The Effects of Career Motivation and Intellectual Curiosity on Proactive Career Behaviors in Undergraduate College Students A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNEOSTA BY Bethany J. Opsata IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Kenneth Bartlett and David Christesen, Advisors May, 2020 Bethany J. Opsata, 2020© i Abstract The rapid change in the contemporary business environment has made careers more complex and requires employees to take a more active role in their career in order to keep pace. This study explored the relationship between career motivation (including career insight, career identity, and career resilience), intellectual curiosity, and proactive career behaviors, measured two ways. The results indicate that there is a positive relationship between the career motivation components of career identity and career insight with proactive career behaviors, but not with the component of career resilience unless it is moderated by the general area of the student’s major. Additionally, student’s self-knowledge has a positive relationship with proactive career behaviors, as does intellectual curiosity when moderated by class standing. The implications for practice are that educators who want to encourage students to increase their voluntary participation in proactive career behaviors may be able to do so by focusing primarily on student’s career insight and career identity, and secondarily their self-knowledge and intellectual curiosity. Further research could be done developing interventions and measuring their impact on students’ career behaviors. And if resources limit the scope of future interventions for either research or practice, an emphasis on career insight will likely make the most impact on students’ career behaviors. ii Table of Contents Abstract ................................................................................................................................ i Table of Contents ................................................................................................................ ii List of Tables ................................................................................................................... viii List of Figures .................................................................................................................... ix Chapter 1: Introduction ....................................................................................................... 1 Background ......................................................................................................................... 3 Human Resource Development (HRD) .............................................................................. 5 Statement of the Problem .................................................................................................... 9 Purpose of the Study ......................................................................................................... 10 Research Hypotheses ........................................................................................................ 11 Conceptual Framework ..................................................................................................... 12 Significance of the Study .................................................................................................. 13 Definition of Key Terms ................................................................................................... 15 Career Motivation ......................................................................................................... 15 Career Identity .............................................................................................................. 16 Career Insight ................................................................................................................ 16 Career Resilience .......................................................................................................... 16 iii Intellectual Curiosity ..................................................................................................... 16 Proactive Career Behaviors ........................................................................................... 17 Chapter 2: Literature Review ............................................................................................ 18 Career Motivation ............................................................................................................. 18 Background ................................................................................................................... 18 Review of Career Motivation Studies ........................................................................... 30 Career motivation in employees. .............................................................................. 30 Career motivation in students. .................................................................................. 40 Intellectual Curiosity ......................................................................................................... 47 Background ................................................................................................................... 47 Review of Relevant Studies .......................................................................................... 49 Proactive Career Behaviors ............................................................................................... 50 Background ................................................................................................................... 50 Review of Relevant Studies .......................................................................................... 51 Similar Constructs ......................................................................................................... 55 Career readiness. ....................................................................................................... 55 Self-directed learning readiness. ............................................................................... 56 Continuous professional development. ..................................................................... 58 Chapter 3: Method ............................................................................................................ 60 iv Research Design................................................................................................................ 60 Population and Sample ..................................................................................................... 61 Protection of Human Subjects .......................................................................................... 61 Data Collection Procedures ............................................................................................... 63 Survey Response Rate....................................................................................................... 65 Variables and Instrumentation .......................................................................................... 65 Variables: Career Identity, Career Insight, and Career Resilience ............................... 67 Variable: Intellectual Curiosity ..................................................................................... 68 Variable: Proactive Career Behaviors ........................................................................... 69 Demographic and Moderator Variables ........................................................................ 70 Data Analysis Procedure ................................................................................................... 70 Reliability and Validity Testing of Instruments ............................................................ 71 Descriptive Statistics and Correlation Analysis ............................................................ 71 Regression Assumptions Tests ..................................................................................... 71 Hypothesis Testing........................................................................................................ 72 Reliability and Validity Testing of Instruments ................................................................ 72 Career Motivation Components .................................................................................... 72 Intellectual Curiosity ..................................................................................................... 77 Proactive Career Behaviors ........................................................................................... 77 v Common Method Variance Test ................................................................................... 78 Chapter 4: Results ............................................................................................................. 80 Descriptive Statistics ..................................................................................................... 80 Independent and dependent variables. ...................................................................... 81 Moderator variables. ................................................................................................. 84 Correlations among Variables ....................................................................................... 86 Regression Assumptions Tests ..................................................................................... 88 Homoscedasticity assumption. .................................................................................. 90 Linearity assumption. ................................................................................................ 92 Normality assumption. .............................................................................................. 95 Multicollinearity. ...................................................................................................... 95 Hypotheses Tests .............................................................................................................. 96 Result of Hierarchical Regression Analysis ................................................................. 96 Summary of Findings .................................................................................................. 104 Chapter 5: Discussion and Conclusion ........................................................................... 108 Discussion ....................................................................................................................... 108 Effects of Career Insight, Career Identity, and Self-Knowledge ................................ 109 Effects of Division of Major and Class Standing ....................................................... 111 Non-Supported Effects................................................................................................ 116 vi Theoretical Implications ................................................................................................. 117 Implications for the Theory of Career Motivation ...................................................... 117 Implications for the Theory of Proactive Career Behaviors ....................................... 118 Implications for Related Theories in Career Development ........................................ 120 Practical Implications...................................................................................................... 120 Implications for Higher Education .............................................................................. 120 Implications for Practitioners ...................................................................................... 123 Limitations ...................................................................................................................... 124 Limitations Due to Participant Characteristics ........................................................... 124 Limitations Due to Method ......................................................................................... 126 Limitations Due to Measures ...................................................................................... 127 Limitations Due to Underlying Assumptions ............................................................. 127 Recommendations for Future Research .......................................................................... 128 Conclusion ...................................................................................................................... 131 References ....................................................................................................................... 132 Appendix A: London’s (1983) Conceptualization of Career Motivation ....................... 155 Appendix B: Carson and Bedeian’s (1994) Instrument .................................................. 157 Appendix C: Noe, Noe, and Bachhuber’s (1990) Instrument ......................................... 158 Appendix D: London’s (1993) Instrument ..................................................................... 160 vii Appendix E: IRB Approval Letters .............................................................................. 161 Appendix F: Participant Invitations ................................................................................ 164 Appendix G: Participants by Major ................................................................................ 166 Appendix H: Demographics of Survey Participants ....................................................... 167 Appendix I: Instrument used for career identity, career insight, and career resilience .. 168 Appendix J: Instrument used for intellectual curiosity (Need for cognition scale – short form) ............................................................................................................................... 170 Appendix K: Instrument used for proactive career behaviors (career engagement scale) ......................................................................................................................................... 172 Appendix L: Instrument used for variables to understand the population ...................... 175 Appendix M: Histograms of Key Variables ................................................................... 177 viii List of Tables Table 1: Description of Measures ..................................................................................... 67 Table 2: Eigenvalues and Total Variance Explained for Career Motivation ................... 73 Table 3: Exploratory Factor Analyses of Career Motivation ........................................... 74 Table 4: Reliability Analysis of the Career Motivation Measure ..................................... 76 Table 5: Eigenvalues and Total Variance Explained ....................................................... 79 Table 6: Demographics of Sample and Population .......................................................... 81 Table 7: Descriptive Statistics of Dependent and Independent Variables ........................ 82 Table 8: Pearson Correlation Coefficients among the Variables ..................................... 87 Table 9: Regression Results for Proactive Career Behaviors-Activity ............................. 98 Table 10: Regression Results for Proactive Career Behaviors-Frequency .................... 102 Table 11: Regression Analysis Model Summaries .......................................................... 104 ix List of Figures Figure 1: Conceptual Framework ..................................................................................... 13 Figure 2: London's model of career motivation. From London & Noe (1990) ................ 21 Figure 3: Frequency Histograms for Dependent and Independent Variables .................. 84 Figure 4: Frequency Histograms for Moderator Variables .............................................. 86 Figure 5: Scatter plots of standardized residuals for dependent and independent variables ........................................................................................................................................... 