................................................... 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q51. How would you describe your math classes in high school? Were they… a. Highly engaging, ........................................................................ 01

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55 Appendix A (Continued) b. Somewhat engaging, ................................................................. 02 c. Neither engaging nor boring, ..................................................... 03 d. Somewhat boring, or ................................................................. 04 e. Extremely boring? ...................................................................... 05 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 Q52 INTRO: I have just a few more questions, and these are about activities that may be related to your {college major/current career} that you may have participated in when you were younger. Yes No RF DK Q52 Did you participate in science or technology fairs? 01 02 98 99 Q53. (Did you participate in) Science clubs, teams, or honor societies? ............................................... 01 02 98 99 Q54. (Did you participate in) Math clubs, teams, or honor societies? ................................................... 01 02 98 99 Q55. (Did you participate in) Technology-oriented programs (such as A/V club)? .............................. 01 02 98 99 Q56. (Did you participate in) Summer camps? ............. 01 02 98 99 Q57. (Did you participate in) Volunteer organizations?......................................................01 02 98 99 Q58. Did you subscribe to any science or technology magazines?.......................................................... 01 02 98 99 Q59. (Did you) Work on any home science or technology kits such as chemistry or model building?...............................................................01 02 98 99 Q60. (Did you) Take trips to “hands-on” museums or displays of science, math or technology applications? ........................................................01 02 98 99 Q61. Are there any other science, technology, or math related hobbies or activities you participated in while growing up? [SPECIFY]: ______________________________________________________ Q62. How frequently did you participate in any science, technology or math related hobbies or activities when you were growing up? Was it… a. Very frequently, ......................................................................... 01 b. Somewhat frequently, ................................................................ 02

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56 Appendix A (Continued) c. Neither frequently nor infrequently, ........................................... 03 d. Somewhat infrequently, ............................................................. 04 e. Very infrequently, or .................................................................. 05 f. Never? ....................................................................................... 06 f. REFUSED ................................................................................. 98 g. DON’T KNOW ........................................................................... 99 That’s all the questions I have. The information you have provided is valuable and I appreciate your time. If you have questions, please call Heather Meikle at 813-974-4082. Thank you.

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57 Appendix B: Westat Interv iew Administration Report

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58 Appendix B Careers in Science Study Telephone Survey Methods Final Report February, 2007 Prepared for: University of South Florida Alliance for Applied Research in Education and Anthropology Tampa, Florida Prepared by: WESTAT Rockville, Maryland

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59 Appendix B (Continued) Project Overview High schools and universities in the Unit ed States are not producing sufficient numbers of students who pursue and persist in science, technology, engineering, and mathematics (STEM) careers to keep up with demand in those fields. Under a grant from the National Science Foundation, th e University of South Florida (USF) is working to understand how student career as pirations in STEM fields are either nourished or inhibited during high school and college. The project involves an extensive literature review, a cohort study of STEM career outcomes (examining the career paths of 82,000 1993/94 Florida high sch ool graduates) and a retrospective study of STEM career outcomes, conducte d with graduates of Florida postsecondary institutions who pursued majors in science, technology, engineering, or mathematics. The purpose of the retrospective study, ca lled the Careers in Science Study, is to provide a better understanding of influences on students’ choice or avoidance of STEM fields. It also examines wheth er different factors enhance or impede participation in STEM education and occupa tions. The findings will help provide a foundation for new policies concerning cl assroom, school, college, employer and societal supports likely to increase motivation and oppo rtunities to participate in STEM. Under a subcontract to USF, We stat conducted telephone data collection for the Careers in Science Study.1 This methods report summarizes the results of the telephone data collection effort. The report is organized into the following areas: Questionnaire design Sample design Interviewer training Data collection Data collection results and response rates Data preparation and delivery Questionnaire Design The Careers in Science Study questionnaire asked about respondents’ high school, college, and work experiences, including what kinds of extracurricular activities they participated in while in high school, what kinds of support (or lack thereof) they received while in college, and what fact ors they consider when choosing their career. It also asked who has influenced them in their decision-maki ng and their level of interest in math and science subjects. The initial questionnaire was designed for unstructured in-depth qualitative interviews. It contained mostly open-ended items and no in terviewer script. Th e Westat and USF 1 This study was approved by the Westat Institutional Review Board on April 25, 2006 under expedited authority.

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60 Appendix B (Continued) teams worked together to shape the questionnaire into an instrument suitable for telephone interview admi nistration. Table 1 lists the ch anges that were made to the original questionnaire and provides examples of some of them.