91 Figure 6: Scatterplots for linearity assumption ................................................................ 94 Figure 7: P-P Plot ............................................................................................................. 95 Figure 8: A Moderator Relationship of Division between Career Resilience and Proactive Career Behaviors-Activity .............................................................................................. 100 Figure 9: A Moderator Relationship of Class Standing between Intellectual Curiosity and Proactive Career Behaviors-Activity .............................................................................. 100 Figure 10: A Moderator Relationship of Class Standing between Intellectual Curiosity and Proactive Career Behaviors-Frequency.................................................................... 103 Figure 11: Summary of Variable Relationships ............................................................. 107 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 1 Chapter 1: Introduction April, 2019: An undergraduate student, a month away from graduation, walks into her advisor’s office and says she’s having a hard time finding a job. Have you searched our career services office’s job sites? No. Have you done any informational interviews? No. Have you been watching your LinkedIn news feeds for recommended jobs to apply for? No, I don’t have a LinkedIn profile. Why not? Because it just seems like too much work to manage another social media platform. For educators, the above conversation seems to be getting more common. The rapid change in the contemporary business environment has made careers more complex and demands employees engage in proactive career self-management behaviors in order to keep pace (Akkermans, Brenninkmeijer, Hibers, & Blonk, 2012). But yet, today’s college student seems to be anything but proactive, and that will likely be increasingly problematic. De Vos, De Clippeleer, and Dewilde defined proactive career behaviors as “the deliberate actions undertaken by individuals in order to realize their career goals” (2009, p. 763) and found that they lead to desired career outcomes and feelings of career success. Proactive career behaviors meaningfully explain both objective and subjective measures of employability during the school-to-work transition (Okay-Somerville & Scholarios, 2017). Okay-Somerville and Scholarios found the effects of the graduate’s process (proactive career behaviors) was greater than their possession of human capital and their position of social capital. “There is no doubt that proactive career behaviors play a critical role in the ‘new’ career”, they wrote, and “For those involved in career PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 2 counseling, the findings suggest that students/graduates should be encouraged to engage in positive career management” (2017, p. 1287). In a theory-building article, Arie Greenleaf summarized his literature review by saying “These studies indicate that when individuals engage proactively in career building behaviors (e.g., networking, interning, working closely with university career centers, taking part-time jobs in alternative fields, actively connecting with alumni), they can significantly increase the likelihood of generating new, unforeseen opportunities and correspondingly improve their chance of gaining employment” (2014, p. 160). Because of this, career counseling is increasingly concerned with getting clients engaged in proactive career management (Greenhaus, Callanan, & Godshalk, 2010). Hirschi and Freund (2014) connected career engagement to proactive career behaviors. They found that little boosts in social support can have a significant effect on career engagement, but argue that we do not yet understand the full factors the promote career engagement. Clements and Kamau (2017) found proactive career behaviors mediated the relationship between mastery approach and perceived employability, and students’ commitment to their goal predicted proactive career behaviors. They also found proactive career behaviors were not negatively impacted by their academic and employment workload (Clements & Kamau, 2017). This indicates that students made time for proactive career behaviors, regardless of how busy they were, if they were committed to their goal. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 3 Background “Ensuring colleges are preparing students to get jobs in which they will feel engaged is just as crucial as urging employers to create engaging workplaces” (Lopez & Sidhu, 2013, Implications section, para. 2). In order for students to engage in their careers, they should first find engagement in their major. And that’s especially difficult when so many students struggle to even pick a major in the first place. Ng and Feldman (2009) wrote about the need to understand vocational indecision. They argued: “vocational indecision can have major short-term and long-term effects on individuals and their employers. For example, vocational indecision in college may lower students’ sense of self-efficacy about their career management skills and the quality of their employment options” (pp. 309-310). Ng and Feldman (2009)’s longitudinal study of career indecision in college students in Hong Kong demonstrated the importance of the formation of identity in career decision making. They found that college students first develop an overall sense of identity, and at a later time, develop that into more specific identities as a student and an anticipatory identity for their work role. Helping students then, explore and develop a vocational identity should be important for academics and practitioners alike (Ng & Feldman, 2009). There has been a significant push in the United States to increase the number of students, especially women, in the science, technology, engineering, and math (STEM) fields and Kerr and Kurpius (2004) posited that enhancing students’ career identity would have significant impact toward that goal. They found that a woman who sees herself as a PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 4 scientist is much more likely to stay with their field than one who only sees herself as a college student. A study by De Vos, De Stobbeleir, and Meganck (2009) demonstrated how college students’ attitudes toward their career should be a valued concern of human resource development researchers and practitioners in that their pre-employment beliefs become part of their psychological contracts for their hiring organization. They recognize time as a student as the pre-employment state of a psychological contract formation (the anticipatory psychological contract) and show that this contract will impact organizational commitment and expectations post-hire in ways that employers should not neglect. The level of organizational commitment is also impacted by their commitment to their overall career. Career commitment is different from organizational commitment and is a strong moderator between organizational commitment and perceived supervisory support and turnover intentions (Chang, 1999). Additionally, Chang argued that an individual’s attitude toward their career will likely influence their attitude toward their current and future (1999). Based on this, we can see that an understanding of organizational commitment, which is important to HRD practitioners and researchers alike, is short-sighted unless also viewed in the broader context of an employee’s total career commitment. A career focus while in college is important for the student as well. The transition from school to work is the first major transition many make in their careers and that often helps set a pattern for how they respond to changes in the future (Ng, & Feldman, 2007). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 5 A successful launch into one’s career is extremely important, as it often sets the trajectory of a career by indicating a graduate’s potential to future employers (Peck, 2010). Additionally, Bridgstock (2010) demonstrated that career identity, a component of career management competence, was a significant predictor of early career success and called universities to build programs to help develop career identity in students. Swanson and Holton defined development as “the planned growth and expansion of the knowledge and expertise of people beyond present job requirements” (2009, p. 231). It is important to understand how undergraduate students plan their growth and the steps they take for the expansion of their knowledge and expertise. Barron (2006) saw the need for research in this area and asked (p. 194), When does learning in school lead to the independent pursuit of knowledge once the formal course is over? Once interest is sparked, what kind of resources do learners seek out, and how might we conceptualize such processes of self-initiated learning? Finally, can we nurture learning by seeding information learning environments with supportive resources that help sustain self-perpetuating processes? Barron went on to explore those questions through a qualitative method, but also opens the door for similar research in this area, including the current study. Human Resource Development (HRD) Calling for research into the career motivation of foreign-born workers, Lopes directly states this as an issue for HRD by writing: PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 6 In 1983, London introduced the concept of career motivation, which “is defined as the set of individual characteristics and associated career decisions and behaviors that reflect the person’s career identity, insight into factors affecting his or her career, and resilience in the face of unfavorable career decisions” (p. 620). From a HRD perspective, an organization could take steps to increase levels of career motivation to reduce turnover (because people are more motivated and happier), increase employee morale, and increase productivity. Employees would increase their own awareness about motivation; where it comes from and what it means. (Lopes, 2006, p. 479) This study supports the career development component of HRD. McLagan’s (1989) wheel of human resource practices identified career development as one of the three primary foci of HRD along with training and development (T&D) and organization development (OD). Gilley, Eggland, and Gilley’s collegiate-level textbook (2002) also include career development as a main principle of HRD, placing it alongside individual development, organization development, and performance management as well. For Gilley et al., career development focuses on providing the analysis necessary to identify the individual interests, values, competencies, activities, and assignments needed to develop skills for future jobs (development). Career development includes both individual and organizational activities. Individual activities include career planning, career awareness, and utilizing career resource centers. (2002, p. 15) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 7 Swanson and Holton (2009) limit HRD’s principle components to just T&D and OD relegating career development to a context or application of HRD instead of a guiding component. It will remain important, though, as Cummings and Worley (2014) identify career planning and development as one of the key possible interventions in their classic OD textbook. They stated: Companies have discovered that organizational growth and effectiveness require career development programs to ensure that needed talent will be available. Competent managers are often the scarcest resource. Many companies also have experienced the high cost of turnover among recent college graduate, including MBAs; the turnover can reach 50% after 5 years. Career planning and development help attract and hold such highly talented people and can increase the chances that their skills and knowledge will be used. (p. 397) Although this description of why career planning and development is important may seem like it would fit better in a human resource management textbook, there is no denying that if “HRD is a process of developing and unleashing expertise for the purpose of improving individual, team, work process, and organizational system performance” (Swanson & Holton, 2009, p. 4), then starting with the best inputs available would go a long way to improving the ultimate performance output. Even though career development seems to fit well with the definitions and models of HRD, it doesn’t seem to have much of a place in the research. Egan, Upton, and Lynham (2006) wrote: PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 8 Our recent exploration of AHRD publications identified fewer than 40 total articles to date in Conference Proceedings and only three in the four AHRD- refereed journals (Advances in Development Human Resources, Human Resource Development Quarterly, and Human Resource Development Review) from 1996 to 2005 that specifically discussed CD. (2006, p. 443) Additionally, they argued “Further connections between CD theory and literature and HRD will enhance HRD research and practice. With its rich history and theoretical frameworks, CD is important to HRD and deserves more attention in HRD literature” (Egan et al., 2006, p. 472). Clearly Egan et al. see value in career development as a part of HRD research. McDonald and Hite (2005) certainly agree. They wrote: “The overriding message appears to be that HRD needs to both reclaim and reinvent its involvement in career development” (p. 421). Before proceeding, it is important to note the underlying context for the study of career and career development in this study. This study approaches career from Westernized, and particularly US assumptions. These assumptions include a belief in individual choice when it comes to career, an assumption that may not be as strong globally. In addition, it is important to recognize that individual choice is often a result of opportunity and privilege that is unequally distributed across people, contexts, and economies. David Blustein (2013) has shed light on the limited perspective that career research has traditionally taken and has called for a new perspective of working. He argues working should be viewed from both a marketplace and a caregiving context. This research will focus solely on the marketplace context and approaches it with an PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 9 underlying assumption that career choice is a privilege that should be valued for ourselves and for others. Statement of the Problem Changes in the past decades have rewritten the traditional organization-based career (Sullivan & Baruch, 2009). Crocitto, Arthur, and Rousseau (1998) identified the rise of the boundaryless career, where individuals can expect their career to span a wide range of employers over their lifetime instead of the classical expectation of working their way up on one company over the course of their full career. An individual today must be nimble, actively seeking opportunities to advance their career inside and outside of their current organization. In this context, then, people are increasingly responsible for the management of their own careers (Arnold & Jackson, 1997), often referred to as a protean career (Hall, 2002; Briscoe & Hall, 2006; Briscoe, Hall, & Farutschy DeMuth, 2006), or career self- management (Stickland, 1996). Professionally-oriented students that are graduating college with a low level of motivation toward their career will likely cause lasting impact for their future employers. Engaging workers in their career is important for employers, but even more importantly, that must begin during their years of professional preparedness through college, when their curiosity is sparked, they are learning how to learn, and gaining the initial skills that will set their career development trajectory for the rest of their lives. Understanding what influences students to voluntarily initiate activities that will benefit their career is important for educators and future employers. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 10 There is a wide range of literature that has explored and tested the construct developed by London (1983) that he referred to as career motivation. However, it’s role in proactive career behavior has not yet been explored. Additionally, further investigation is needed to determine if proactive career behavior is influenced by traits that are not specific to careers, such as a generalized construct of intellectual curiosity. Purpose of the Study There is currently a gap in the literature explaining the engagement students show toward their career. Although we know active career management is important, there is very little literature to show how it can be developed in students. The purpose of this study, then, was to identify the relationships between career insight, career identity, career resilience, intellectual curiosity, and proactive career behaviors such as career exploration and networking in undergraduate college students. If these relationships are understood, future research can be conducted to develop interventions for increasing the frequency of proactive career behaviors. This research is important for students, educators, and employers alike. It will help both students and educators understand the predictors of early career success Bridgstock (2010), which should foster an increase in actions toward their careers, better enabling graduates to start their career on an upward trajectory. For employers, this study will provide insight into the pre-employment psychological contract and career mindfulness of incoming new graduates (De Vos & De Stobbeleir et al., 2009). This should translate into an understanding of the career engagement and commitment of their new employees. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 11 This study addressed the following main research questions. 1. Do the components of career motivation (career insight, career identity, and career resilience) and intellectual curiosity help explain students’ voluntary career behaviors? 2. How does a student’s major, having completed an internship, and their class standing moderate the above relationships? Research Hypotheses The seven research hypotheses were proposed based on the supporting literature of the field and conceptual framework of this study. The first four address the predictors of students’ career behaviors. Hypothesis 1: Student career insight will be positively related to proactive career behaviors Hypothesis 2: Student career identity will be positively related to proactive career behaviors. Hypothesis 3: Student career resilience will be positively related to proactive career behaviors Hypothesis 4: Student intellectual curiosity will be positively related to proactive career behaviors. The remaining three hypotheses proposed a moderating effect of having completed a required internship, students’ majors, and their class standing on the relationships in hypotheses one through four. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 12 Hypothesis 5: Having completed a required internship/practicum will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. Hypothesis 6: A student’s major will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. Hypothesis 7: A student’s class standing will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. Conceptual Framework As defined above, career motivation is a combination of career identity, career insight, and career resilience. All three of these served as independent variables in this study. It was expected that participants’ major, their class standing, and whether or not they have already completed a required career-related experience such as an internship or practicum would moderate the relationship between these variables and proactive career behaviors. Intellectual curiosity, a more content-neutral variable also served as an independent variable. The conceptual framework, then, can be seen in Figure 1. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 13 Figure 1: Conceptual Framework Significance of the Study The need for career motivated employees is clear. The engagement of workers is declining and this is costing employers billions of dollars each year (Saks & Gruman, 2014). Although there are many antecedents to engagement that are organization controlled like work environment and leadership, characteristics of the individual, like self-efficacy and conscientiousness, do also contribute (Saks & Gruman, 2014). Understanding the engagement of the future workforce begins with understanding the motivation of college students. Polach stressed the importance for HRD of studying college students: HRD professionals must understand new college graduates because they are a significant source of new employees in the organization…. Further, organizations hire college graduates based on their long-term potential for becoming future leaders; thus, it is paramount that development professionals understand college graduates’ hopes, expectations, and challenges so that, early on, graduated can be Intellectual Curiosity Proactive Career Behaviors Career Motivation Components: Career Identity Career Insight Career Resilience Required internship completed Class standing Major PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 14 provided with the specific development and coaching strategies they need to grow into the role of leader and influencer over time. (Polach, 2004, p. 6) Holton also argued that understanding the recent college graduate is important for HRD. In an article designed to reconceptualize new employee development, Holton wrote: All employees, regardless of experience level, bring with them accumulated learning, attitudes, and values shaped by previous cultures and work experiences. Considering the highly interactive nature of the learning process and an emphasis on congruence between the individual and the organization, it is likely that prior learning will influence entry success. Trainability research supports the notion that preentry attitudes, expectations, and motivation might affect training and, by extension, socialization outcomes. (Holton, 1996, p.236) Holton also clearly made the connection between organizational entry and HRD’s responsibility. “The job attitudes reported here suggest that HRD has an opportunity to enhance the productivity of new college graduates and make a substantial impact on the organization’s bottom line if a more comprehensive model is developed” (Holton, 1995, p. 76). Much of the responsibility for this organization impact, then was laid at the feet of educators. In the same study, Holton concluded: This study also has important implications for academic programs preparing HRD practitioners. First, programs should include training in the professional skills necessary to adapt to an organization. Second, the classes should be structured more like the “real world” to condition students to the expectations and cultures in PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 15 which they will work after graduation. While this is not a popular change with students, it is a necessary one. Third, emphasis must be placed on field experiences for students. Fourth, academics must hold themselves accountable for successful organizational entry, not just job placement. (Holton, 1995, p. 75) Although Holton was speaking specifically to academic programs that will prepare HRD practitioners, these same responsibilities should fall to all professional preparedness programs and is one of the main motivations for this current study. Watkins and Marsick (2014) saw an individual who can learn and adapt to be vital to organizations and the development thereof to be vital to HRD. I believe the development of these individuals begins during college through the building of students’ proactive career behaviors and this study is designed to seek support for that position. Definition of Key Terms Every field has a wide range of specific language, including the field of career development. In addition, the same word may have different connotations in different contexts. It is important, then, to have clarity of the definitions of the key terms used in this study. The terms defined in this section: career motivation, career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors, also served as the key variables in the study. Career Motivation Career motivation is defined as “the set of individual characteristics and associated career decisions and behaviors that reflect a person’s career identity, insight into factors affecting his or her career, and resilience in the face of unfavorable career PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 16 conditions” (London, 1983, p. 620). It is the arousal, direction and persistence of behavior toward one’s career. Career Identity Career identity includes the “the extent to which one defines oneself by work. It consists of job, organizational, and professional involvement and needs for advancement, recognition, and a leadership role” (London & Noe, 1997, p. 62). Career identity is the direction component of career motivation. Career Insight Career insight is “the ability to be realistic about oneself and ones’ career and to put these perceptions to use in establishing goals. It consists of establishing clear career goals and knowing ones’ strengths and weaknesses” (London & Noe, 1997, p. 62). Career identity is the arousal component of career motivation. Career Resilience Career resilience is “the ability to adapt to changing circumstances, even when the circumstances are discouraging or disruptive” (London & Noe, 1997, p. 62). Career resilience is the persistence component of career motivation. Intellectual Curiosity Intellectual curiosity includes “Tendencies to seek out, engage in, enjoy, and pursue opportunities for effortful cognitive activity” (von Stumm et al., 2011, p. 577). This is very similar to Cacioppo, Petty, and Kao’s (1984) definition of need for cognition, “an individual’s tendency to engage in and enjoy effortful cognitive endeavors” which provides the foundation for their Need for Cognition Scale. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 17 Intellectual Curiosity has overlap with the Big-Five personality characteristic of Openness to Experience, which often viewed as a multi-dimensional construct including six facets of Fantasy, Aesthetic Sensitivity, Attentiveness to Inner Feelings, Actions, ideas, and Values. According to von Stumm et al. (2011), the Ideas sub-construct is often synonymous with intellectual curiosity, but the other facets of Openness to Experience do not overlap intellectual curiosity when tested. This study will be using the more specific definition of effortful cognitive activity and term intellectual curiosity, instead of the broader definition of Openness to Experience, as it better fits the research’s purpose. Proactive Career Behaviors Proactive career behaviors are actions taken by learners to advance their professional knowledge, skills, or abilities in their intended career. These activities must be voluntary and initiated by the learner themselves. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 18 Chapter 2: Literature Review This chapter presents a review of the literature relevant to the study. First, background information is provided about the construct of career motivation, then research that studied career motivation in employees is reviewed. Special attention is then given to how career identity, career insight, and career resilience has been studied in students. Second, background information and a review of the literature is provided for intellectual curiosity. Finally, background information and a review of the literature is provided for proactive career behaviors, including a look at similar constructs to proactive career behaviors as studied here. Career Motivation Before reviewing the literature of career motivation, an overview of the background of the construct is useful. Background During the 1960s and 70s, research branched from looking at just general motivation to a more contextual concept of motivation in education and jobs. One such branch was studying the construct achievement motivation, where researchers were seeking to understand the lower levels of achievement motivation exhibited by women as compared to their male counterparts (Maccoby & Jacklin, 1974). Researchers were concerned as this lower level of achievement motivation seemed to be manifesting itself in disproportionately fewer women in science and managerial ranks. In 1976, Helen Farmer, Professor Emerita of the University of Illinois, Champaign-Urbana, published a PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 19 theory building article in the Counseling Psychologist lighting a path between achievement motivation and career motivation (Farmer, 1976). The idea of career motivation was not an established construct at the time. Articles and researchers may have used the words, but certainly didn’t all use it in the same way. For example, although Peck’s 1975 study was called “Distinctive National Patterns of Career Motivation”, what was actually studied was based on Super’s (1957) occupational values inventory (altruism, security, prestige) and the word motivation rarely appears in the article except in the title. Farmer, though, began to define and push for further research into career motivation as she believed “Achievement and career motivation in girls differs from that of boys as a result of yet poorly defined factors” and that “comparative studies of the effect on motivation of various legal, economic and social changes could potentially influence social reform as well as educational and counseling practice” (Farmer, 1976, p. 13). Farmer began testing career motivation with papers published in 1980 and 1983. Both studies used career motivation and achievement motivation as criterion variables, looking for relationships with a range of environmental and psychological predictor variables. Her measurement for career motivation, though, was based on Holland’s (1977) career choice occupational daydreams which didn’t lead to furthering career motivation as a unique construct (Farmer, 1980; Farmer & Fyans, 1983). In 1984 Farmer focused on developing a measurement for the conflict between home and career faced by college women, expecting career motivation to be a link. Although it provided an interesting instrument for measuring aspects of home and career conflict, it didn’t add PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 20 much to the development of career motivation as its measurement was weak and ill- defined. The study of career motivation then moved to be the focus of Manuel London. London received his Ph.D. from The Ohio State University in 1974 and in 1983 was serving as Staff Psychologist at AT&T. He left AT&T in 1989 to join the faculty at the State University of New York at Stony Brook where he has been since, currently serving as the Dean of the College of Business (“Manny London, Ph.D.”, n.d.). His theory building article in the Academy of Management Review argued that the terms of the day, motivation, work motivation, and managerial motivation, were too limited and constrictive in their coverage. He presented career motivation from a broader view, including work motivation, managerial motivation, and a “wide range of career decisions and career behaviors” (London, 1983, p. 620) which include both individual characteristics and situational factors. He defined career motivation as “the set of individual characteristics and associated career decisions and behaviors that reflect a person’s career identity, insight into factors affecting his or her career, and resilience in the face of unfavorable career conditions” (p. 620). London’s theory conceptualized career motivation as multi-dimensional. First, he argued that career motivation is comprised of three components that are characteristics of individuals which he labels as career identity, career