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61 Appendix B (Continued) Table 1. Changes made to the original Careers in Science Study questionnaire Type of questionnaire revision Example Reduced the number of open-ended items Developed introductory language at the beginning of the questionnaire and scripted statements throughout the questionnaire that helped segue from one section to the next Inserted likert-type scales where appropriate Original item Do you feel your parents or other family members played a major role in your career decisions? How so? Revised item To what extent did your parents or immediate family members encourage you to pursue your {college major/current career}? Did they encourage you a lot, encourage you somewhat, neither encourage nor discourage you, discourage you somewhat, or discourage you a lot? Created preset response lists for selected items (with an “other specify” option at the end of each list) Initial item Did you participate in any science or math related extracurricular activities either at school or in the community? What were they? Revised items Did you participate in science or technology fairs? Science clubs, science teams, or science honor societies? Math clubs, math teams, or math honor societies? Technology-oriented programs (such as A/V club)? Summer camps? Volunteer organizations? Did you subscribe to any science or technology magazines? Work on any home science or technology kits such as chemistry or model building? Take trips to “hands-on” museums or displays of science, math or technology applications? Are there any other science, technology, or math related hobbies or activities you participated in while you were growing up? Clustered items together by topic Questionnaire topic areas Post-secondary education information (number and type of degrees, schools at which the degrees were earned) Current enrollment and employment status, including type of program enrolled in and/or type of job held Job attitudes Factors influencing pursuit of educational and career goals Obstacles to and support for educational and career goals Interest and participation in scienceand mathrelated classes and activities

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62 Updated selected items with clearer explanations and simplified wording Initial item Briefly describe your primary job duties. Revised item What is your occupation? Please describe your job as you would to a layperson. After the Westat and USF team agreed on a final set of items, Westat converted the questionnaire into a format suitable for pa per-and-pencil telephone administration. This means the questions and scripts had to be organized in such a way that interviewers could move through the survey instru ment quickly and naturally. This phase of questionnaire development included formatting the respons e options with space for indicating which the respondent had chosen, adding the unread response options of “r efused” and “don’t know,” and creating simple skip pattern inst ructions. A contact script and informed consent language at the beginning of the questionnaire comple ted the instrument. Sample Design Careers in Science Study respondents were rand omly selected from a list of students who graduated from the Florida state university syst em within the past 6 years. USF received from the Florida Department of Educati on a list of 3,200 sample members, which included first and last name, along with a few demographic variables (e.g., date of birth, race, and gender). The USF research team, in turn, used internet search engines (e.g., PrivateEye.com and Intelius on Bigfoot.com ) to look up addresses and phone numbers for the sample members. Among the 3,200 sample members, USF identified a total of 164 phone numbers at which they were able to reach someone with the sample member’s name and 309 addresses without phone numbers. In some cases, multiple addresses were found for one sample member. USF provided the 473 names to Westat in two waves. USF delivered the Wave 1 list prior to the st art of data collection. It consisted of 365 names, 84 with phone numbers and addre sses and 281 with addresses but no phone numbers. Once the file was received, West at performed some cl eaning activities on it, including deleting duplicates and parsing contact information from one column into four columns (street address, city, state, and zip) for loading into the sample tracking system. Westat then used a subscription internet serv ice for telephone look up to verify or identify additional phone numbers for 77 of the 842 and find phone numbers for 181 of the 281. USF provided the Wave 2 list about halfway th rough data collection. This list contained 28 names with phone numbers but no addre sses and 80 names with addresses but no phone numbers (for a total of 108). Afte r cleaning and perfor ming a telephone look up on these cases, a list containing 81 cases with phone numbers was re leased for calling. The total sample size for the Careers in Sc ience Study was 339. Table 2 depicts the steps taken during sampling and the sample size at each. 2 Seven phone numbers had to be deleted from the sample because they had no ar ea code and the accompanying address information was not reliable or complete enough to deduce the correct area c ode. The possibility that these numbers could be for cell phon es further hindered efforts to assign a correct area code.

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63 Appendix B (Continued) Table 2. Sample size at each sampling step Step Sample Size USF receives from FLDOE sample list without contact information 3,200 USF identifies contact information 473 Phone (with or without address) 164 No phone (address only) 309 Westat identifies phone numbers 339 Wave 1 258 Wave 2 81 Interviewer Training On November 9, 2006, Westat conducted a f our-hour interviewer training with 6 experienced interviewers. A trai ning agenda appears in Exhibit 1.

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64 Appendix B (Continued) Exhibit 1. Careers in Scien ce Study Training Agenda Topic Time Lecturer 1. Introduction/Background………….… 6:00pm to 6:15pm Project Director 2. Voice Quality Demonstration…….…. 6:10pm to 6: 40pm Operations Manager 3. Frequently Asked Questi ons…………… 6:40pm to 6:50pm Group participation 4. Call Record…………………………… 6:50pm to 6:55pm Group participation 5. Response Code List……………………… 6:55pm to 7:00pm Group participation 6. Toll-Free Number/Inbound Calls…... 7:00pm to 7:05pm Operations Manager 7. Answering Machine Message…….... 7:05pm to 7:10pm Operations Manager 8. Non-Interview Report Form……………… 7:10pm to 7:15pm Operations Manager 9. Avoiding Refusals…………………… 7:30pm to 7:40pm Operations Manager 10. Contact Role Plays………………….. 7: 00pm to 7:15pm Operations Manager 11. Question by Question Review ……………. 7:15pm to 7:55pm Project Director BREAK ------15 minutes 12. Interactive 1……………………….…. 8:10pm to 8:30pm Group participation 13. Interactive 2 …………………….…… 8:30pm to 8:45pm Group participation