insight, and career resilience. Career identity was defined as “how central one’s career is to one’s identity”, career insight as “the extent to which the person has realistic perceptions of him or herself and the PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 21 organization and relates these perceptions to career goals”, and career resilience as “a person’s resistance to career disruption in a less than optimal environment” (p. 621). When seen all together, London’s model is complex and highly detailed. It includes three different factors (career identity, career insight, career resilience), in relationship with three components (individual characteristics, situational variables, career decisions and behaviors), and further breaks down all of that into subdomains and variables. The complexity stems from the fact that he was not presenting a new model from a clean slate, but rather trying to establish a framework to understand the career motivation of managers from a myriad of existing variables. By the time the model is complete there were 108 different variables included. A representation of his framework can be seen in Appendix A. Additionally, a graphic representation of his model as published by London and Noe (1990) can be seen below. Figure 2: London's model of career motivation. From London & Noe (1990) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 22 With so many angles to explore, it became a theory of choice for future researchers. Over the 30 years since its publication, London’s article has been cited over 125 times in journals indexed in the Web of Science database. The next steps in the refinement of the theory were the development of an instrument to measure the components and to test its correlations to other constructs to see if it was a unique construct. In a theory-building article, Grzeda (1999) argued that career motivation provides an excellent framework for both research and practice, particular because it “extends the career development framework to career change” (p. 241), and legitimizes career change and encourages more research in this area” (p. 242). While London was developing the theory of career motivation, Blau (1985a) published an article titled “The measurement and prediction of career commitment”. To start, he takes his definition of career commitment from Hall (1971) as “the strength of one’s motivation to work in a chosen career role” (p. 59) which he believed to be different to the commitment to one’s job or one’s organization. But while building his theoretical framework for predicting career commitment, he drew extensively from London’s (1983) model. His variables overlapped as well. Most notably, Blau studied job involvement which he defined as “the degree to which the individual identifies with a job” (1984, p. 281) which is very similar to London’s career identity. In fact, Blau even admitted he was studying the same thing as London. In the opening paragraphs he wrote, “Another purpose of this study is to investigate the importance of specific situational and individual difference variables in predicting career commitment” (p. 277). Then in his conclusion he writes, “Turning to the second study purpose, a partial empirical test of PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 23 London’s (1983) model was successfully made. Two individual and two situational characteristics were found to be the best predictors of career commitment” (p. 287). Clearly Blau saw his career commitment as being equivalent to London’s career motivation, just under a different name. In fact, a casual reader of Blau probably wouldn’t have even know that London’s model wasn’t actually called career commitment. Blau will eventually state that “One approach to understanding career motivation is by investigating an individual’s career commitment” (Blau, 1988, p. 284) showing he believed they are intimately related constructs. Over the decade, Blau continued to refine his theory of career commitment through instrumentation and testing (Blau, 1985a, 1985b, 1988, 1989). Blau’s work also sparked continuing research in an ever-widening field having been cited even more frequently than London’s work at over 190 times in the Web of Science. One of these in particular will be influential in the furthering of the body of literature. Carson and Bedeian (1994) developed an instrument to measure career commitment that will be used and referenced extensively in subsequent research, a 12-item measure they name the Career Commitment Measure (CCM) which can be seen in Appendix B. The next voice to enter the career motivation conversation is that of Raymond Noe. Noe, as senior author teamed with Ann Noe and Julie Bachhuber, revisited London’s 1983 theory-building article in order to find which other known constructs would correlate with career motivation (Noe, Noe, & Bachhuber, 1990). Their factors of concern included career stage, work role salience, position, distance from career goal, match between individual and organizational career plans, managerial support, and job PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 24 characteristics as compared to the career motivation domains of career insight, career identity, and career resilience. In order to test for career motivation, though, they needed to build a measurement as none existed at the time. The authors developed a twenty-six- item scale to measure career motivation. Tests of intercorrelations and internal consistency reliability indicated three separate factors that corresponded to the career motivation domains. Items for each domain were then averaged to get a single score for career identity (8 items), career insight (5 items), and career resilience (13 items). The items used can be seen in Appendix C. Noe et al.’s (1990) results showed a significant correlation between career motivation and work role salience and job characteristics indicating that the more important a career was to a person and the more they found their job motivating, the more likely they were to have a high level of career insight, identity, and resilience. Other factors were not, or only partially, supported as being predictors of career motivation. Overall, the study did show support for London’s (1983) 3 dimensions of career motivation, but calls for further investigation into the theory. They end the article by stating: The increasing emphasis on the development of career planning and management systems by organizations indicates that further systematic study of the theory of career motivation is necessary in order to better understand the implications of career development interventions and individual career attitudes on work attitudes, behaviors, and organizational productivity. (Noe et al., 1990, p. 354) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 25 Manuel London himself would take the next step along that journey. In 1993 London looked for the relationship between the career motivation components and empowerment and supervisor’s support for career development. He opened by stating that: The concept of career motivation applies motivation theory to understanding career plans, behaviors, and decisions. To date, there has been theorizing about the content of career motivation and the association between career motivation, situational characteristics and behaviors (London, 1983, 1985, 1988). However, there has been limited empirical work to measure the components of career motivation and their relationships to situational characteristics. (p. 55) London will proceed to develop an instrument for measuring career motivation and compare its relationship to empowerment and support for career development. The first part of the study was to develop scales for career motivation. London used 17 items which were measured on a five-point scale. A factor analysis on London’s items does provide support for a 3-component theory of career motivation. He further tested that with a second study to evaluate the instrument’s reliability. The same 17 questions were used, although some are re-written for increased clarity. The items are recorded in Appendix D, and are deemed by London to be “those recommended for future use of this scale” (p. 63). In addition to presenting instrumentation, London also “provides some evidence that supervisor’s views of their subordinates’ career motivation are associated with the PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 26 support and empowerment the subordinates consider they receive from the supervisor” (1993, p. 67). The next key piece of research in the development of a theory of career motivation came through a collaboration of two of our key theorists to date: London and Noe. In 1997 they jointly published “London’s Career Motivation Theory: An Update on Measurement and Research” in the Journal of Career Assessment. They said, “The purpose of this article is to describe London’s model, examine how the domains of career motivation have been measured, present the results of a convergent validity study of three career motivation measures, and review research stimulated by the model” (London & Noe, 1997, p. 61). The London and Noe article is important in that it provided a theoretical foundation for career motivation that is missing in London’s original work. It provides a connection between career motivation to some of the most influential theories in career development and motivation including Holland (1973), McClelland (1965), Bandura (1977), and Super (1957). Another important contribution of the paper is a review of measurements that have been used for career motivation. One such instrument was a two- day assessment center used by London (1985). The assessment center provided extensive information about career motivation, but is too costly to be considered by most researchers, especially with a meaningful sample size. Also described were paper-and- pencil instruments like London’s (1993) 17-item test that has already been described, a test that focuses on feelings and attitudes. Also, Noe et al.’s (1990) instrument, which focuses more on behaviors, is reviewed. Thirdly, Blau’s (1988, 1989) measure of career PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 27 commitment is included as they argue it “contains items that are similar to that of career identity” (London & Noe, 1997, p. 66). And finally, they reviewed Carson and Bedeian’s (1994) instrument of career commitment, signally further confirmation of the significant overlap between career motivation and career commitment. They then administered London’s (1993), Noe et al.’s (1990) and Carson and Bedeian’s (1994) instruments to 336 adults. They found moderate convergent validity between the London and Noe et al. instruments, and high convergent validity between London and Noe et al.’s career insight and career identity with those of Carson and Bedeian. However, they found Carson and Bedeian’s measure of career resilience to be very different from the others with a focus more on the perceived value of work effort than on career resilience. Finally, London and Noe presented a number of ideas for future research and practice to “help increase our understanding of the antecedents and consequences of career motivation” (p. 73). It is the intent of this paper to contribute to that understanding. Grzeda and Prince published an article in 1997 looking at the validity of existing measures for career motivation. They took and rejected items developed by both London (1993) and Noe et al. (1990) to end with a 30-item instrument. It is important to note that Grzeda and Prince (1997) sampled employees who had lost their job due to downsizing. Because of this, their questions were worded in the past tense, and had more of an emphasis on career resilience. The 30 items where then combined into summative indices. They coded the three main dimensions of career identity, career insight, and career resilience as latent variables and the 6 summative indices from the scales as PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 28 indicator variables. To measure discriminate validity, they expected each indicator variable would load to only one latent variable. Although this was the case in all but one indicator variable (organizational identification), goodness of fit indices showed the model was a poor fit for the data. After two changes (dropping organizational identification and including reliance on feedback in both career insight and identity), the model was shown to be a much better fit. And although feedback was no longer tied to just one latent variable, it was only significant in its relationship to career identity which does support the evidence for discriminant validity. A further test of the measurement by Grzeda and Prince (1997) was to look for convergent validity. They did this by taking results from other instruments and setting them up as exogenous variables to compare against the endogenous variables from their model. Within their sample of people in career transitions, the career resilience models seemed to have more convergent validity than did career insight or identity. This may be partially explained though, by their narrow interpretation of especially career insight. While career resilience was compared to creative, autonomy, persistence, and perseverance; and career identity was compared to upward mobility, managerial competence, job involvement, and an alternate measure of career identity; career insight was only compared to a need for change. They recommend further testing and replications for career motivation instruments, including in a wider range of populations. A 1997 article by Albert King also presents a model of career motivation. He states, “The social psychological dimensions that govern the interrelationships and energy-giving states of a business organization’s elementary building blocks – its PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 29 employees’ self-identity, self-insight, and career resilience – we call the force of commitment” (p. 293). He defined each of these as very similar to the London and Noe definitions, yet barely referenced their work at all. Instead, he situated his model in the work of Meyer, Paunonen, Gellatley, Goffin, and Jackson (1989) on organizational commitment. He then argued that self-identity, self-insight, and career resilience develop independently of each other and as they build they also build career commitment through an eight-phase process. He then simplified the eight phases into four steps: awareness and concern, experimentation and options, partial acceptance and momenta, and finally convergence-congruence and affective commitment. He supported his model with a case field study. King’s article deserves attention in this literature review for what it does as well as what it doesn’t do. What it doesn’t do is present a new and unique way of looking at career motivation. It takes the ideas of London, Noe, and Blau and just repackages them slightly. What it does do, though, is show us that even by 1997 the ideas of career motivation and career commitment were becoming common in the field and being linked to additional concerns such as organizational commitment. Deemer, Smith, Thoman, and Chase sought to develop a relevant instrument (2014). The study evaluated the Subject Science Attitude Change Measures (SSACM), as self-report instrument “for assessing change in high school students’ science attitudes as a function of a given motivational intervention” (p. 489). Using a factor analysis, they sought motivation factors in the overall assessment. They found four. One factor was identified as a general motivation toward science. The other three were identified as PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 30 intrinsic science interest, science career identity, and science self-efficacy. These three clearly overlap with the theory of career motivation originated by London and the authors even title the paper “Precision in Career Motivation: Testing the Subjective Science Attitude Change Measure”, however their literature review contains no references to the theoretical foundation of career motivation demonstrated here. On one hand we may say their literature review was lacking, but on the other it is good independent confirmation of the connection between career identity, interest, and self-efficacy to motivation. Review of Career Motivation Studies With an understanding of the theory of career motivation, it is important to next look at how the theory has been explored and tested through research. In some studies career motivation was studied as a whole, with others focused on one of the particular components instead of using all three. Fitting with that, literature with be separated into its particular area of emphasis and then described chronologically within the section. First, how career motivation has been studied in employees will be reviewed, and then its testing with a student population. Career motivation in employees. London himself participated in studies on career motivation. In one of the earliest works post theory development, London and Bray conducted an assessment center from which they found a manager’s behaviors are critical to the career motivation of their employees (1984). Then in 1995, London teamed with Wolf, Casey, and Pufahl to explore a connection between career motivation and training behaviors. Although they found no significant relationship between them across the full sample, they did find that PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 31 career motivation influenced training behavior differently at different points in a person’s experience level (Wofl, London, Casey, & Pufahl, 1995). Studying current employees, Aryee, Chay, and Chew (1994) found both predictors to and impacts of career commitment. First, they found job characteristics like the expected utility of a current job to predict high career commitment. They also found career commitment to contribute different things at different career stages. Participants with a high career commitment at early stages of their career were more likely to show high levels of career satisfaction, where participants at later stages of their career with high career commitment were more likely to show high organizational commitment. This showed the need for career commitment and motivation research at all stages of the career as it is a dynamic construct that changes over a lifetime. Kidd and Smewing (2001) investigated the role of supervisor support in career motivation and organizational commitment. They found a significant positive relationship between supervisor support and organizational commitment; those with a supervisor who encouraged their learning and development were much more likely to remain with their company. No relationship was found, though, between supervisor support and career motivation. This showed that although employee retention to their company is dependent on good managers, a good manager does not necessarily influence an employee’s commitment to their career field. On the other hand, a 2004 study by Day and Allen showed a connection with career motivation and management behaviors. They found that career motivation was a strong mediator between career mentoring and protégé success. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 32 Kidd and Green (2006) sought to understand why scientists in the UK decided to leave the field after they had already joined it. They hypothesized that demographic and work-related variables would influence the career resilience, career identity, and career planning (using Carson and Bedeian’s (1994) wording for career insight) of research scientists. These, in turn, would influence their intention to leave science. Using a longitudinal survey with a final sample of 220 participants, they found significant support for career motivation’s importance. Higher scores in the three career motivation measures increased the likelihood the participant intended to stay in science. Lebanese bank employees were surveyed to compare career commitment (as defined similarly to career motivation) to career success (Ballout, 2009). It was found that a higher level of career commitment did significantly relate to a higher level of both salary and career satisfaction, but only through the moderator variable of self-efficacy. For those with a medium to high self-efficacy, the relationship was significant, but there was no a relevant relationship between career commitment and career success for those with low self-efficacy. Pas, Peters, Doorewaard, Eisinga, and Largo-Janssen (2014) used London’s (1983) conceptualization to study the career motivation of Dutch women physicians. They compared career motivation with 4 different goal frames of being an ideal worker and an ideal mother. Adapting items from three different instruments, they identified dimensions of career centrality, career insight, and career ambition. They found that the goal frame of a woman physician, i.e. their view of an ideal worker and an ideal mother, did affect their career motivation. Those with a traditional view of the ideal worker did PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 33 have a higher career motivation than those with a non-traditional view of the role identity of a physician. However, having a traditional view of the ideal mother did not lessen the career motivation of those with a traditional career view. In fact, the women with the traditional view of a physician and the traditional view of a mother had the highest level of career motivation, which can perhaps be viewed as a driving desire to having it all. Using the Noe et al. instrument (1990), Sadeghifar, Bahadori, Baldacchino, Raadabadi, and Jafari found that higher levels of spiritual leadership demonstrated by administrators at universities increased the career motivation of the faculty (2014). Also studying university employees, Ricketts and Pringle (2014) showed a high level of career motivation in their participants of female university staff, a level which was even higher for those with postgraduate qualifications than those with only an undergraduate education. Additionally, Aytekin, Erdil, Erdogmus, and Akgun (2016) used both career identity, career insight, and career commitment as components of career capital to investigate their relationship to career success in university-employed academicians in Turkey. They found that career capital has a positive effect on research productivity, which in turn mediates the relationship between career capital and career satisfaction. Three career motivation studies were done in 2017, two of which explored the relationship between career motivation and leadership. Fritz and van Knippenberg found that gender didn’t affect one’s leadership aspirations as measured by an adaptation of pre- existing career motivation scales (2017), and Baethge, Rigotti, and Vincent-Heoper showed transformational leadership does influence the career success of followers, but unlike was hypothesized, career motivation didn’t moderate the relationship except for in PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 34 limited situations (2017). The third study in 2017 showed increased career motivation relates to higher college adjustment and teaching efficacy (Kim & Yang, 2017). Career identity. In an opinion piece, Wolf and Sherwood (1981) argue that the transition from a technical position into management is a time when coaching can be especially helpful. They believed a strong career identity is important in a successful transition and urge executive coaching services to take it into consideration. Studying librarians, Phillips, Carson, and Carson (1994) found that career identity changes over time. Their results showed a lower level of career identity with librarians early in their career and higher in mid-career anticipated, but that it went back for individuals later in their career. Eby, Butts, and Lockwood (2003) were also concerned about success in a demanding marketplace. Surveying 458 employed adults about their perceptions of their future in boundaryless careers, where inter-firm and intra-firm mobility in an unpredictable job market is paramount. They found that high levels of both career identify and career insight relate positively to employees’ perceived career success, perceived internal marketability, and perceived external marketability, demonstrating that career motivation will play an important role in uncertain times. A qualitative study of employees in a steel mill indicated that higher career identity contributes to an emphasis in on-going career development (Rose, Jeris, & Smith, 2005). While studying adults employed in a large call center, Wilk and Moynihan (2005) provided a significant relationship between high career identity and less worker PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 35 exhaustion, which is certainly an advantage in today’s fast-paced and demanding marketplace. Using the Career Commitment Measure (Carson & Bedeian, 1994), Coogle, Head, and Parham (2006) investigated the stability of career motivation after a training intervention for workers in the long-term care field. They found that as long as the participants increased in their commitment to work in long-term care, their career identity remained stable. But, if their intent to remain in the field decreased or even remained stable, their career identity decreased. This showed that our career identity is not just based on today, but also on where we see career going in the future. In a phenomenological research design, Suutari and Mäkelä (2007) surveyed 20 managers who had taken international assignments for their job. The participants reported a very high level of career identity as an outcome of their global career. Additionally, career identity affected self-perceived employability in Chilean male middle-aged mangers (Nazar & van der Heijden, 2012), and helped employees respond to organizational change (Lysova, Richardson, Khapova, & Jansen, 2015) and the development of a leader identity improves the effectiveness and success of a leader (Muir, 2014). Finally, career identity (as worded as professional identity) was enhanced by career contentment and entrenchment aids in college-level student affairs employees (Wilson, Liddell, Hirschy, & Pasquesi, 2016). Career insight. Career insight was a key variable for Maurer and Tarulli (1994) as they sought to explain participation in voluntary development activities by employees. They measured PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 36 career insight with three of the items from Noe et al.’s (1990) scale. They also measured job involvement which they defined as “the degree to which a person identifies with his or her work or the degree to which a person considers work to be central to their life concern” (p. 5). This definition of job involvement matches very well with the definition of career identity and will be treated as such, even though it was not measured with Noe et al.’s scale. They found that career insight was related to past participation and current interest in development activities. They state, “to the extent an employee gains knowledge of his or her skills, weaknesses, and interests and also learns about various career opportunities, career paths, and so on, he or she may be more likely to see the relevance and value of development activities” (p. 12). They also found a relationship between job involvement and participation in development activities, although the relationship was much stronger for expected participation in the future than it was for actual participation in the past. Speaking, perhaps, more strongly to their intentions than their actual behaviors. Samuel Aryee of Hong Kong Baptist University and Yue Wah Chay and Juniper Chew from the National University of Singapore have published twice studying pieces of career motivation. Their first study (1994) was referenced earlier. Their second study (Aryee, Chay, & Chew, 1996) was specifically related to career insight instead of the more general career motivation as was their first. They sought to explore why managerial employees do, or do not, accept an expatriate assignment. They found, “the career factors of distance from career goal and career insight were significantly positively related to receptivity to an expatriate assignment” (p. 279). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 37 Eby et al. demonstrated that career insight increased employees’ feelings of perceived career success, perceived internal marketability, and perceived external marketability in boundaryless careers (2003). Jung and Tak (2008) found that Korean employees who perceived themselves to be at a career plateau have lower levels of job satisfaction and organizational commitment. When career insight was introduced as a moderating variable they found that it significantly weakened the relationship between a perceived career plateau and organizational commitment; those with a higher level of career insight were less likely to allow a career plateau to weaken their relationship with their employer. This demonstrates that one way for employers to build organizational commitment might be to strengthen their career insight. It should be noted that although Jung and Tak’s paper describes their moderating effect as being of career motivation, they also described that they faced difficulty translating the career identity and career resilience domains’ measurements into Korean and as such only used the career insight questions from Noe et al.’s (1990) Career Motivation Scale. In a study designed to study the reasons why employees in Japan explore careers outside of their existing organization, Yamamoto (2006) found that a higher level of career insight contributed positively to an inter-organizational career orientation as moderated by job involvement, career satisfaction, and career goal commitment. Fertig, Zeitz, and Blau (2009) theorized that career motivation and its more general counterpart intrinsic motivation, is instrumental in why employees voluntarily seek professional certifications and credentialing, and in 2013, Lin, Wang, and Wang PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 38 found career insight to have a significant positive effect on the intrinsic and extrinsic motivations for information systems developers to learn business skills (Lin et al., 2013). Both of these studies show a connection between career insight and proactive career behaviors. Chang and Feng (2014) explored the predictors of career success. They found career insight significantly influenced participants’ subjective view of their career success, but there was no relationship found between career insight and the participants’ objective career success as measured by salary. Career resilience. Although there are a lot of ways to understand and measure resilience, the current study will focus exclusively on career resilience, as specifically defined by London (1983). The understanding of career resilience was advanced in 2017 with Human Resource Development Review published an integrated literature review on the construct by Paresh Mishra and Kimberly McDonald from Indiana University—Purdue University. The review’s purpose was to provide a review with “a focus on how HRD can assist in creating new knowledge initiatives that will enhance the develop of individuals’ CR” (Mishra & McDonald, 2017, p. 209). Their literature review included 43 articles that their method indicated were relevant which were summarized and then presented in a nomological network. Mishra and McDonald’s review showed studies had both focused on the antecedents and the consequences of career resilience (2017). The antecedents were found to include personal factors (individual characteristics/traits, skills, attitudes, PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 39 behaviors/habits, and career history) as well as contextual factors (supportive workplace, job characteristics, and supportive family). These factors contributed to career resilience. Career resilience in