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65 14. Interactive 3 …………………….…… 8:45pm to 9:00pm Group participation 15. Roleplay 1 …………………………… 9:00pm to 9:30pm Group participation 16. Roleplay 2……………………………. 9:30pm to 10:00pm Group participation

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66 Appendix B (Continued) Data Collection Data collection began on November 10, 2006 and ended on January 31, 2007. The original 8-week field period was extended by 4 weeks. Shortly after data collection began, Westat noticed that a high number of sample members were refusing or hanging up before interviewers could finish explaini ng the purposes of the study. To alleviate this problem, Westat shortened the study introduction. Exhibit 2 shows the initial and revised study introduction wording. Refusal conve rsion efforts began on November 17, 2006. This is a procedure where highly experienced interviewers call b ack respondents who initially refused to participate, further explain the importance of the study and seek participation. Exhibit 2. Original and revised Careers in Science Study questionnaire introduction Original Hello, my name is [INTERVIEWER NAME ] and I’m calling from Westat, a survey research company in Rockville, Maryland. We are conducting a study for a research team at the Univer sity of South Florida. The purpose of the research is to find out more about what influences t he career choices of college graduates. You were carefully selected to participate in this study because of the unique insight you can provide to us. Revised Hello, my name is [INTERVIEWER NAME ] and on behalf of the University of South Florida. Through a grant from the National Science Foundation, we are conducting research about the career choices of college graduates. Supervisors regularly monitored intervie wer performance during data collection. Monitoring sessions lasted a minimum of 10 minutes and interviewers were provided with feedback on their performance and pointers for improvement, if needed. Approximately 10 percent of cases were monitored. Data collection results and response rates Of the 339 sampled respondents for whom USF and Westat were able to obtain contact information, 62 completed an interview. Table 2 shows the outcome or disposition of each case.

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67 Appendix B (Continued) Table 2. Number of cases assigned to each final disposition category Final disposition Number of cases Complete (C) 62 Language problem -interv iew cannot be conducted in English (LP) 2 Non-response – human or an swering machine contact made (MC, NM) 50 Non-response – no contact ever made (NA, NC) 7 Non-response – sample member is deceased (ND) 2 Sample member cannot be located (NL) 115 Sample member is not av ailable during the field period (NP) 1 Non-working telephone number (NW) 45 Refusal (RB) 55 Total 339 Response rates were calculated using the Council of American Survey Research Organizations (CASRO) respons e rate calculation guideline s, published in 1982. Survey disposition codes are central to the calcul ation of response rates because they help establish a case’s eligib ility. For cases where el igibility is unknown, CASRO recommends distributing them between eligib le and ineligible respondents in the same proportion as those of known eligibility are di stributed. Following these guidelines the Careers in Science Study final disposition code s were distributed across four categories – eligible respondents, eligible nonrespondents, unknown, and ineligible – as presented below. Eligible respondents (ER) – C (62) Eligible nonrespondents (ENR) -MC, NA, NC, NM, RB (112) Unknown (UNK) -NL, NW (160) Ineligible (IE) = ND, NP, LP (5) Westat then calculated the pr oportion of eligible responde nts and eligible nonrespondents among the population of known eligibili ty using the following formula: ER+ENR/ER+ENR+IE The results of this calculation showed that 97.2 percent of cases were known to be eligible and 2.8 percent were know n to be ineligible. This proportion was then applied to the unknown cases and the result (156 assigne d to the eligible nonrespondent category and 4 assigned to the ineligible category) added back into the ER and ENR cases. The response rate formula is: ER / ER + ENR + UNK cases assigned to ENR category

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68 Appendix B (Continued) Applying this formula, the re sponse rate is 23 percent. Data preparation and delivery At the conclusion of data collection, all case s were closed out with the assignment of a final disposition code. Data preparation staff key entered all the collected data. Each case was keyed twice to ensure accuracy. Westat produced a frequency on the keyed dataset and conducted a frequency review to en sure that all skip patterns were properly followed and all missing data properly accounted for. The frequency review included the following steps: Appendix B (Continued) 1. Check that responses fell within th e allowable range for each question. 2. Verify that the relationships of respons es across individual questionnaires were logical. 3. Ensure that the data accurately reflected the instrument’s skip patterns. A few data updates were made as a result of this review. For example, some open-ended responses were coded into an appropriat e preset response category and a few missing responses were filled based on other info rmation in the questionnaire. After the frequency review and data updates, the fina l dataset was provided to USF February 21, 2007 in SPSS format, along with freque ncies and a content listing.