turn influenced participants’’ career satisfaction, intention to change careers, and subjective career success (2017). In conclusion they write, “…the complex environment in which career emerge, develop, and grow clearly demonstrate the need for CR. While the research to date is limited, it does identify a variety of personal and contextual factors that influence CR. More research is needed to clarify definition ambiguities and to determine how CR impacts important career outcomes” (p. 229). In addition to the articles reviewed by Mishra and McDonald (2017), there are additional articles worth review. The following articles were not included in Mishra and McDonald because they are opinion pieces, and not empirical research yet they are informative for this study. Both Szymanski (1999) and Borgen, Amundson, and Reuter (2004) argued career portfolios can be used to enhance career resilience. Moffett, Matthew, and Fawcett (2015) wrote that career resilience is important for veterinarians. Seibert, Kraimer, and Heslin (2016) presented an argument that career resilience could be developed through a combination of psychological and behavioral strategies. Four additional studies were not included in Mishra and McDonald’s (2017) study as they were published more recently. Career resilience, as a function of ability to cope with changes, social skills, interest in novelty, and optimism about the future, can mitigate the effects of reality shock on full-time employees (Kodama, 2017). In employees of the South African financial services sector, career resilience predicted factors of job retention (Potgieter & Mawande, 2018) and career counseling was found to PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 40 be able to increase the career resilience in survivors of sexual abuse (Maree & Venter, 2018). Career motivation in students. Although career motivation has been studied widely in employed adults, it has not been given as much attention in students. A model of career motivation in students was developed by Agbor-Biyee in 1997. First, he argued, a student is impacted by their experiences. Those positive experiences in turn lead to perceptions about themselves and their career. These perceptions lead to motivation, where extrinsic motivation is dominant and intrinsic motivation is latent. Then, with feedback, the student makes a commitment to a career. At that time, Agbor- Biyee argued that the motivation switches from predominately extrinsic to intrinsic. In a final feedback loop, this intrinsic motivation drives the student to gain even more experiences. Does an internship or practicum increase career motivation in psychology students? That was one of the key questions for Carless and Prodan’s quasi-experimental study of Australian graduate students (2003). Although they found that extensive practicum experience did increase vocational clarity as measured by Holland’s (1977) Career Decision Making scale, they found no significant relationship to career identity, career planning, or career resilience as measured by Carson and Bedeian’s (1994) Career Commitment Measure. Carless and Prodan explain this may be caused by a high level of career commitment in all graduate students, regardless of whether or not they had practicum experience (2003). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 41 Also looking at graduate students, Basham and Buchanan investigated the difference in career motivations for students seeking a master’s degree in social work compared to students seeking an MBA. Although they found a high level of careerism in social work majors, they found that “social work students in the sample tended to return to college to gain more knowledge, whereas the motives of students returning to college for a graduate degree in business were more associated with career advancement” (2009, p. 200). In a sample of South Korean high school students, Shin, Lee, and Ha found that career motivation influences grade motivation, need for learning, self-determination, self- efficacy, and predicts the students’ choice to enter STEM fields (2017). Finally, Schmid and Bogner (2017) conducted an experimental study using a 3-hour inquiry course as a career development intervention for high school students in Germany. They found their intervention did not actually affect career motivation as compared to a control group. Career identity. Of the three domains of career motivation career identity has been studied the most in students. Career identity is defined as “how central one’s career is to one’s identity” (London, 1983, p. 621). The more we resonate with our career field as being part of who we are, the more likely we will want to put forth effort that persists over time. Lopez (2001), showed no connection between career identity and math scores, but did find a connection between individualization (individuality and connectedness) and career identity. Lopez’s study also demonstrated a unique way to developmentally measure career identity (2001). They used an 8-item scale from the Extended Objective PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 42 Measure of Ego Identity Status Survey-2 from Bennion and Adams (1986) to survey 112 Latino high school students in a Northern California public high school. This scale divided participants into four categories based on their level of career identity. They describe the framework as follows: Adolescents considered identity achieved have explored different career options and made a commitment toward pursuing a particular career, whereas those classified as diffused have experienced neither exploration nor commitment. Adolescents classified as being in a state of moratorium are still exploring different career options but have not made any commitments, and adolescents classified as foreclosed have make a commitment to a particular career without exploring. (Lopez, 2001, p. 191) To underscore the need for career interventions, 57 of the 112 participants were classified as being in diffusion with no significant difference by gender or grade in school. Also from a student perspective, Kerr and Kurpius (2004) showed that talented at- risk girls with a higher career identity were more likely to raise their career aspirations, increasing the likelihood they would choose math and science careers. It is important to understand how career identity develops in students. As far back as 1979 Wolf wrote about how he believed internships for public service careers would “play a critical role in the development of an individual’s career identity” (1979, p. 130). More recently, Stringer and Kerpelman (2010) surveyed 345 college students to determine if parental support, work experience, gender, or career decision self-efficacy would influence the development of career identity. Their results showed that parental PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 43 support and career decision self-efficacy did impact the development of career identity, but an interesting twist was found while looking at work experience. They found that the work experience’s perceived relevance to a future career didn’t significantly impact career identity, but the number of jobs did. The more jobs a student had through their life the higher their career identity. This seems to indicate that having a wide range of jobs can help students make career choices even more than having a more relevant few. Malanchuk, Messersmith, and Eccles (2010) had a group of adolescents describe for them how a higher career identity gave them a stronger feeling of psychological well- being. And in analyzing data from a national survey of more than 7,000 adolescents in Vietnam, Nguyen, Cohen, and Hines (2012) showed that although youth gain much of their overall identity from their friends, that influence drops as they begin to form their career identity which is impacted more strongly by their family than by their peers. Their data also confirmed a gender gap in career thinking that seems to be an issue the world over. Sadly, even though young women were found to have career aspirations equal to men, they had a significant lower level of hope that they can have “a happy family, good job, and opportunity to do what they want in the future” (Nguyen et al., 2012, p. 1504). Mack, Rankins, and Woodson (2013) divided the development of career identity into four stages. Blending social cognitive career theory with identity development models, they developed a model to represent the career identity development for women of color in STEM disciplines. Their model begins with demographic factors and progresses to informal and formal interventions of professional development activities. Those interventions would address factors of self (esteem, concept, efficacy), motivation PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 44 (career aspirations, career goals, future orientation), skills development (navigating professional environments), and career development (career satisfaction, career choices and career expectations) with period infusions of career identity catalysts. These activities then lead to the four phases of career identity development. Mack et al. described the first stage as pre-encounter where “the academy is viewed as equitable and the implications of being a woman of color are likely not completely realized” (2013, p. 30). During the second, encounter, phase STEM students of color experienced episodes of discrimination that challenge their identity. In the third, the immersion stage, women were aware of differences and embrace their self-identity, but do not yet see themselves fitting into a body of colleagues. In the fourth and final stage, the level of full integration, Mack et al. theorize the women had not only build their career identity individually, but had integrated their role into the larger academy of science and math and recognize the differences and value of every voice in the dialogue. Meijers, Kuijpers, and Gundy (2013) simultaneously studied both high school students and their teachers and found that in both populations, career identity positively contributed to career outcomes. Career identity has been studied in college students around the globe. In an experimental study of US college students, Murdock, Strear, Jenkins-Guarnieri, and Henderson showed that attending a career intervention did not affect the career identity of student athletes, but gender did (2014). Career identity was found to mediate career exploration and career planning’s influence on perceived employability and career distress in Australian college students (Praskova, Creed, & Hood, 2015), and increased PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 45 life satisfaction when it is mediated by tolerance for uncertainty in South Korean college students (Garrison, Lee, & Ali, 2017). Trying to understand how career identity develops in college students in Vietnam, Mate et al. found the student’s family has the biggest influence on their career identity, followed by the media, and the individual’s values (2017). And in a mixed-method, longitudinal study of Asian American students living in the US, Polenova, Bedral, Brisson, and Zinn (2018) found that career identity was developed through the combination of the interaction of Asian and US cultures combined with individual characteristics which “are critical to facilitate the career identity formation of Asian American emerging adults when identity development coincides with the process of acculturation” (p. 63). Career insight. Career insight asks if the individual has clear career goals, realistic perceptions of their own abilities, and focused expectations of the future. Greller (2000) was not able to find support for age norms of career motivation, but found that university students of all ages who think career development increases in importance as one ages did have higher levels of career insight and career resilience. Additionally, he found that those who believe they should build their skills across their career tend to have a higher life satisfaction, especially as measured by health and security. In a later study, Greller and Richtermeyer did find a relationship between career insight and age, finding that it actually decreases with age but increases with support (2006). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 46 Reich and Rosenberg (2004) looked at the intent for university students enrolled in an Army Reserve Officers Training Corps (ROTC) program to remain enrolled in the program in a study that has an interesting parallel to career insight. They had 23 students rate three things 1) their reflective self-image – how they believe others see them, 2) their actual career self – how they see themselves, and 3) their desired career identity – how they want to be seen in the future. They then looked at the gaps between these three self- identities, finding the larger the gap the more likely the student was to remain enrolled. Career insight is about having clear and realistic goals and perceptions about one’s career. The gap then, between where the students are today and where they wanted to be in the future is a better indication of goals than of identity. The career insight motivated them to remain in the ROTC program when they would have an opportunity to make their desired career identity a reality. When studying college students, career insight is sometimes studied as career indecision, essentially its mirror image. Studying Dutch high school students, Germeijs and De Boeck (2003) found three sources for career indecision, lack of knowledge about the possibilities, uncertainty about what choice to pursue, and uncertainty about the outcomes from the possible choices. Each of these three was shown to be an independent component in career indecision and further investigation into their impact was call for. Using social cognitive career theory, Wang (2013) demonstrated that a higher level of math self-efficacy lead to an increased likelihood of choosing a STEM (science, technology, engineering, math) major. This reinforces career insight, as it shows that a PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 47 belief that a STEM goal is realistic, as indicated by self-efficacy level, and that realistic goal lead to career decisions through major choice. Tziner, Oren, and Caduri (2014) sought to understand occupational choice in college students by looking at the congruence of the students’ chosen occupation, their vocational personalities, and their parents’ chosen occupation, as well as with the students’ self-efficacy and self-regulation. They found that students with a higher self- efficacy tended to have made occupational choices that more closely aligned with their vocational personalities. Interestingly, though, they found for even students with low self- efficacies their occupational choice showed more congruence with their own vocational personalities than with their parents’ occupation showing that personal insight is likely more telling for career choice than knowledge of a career based on exposure to it in the home. This goes to career insight as it shows the influence of the understanding ones’ own strengths interests in career decision making. Intellectual Curiosity Intellectual curiosity is a context-neutral construct that seeks to explain an individual’s approach toward opportunities for cognitive effort. This section provides background information and a review of relevant literature. Background It has long been understood that intelligence affects academic performance. Universities use measures such as high school ranking and ACT/SAT scores as substitutes for intelligence tests in admissions decisions and elementary schools use intelligence testing to help understand why a student might be struggling. But intelligence PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 48 is not the only factor linked with academic performance, personality is seen to factor in as well. In 2011, von Stumm, Hell, and Chamorro-Premuzic sought to explain the main components of academic performance, and provide an overview of the links between intelligence, personality, and academic performance in existing literature. Using a meta- analysis and correlation matrix, they studied intelligence, maximum versus typical performance, conscientiousness, investment, curiosity, and openness to experience to find how they tie to academic performance. They wrote that what they found to be the greatest driver of individual academic performance is a “hungry mind”. They found: (a) intelligence is the single most powerful predictor of academic performance; (b) the effects of intelligence on academic performance are not mediated by personality traits; (c) intelligence, Conscientiousness (as marker of effort), and Typical Intellectual Engagement (as marker of intellectual curiosity) are direct, correlated predictors of academic performance; and (d) the addictive predictive effect of the personality traits of intellectual curiosity and effort rival that the influence of intelligence. Our results highlight that a “hungry mind” is a core determinant of individual differences in academic achievement. (2011, p. 574) Therefore, a key to increasing performance in students is to seek to find the antecedents and consequences of a hungry mind. Intellectual Curiosity has overlap with the Big-Five personality characteristic of Openness to Experience, which often viewed as a multi-dimensional construct including six facets of Fantasy, Aesthetic Sensitivity, Attentiveness to Inner Feelings, Actions, ideas, and Values. According to von Stumm et al. (2011), the Ideas sub-construct is often PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 49 synonymous with intellectual curiosity, but the other facets of Openness to Experience do not overlap intellectual curiosity when tested. This study will be using the more specific definition of effortful cognitive activity and term intellectual curiosity, instead of the broader definition of Openness to Experience, as it better fits the research’s purpose. Review of Relevant Studies The effect intelligence has on performance doesn’t stop when a student graduates, but certainly also affects performance on the job. Scager et al. (2012) looked at college honor students with an attempt to understand how that related to potential professional excellence. They found that honors students differ significantly from their non-honors peers on self-report measures of intelligence, motivation, and creativity which are known predictors of professional excellence based on Renzulli’s (1986) model of giftedness. Although intellectual curiosity is typically evaluated in students, a very similar construct has appeared in human resource development literature in the past decades, that of learning agility. In 2000, Lombardo and Eichinger published a paper that gave legs to learning agility in research and practice. They argue “The measurement of potential can be strengthened by adding another concept to the success profiles, that is—the willingness and ability to learn new competencies in order to perform under first-time, tough, or different conditions [emphasis in original]” (p. 323). They term these high potentials to be “learning agile” and seek to measure what that means. They describe people high in learning agility as: seeking and having more experiences from which to learn; enjoying complex first-time problems and challenges associated with new experiences; getting more PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 50 out of these experiences because they have an interest in making sense of them; and performing better because they incorporate new skills into their repertoires. (p. 326). This willingness to learn new competencies for the employee is very similar to the desire to learn new things as a student. Kuncel, Hezlett, and Ones’ (2004) meta-analysis helps us see that performance levels in college and on the job and not unrelated. Using the Miller Analogies Test as a measurement of cognitive ability, they found it to be a valid predictor of academic performance, career potential, creativity, and job performance. With this they argue that intelligence in work is not different from intelligence in school. In addition to supporting a theory of general intelligence, it also lends credence to argument of this paper, that by understanding the college student, human resource development practitioners would be better able to understand their employees. Proactive Career Behaviors This section provides an overview of the construct of proactive career behaviors, including both background information on the construct, and a review of relevant literature. Background De Vos and De Clippeleer et al. define proactive career behaviors as “the deliberate actions undertaken by individuals in order to realize their career goals (2009, p. 763). Of particular interest in this study is the extent to which undergraduate students voluntarily engage in activities that advance their career-related learning and PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 51 development. This may include activities like reading articles, journals, or books in their field, watching related videos or documentaries, or attending conferences or seminars. At the core of the definition for this particular study, though, is that these career-related activities the students participate in are initiated by the student themselves; they are not required for any class. Proactive career behaviors are based on the theoretical foundations of behavioral agency (Betz & Hackett, 1987) which holds that individuals behave in a way that affect their environment in areas related to their career development. Review of Relevant Studies In the opening to their 1998 paper, Claes and Ruiz-Quintanilla wrote, “We know little about the influences of individual, historical, and situational characteristics on young workers’ proactive career behaviors” (p. 357). Citing four types of proactive career behaviors as dependent variables including career planning, skill development, consultation, and networking, they sought to identify the predictive value of the participants’ country of origin, their occupation, employment experience, and mobility experience. They found that while some of their predictor variables were significant, together they only covered 3-8% of the variance for each of the career behaviors, showing that there is still more to explore in this field. Another seminal work on proactive career behaviors was published by Strauss, Griffin, and Parker in 2012. They wrote, “The greater demands on individuals to manage their own careers mean that it is increasingly important to understand how and why people choose to engage in proactive career behaviors such as building new networks or actively seeking career advice” (p. 580). Their three included studies presented their PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 52 construct of “future work self salience” and showed it to be distinct from other constructs, most notably career identity and proactive career behaviors. In addition, they found that their construct of future work self salience significantly explained the variance in proactive career behaviors, to a greater extent even than did career identity. Although they didn’t call it proactive career behaviors, Ozuah, Curtis, and Stein (2001) studied something very similar. A group of 80 pediatric residents were part of a 3- month professional development program of daily lectures, and participated in the study to understand their self-directed learning. Then, for a second 3-month period a control group continued with the lectures and a study group was switched to problem-based learning. All through the 6 months, the participants recorded their outside learning activities including studying independently, engaging in medical discussions, and performing computer literature searches. The results indicated that the study group who had received problem-based learning had an increase in self-directed learning activities. Andreas Hirschi from the University of Lausanne, in Lausanne, Switzerland, has made significant contributions to the understanding of proactive career behaviors. He began by developing a framework for self-directed career management (2012). He argued that self-directed career management is comprised of 1) career adaptability, 2) employability, 3) career self-management, 4) career competencies, 5) career motivation as defined by London (1983), and 6) protean and boundaryless career orientations. Hirschi, along with Philipp Alexander Freund from the Leuphana University of Leuneberg in Luenberg, Greman, and Anne Herrmann from the Kaladios University of Applied Sciences in Zurich Switzerland, continued to advance the field through their PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 53 work with career engagement as measured by proactive career behaviors (Hirschi, Freund, & Herrmann, 2014). Hirschi (2014) showed that dispositional hope had a direct effect on proactive career behaviors, including planning, decidedness, and self-efficacy, and that more differences in career engagement can be found between people than within the same person over time (Hirschi & Freund, 2014). Proactive career behaviors increased with participants’ exposure to a successful role model, but not with exposure to an unsuccessful example, showing that comparing oneself to others who have done well “may inspire individuals to actively work on their careers” (Buunk, Peiro, & Griffioen, 2007, p. 1489). This is important as proactive career behaviors are essential for attaining objective and subjective career success, especially after a job loss (Zikic & Klehe, 2006). Ans De Vos, from the Vlerick Leuven Gent Management School in Gent, Belgium has conducted multiple studies about proactive career behaviors. In 2008, De Vos, with Nele Soens, developed a model that ties together a protean career attitude with perceived employability and career satisfaction, with the relationship being mediated by proactive career behaviors (measured as career self-management behaviors) and career insight which was measured using fourteen items adapted from London (1993). They found that “Protean career attitude related significantly to career insight, career self- management behaviors, career satisfaction, and employability. Career insight and career self-management behaviors related significantly to career satisfaction and employability” (De Vos & Soens, 2008, p. 453). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 54 Then in 2009, using a longitudinal research design, De Vos and De Clippeleer et al. tested a model of proactive career behaviors and their influence on the participants’ career success at both graduation and 3 years after graduation. Their results showed “that the goal to make career progress affects graduates’ proactive behavior and that proactive career behaviors are related to career success in the early career” (2009, p. 773). More recently, proactive work behaviors were found to contribute positively to subjective career success in the hospitality industry (Cha, Kim, Beck, & Knutson, 2017). In addition, Sofo and Abonyi (2018) used a mixed-methods approach to study the “professional development activities” of school leaders in rural Ghana. Through interviews and self-reports, they learned that self-directed learning methods played a very important role in professional development as very few formal programs were available. Shin, Kim, and Ahn found that proactive career behaviors (referred to as career preparation behaviors in their study) had a moderating affect between a calling and their ability to find meaning in life in a sampling of South Korean college students. They state, “students with a higher sense of calling are likely to experience a higher sense of meaning in life in part because they tend to engage in higher levels of career preparation behaviors” (2018, p. 734). In summary, although the study of proactive behaviors of any kind has been fragmented (Parker & Collins, 2010), using meta-analysis to review 107 studies, Fuller and Marler found a proactive personality is positively related to both objective and subjective career success (2009). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 55 Similar Constructs This study sought to understand the reasons why students voluntary engage in career-related behaviors. A review of the literature found many constructs related to this particular topic such as self-directed learning, self-directed learning readiness, self- regulated learning, lifelong learning, continuous professional development, self-directed professional development, self-initiated professional development, self-development, career self-management, and heutagogy. The three most relevant are focused on here. Career readiness. The readiness of high school students for a career has become an increasing concern for educators since the passing of the Every Student Succeeds Act (ESSA) of 2015 (Monahan, Lombardi, & Madaus, 2018). In addition to educators, career readiness is also vital to “employers, policy makers, and the public at large” (Brink, 2018, p. 5). New Directions for Student Leadership dedicated its Spring 2018 issue to the concept of career readiness. The editors, Smith, Rooney, and Spencer wrote: Career readiness must be the result of the whole college experience and student engagement, not just career services on campus…. The purpose of this issue of the New Directions for Student Leadership sourcebook is to explore and articulate the relationship between leadership development experiences and competencies within higher education and how those relate to the career readiness of students for postgraduate success. (2018, p. 7) In the first article in the issue, Fox described what career readiness is. She wrote: PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 56 At a basic level, to be career-ready, students need to present themselves in a dynamic way in a variety of platforms: resume or curriculum vitae, cover letters or personal statements, networking opportunities, and interviews. Students must be self-aware enough to understand the unique value they bring, while demonstrating learned knowledge, skills, and competencies congruent with employer expectations. (2018, p. 16) Fox went on to describe that it takes a wide range of stakeholders to help a student become career ready. These include faculty, campus partners, and the students themselves. Seemiller (2018), in the same issue, describes the competencies necessary for career readiness and how they can be built into events and activities across the campus by the institution. Although career readiness is an important construct, it is slightly different than the focus of this current study. Career readiness is an intended outcome of the whole educational experience, in some of which the student is required to participate. This current study focuses instead of the voluntary activities students initiate on their own behalf, outside of required events and curriculum. Self-directed learning readiness. Self-Directed Learning is a widely known and studied construct. Described by Merriam as, “learning that is widespread, that occurs as part of adults’ everyday life, and that is systematic yet does not depend on an instructor or a classroom” (2001) it is based on the work of Knowles (1975), Tough (1967, 1971), and Houle (1961). As an example of research based on this framework, Louws, Meirink, van Veen, and van Driel (2017) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 57 showed teachers vary greatly in what they want to learn, how they want to learn it, and why they want to learn. Self-directed learning then is beneficial as different people can accomplish it in the way that fits best for their needs and preferences. In research that studies students the related idea of self-directed learning readiness (SDLR) is often used, typically being measured by the Self-Directed Learning Readiness Scale (SDLRS) developed by Fisher et al. (2001) for nursing education, although a much earlier instrument by Guglielmino (1977) shows its historical roots. Some examples research using the SDLRS include Litzinger, Wise, and Lee’s (2005) measurement of engineering undergraduate students which showed correlation but not prediction between SDLR and year in school, GPA, and gender; Hsu and Shiue’s (2005) study that showed SDLR may be a stronger predictor of academic success in distance education than it is in face-to-face education, and Jiusto and DiBiasio’s (2006) study that showed undergraduate students’ self-directed learning readiness score does increase after a study- abroad experience. [NOTE: there are about 10 more similar studies I could talk about if needed.] Although still widely used, subsequent researched has shown validity issues with the instrument (Hendry & Ginns, 2009; Hoban, Lawson, Mazmanian, Best, & Seibel, 2005; Williams & Brown, 2013). A more recent instrument, the Self-Directed Learning Inventory, by Chen, Kuo, Lin, and Lee-Hsieh (2010) may provide a better foundation for future research. Although self-directed learning readiness is a valuable item to study, its definition is slightly different from what is being studied here. Self-directed learning readiness PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 58 evaluates the preparedness of students and relates to all contexts, this study will instead study the actual behaviors of students as related specifically to their career. Continuous professional development. Continuous Professional Development (CPD) is a term used frequently, often in research originating in Europe. While self-directed learning readiness is often studied in students, CPD is typically studied in adults. The Institute for Personnel and Development in the United Kingdom defines continues professional development as “systematic, on- going, self-directed learning. It is an approach or process which should be a normal part of how one plans and manages one’s whole working life” (Austin, Marini, Macleod Glover, & Croteau, 2005). One body of literature uses reviews how CPD increases the effectiveness of Early Childhood Education and Care (ECEC) as framed by the priorities of the EU council in 2011. It defines CPD as all planned programs of learning opportunities for those working in ECEC that were undertaken to complement, update, and consolidate the professional knowledge and competence of individuals and teams working in those settings (Hauari et al., 2014). A literature review on the subject concluded that “most studies indicated that the main benefits of continuous professional development for practitioners concerned capacity” (Peleman, et al., 2017), meaning the teachers had greater pedagogical awareness and competence. Although many say CPD is highly valued there seems to be a disconnect between what is said and what is done. Hain, Hain, and Matthewman (2011) also stressed the importance of CPD for professional growth, this time for coaches. They argued that the coach should utilize a diverse range of CPD activities to develop their competence, and PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 59 that the learning should be managed by the learner. Jepson (2016) built off this conceptual framework in her qualitative review of coaches’ perceptions. She found that all though the coaches valued continuous professional development, the admitted that they valued it more than they actually did it. A study of mid-career dentists in the UK concluded that CPD was only undertaken for pragmatic reasons, mainly to meet regulatory requirements (Brown & Wassif, 2017), and interviews with pharmacists found them to “express ambivalence toward CPD” and a general feeling of poor self- identification of learning needs (Austin et al., 2005). Similarly, Geldenhuys and Oostheizen (2015) found that teachers, a group that you would assume to be very supportive of learning, found that the barriers to continuous professional development, such as insufficient support by school management, have created hurdles to CPD that are just too hard to overcome and have therefore reduced participation in the programs. Again, although continuous professional development is a valuable construct to study, it does not quite fit the goals of this particular research. Most studies that apply CPD, view it as required development as part of a profession, such as credentialing for nurses or continuing education credits for accountants. Because this research focuses on voluntary activities, CPD is not a good fit. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 60 Chapter 3: Method Based on the review of the current literature in chapter 2, the method of research will now be described. Research Design This study was a causal relationship design using predominately interval scales (Gall, Gall, & Borg, 2007). Because a causal relationship study is not experimental it cannot make definitive statements about causality, but rather it explores cause-and-effect relationships. If a significant relationship between the variables are found, an experimental research design would need to be designed to test the causality more definitively (Gall et al., 2007). The study was cross-sectional, based on a single point in time. This study was based on a postpostivistic philosophy. Postivism, is an epistemological view that assumes an objective reality about from the actors or observers, and that there are causes for events that be researched and studying in a bias-free manner. Behavioral researchers using a positivistic framework believe that observable behaviors form the basis of knowledge and with study behaviors can be labeled and measured. Postpostivism adapts the theoretical philosophy of positivism by recognizing the reality of research with human subjects – that reality can never be known perfectly and that behavioral theories can only be strengthened or confirmed (Gall et al., 2007). Based on this philosophical epistemology, this study attempted to understand in part the reality of college students in relationship to career development activities, knowing that it can neither fully explain nor predict students’ behaviors. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 61 Population and Sample The research population for this study was students at a faith-based, private, 4- year university in the upper Midwest. The students were part of a traditional residential college within the university where ages typically run between 18 and 22. The college contains over 2,000 students studying over 50 majors divided into three divisions. The student body in the university is fairly homogenous which both focuses and limits the scope of this study. A narrow distribution in demographic variables including age, ethnicity, and religion was expected in the sample. Although this homogeneity makes the study less generalizable to other populations, it also reduces the confounding effect of these variables and enables the research to focus in to the research variables more clearly. Potential participants for the study were identified in two ways. First, students who were enrolled at the university in Spring 2019 and were still current students at the time of sampling (October 2019) were identified by the Office of the Registrar through students’ official academic records. Second, students who were enrolled at the university in Spring 2019 but had graduated by the time of sampling were identified by the Office of Alumni and Family Services. Invited participants were selected randomly by these two offices. Protection of Human Subjects At the time of the study, the author was employed as a full-time Associate Professor of Business at the university, where the sampling took place. Because of the organizational affiliation, gaining permission from the institution for sampling was easier PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 62 than it would be for an outside researcher. However, because of this relationship, precautions were taken to ensure that confidentiality is protected on behalf of the participants. No identifying questions were required, and no names or student identification numbers were recorded. In order to increase the sampling response, gift cards were offered to random participants, to the order of one $10 Amazon gift card for every 25 participants who completed the full survey. Participants who wanted to be included in the drawing needed to include their email address. These email addresses were the only identifying information in the dataset, and they were stripped out of the data prior to any analysis being conducted. Participants who chose not to provide their email address were still included in the study, but not the drawing. A total of five gift cards were distributed electronically to the emails given, by using Excel’s random number generator to pick the awarded participants. Approval for this study was obtained from the Institutional Review Board of both The University of Minnesota and the sampled university. Both IRBs had requirements to be added to the instrument instructions and the participant invitation text. In addition, to satisfy the request of The University of Minnesota, an additional information paid was available for access, downloading, and printing if a participant chose to do so. In order to satisfy the sampled university’s IRB, participants were only emailed once with the link to the survey. No follow-up emails were sent to participants who did not initially respond. IRB approval letters may be seen in Appendix E. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 63 For current students, the survey was sent directly by the Office of the Registrar and not by the researcher. The researcher was never provided with a list of names of who received the survey. The only way a current student could have been identified as a participant is if they voluntary submitted their email address on the survey. When a student graduates from the university they complete a form and indicate the reasons for which they would like to be contacted in the future. The Office of Alumni and Family Services randomly selected participants from the list of Spring 2019 graduates, all of whom had indicated consent to be contacted for research purposes. The survey, and every individual question in it, was voluntary, a point which was clearly communicated to participants. The participants’ identity and identifying information has been treated with the utmost respect. Because sampling was conducted at the university where the researcher was employed on the faculty, extra care was taken to reduce pressure to participate. All students who were enrolled in a class with the researcher were removed from the sampling set. No other vulnerable populations were included in the sampling. Data Collection Procedures To ensure that the survey was understandable, a pilot test was conducted. A current undergraduate student at the university was hired to take the survey and suggest changes. A few minor changes to terminology were made based on her recommendations. This ensured the survey would make sense to the intended population. She was also able to identify a few typos to be fixed before deployment. She was also timed while taking PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 64 the survey to get a good idea of the approximate time it would take a participant to complete it. The data for this survey was collected using an online self-report survey. Survey instrumentation is a well-known and commonly used method of research. They provide a cost and time effective way to gather a large amount of data. Online surveys can be problematic if your research sample does not have adequate access to the internet-enabled technology. However, the sample in this study has access to the internet through their own or school-owned computers on campus. Online surveys give the participants the ability to answer them in their own time and space, which also enables the survey feel less invasive. The survey was conducted using RedCap a web-based survey software available through the University of Minnesota. RedCap provides security for the data through password protection and secure data storage. Participants responded in their own space and time, using their own technology. There was not personal interaction between the researcher and participants during data collection. The survey was sent to current students by the Office of the Registrar to students’ official email addresses on file. The survey was sent to alumni via email, as provided, directly by the researcher. Because both emails came through the .edu system, participants could be assured the survey was not spam nor did it contain a harmful virus, both of which could reduce the response rate. A copy of the participation invitation email can be seen in Appendix F. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 65 Survey Response Rate The survey invitation was sent via email to 1,000 participants, 750 current students and 250 alumni. A total of 136 participants began the survey, however 16 did not finish and did not provide useable data and were therefore eliminated from subsequent analysis. The remaining 120 surveys provided a response rate of 12%. There were some questions that participants chose not to answer. Two participants did not respond to career insight item two (an item non-response rate of 1.7%), and 12 other items were skipped by only one person. This low non-response rate shows that participants were comfortable with the questions, but yet they were also comfortable skipping one if desired. Because each skipped question was just one item in set to measure the variable, the variable’s score could be calculated even with the missing data. More information about the demographics of the survey respondents can be seen in Appendices G (Participants by Major) and H (Demographics of Survey Participants). Variables and Instrumentation This study was designed to exam the following research hypotheses. In order to do so, instrumentation was deployed. An overview of the instrumentation can be seen in Table 1. Hypothesis 1: Student career insight will be positively related to proactive career behaviors Hypothesis 2: Student career identity will be positively related to proactive career behaviors. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 66 Hypothesis 3: Student career resilience will be positively related to proactive career behaviors Hypothesis 4: Student intellectual curiosity will be positively related to proactive career behaviors. Hypothesis 5: Having completed a required internship/practicum will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. Hypothesis 6: A student’s major will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. Hypothesis 7: A student’s class standing will moderate the relationship between career identity, career insight, career resilience, intellectual curiosity, and proactive career behaviors. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 67 Table 1: Description of Measures Variable Scale Number of items Response options Career Insight, Career Identity, Career Resilience Varies 19 Likert scale, 5 points, agreement Intellectual Curiosity Need for Cognition – Short Form 18 Likert scale, 5 points, agreement Proactive Career Behaviors Scale from Strauss et al. (2012), Career Engagement Scale, Original items 31 Likert scale, 5 points, agreement Likert scale, 4 points, frequency Moderators and demographics Original items 12 Varies Variables: Career Identity, Career Insight, and Career Resilience The dominate instruments for measuring career motivation are those of Noe, et al. (1990), London (1993), and Carson and Bedeian (1994). Lopes (2006), in his doctoral dissertation at The Pennsylvania State University, used all three in his study of career motivation variation by age, gender, and nationality in graduate students. To measure career identity, career insight, and career resilience, a combination of questions from existing instruments and original items was used. Most of the items came from Carson and Bedeian (1994) as they have strong relevance for college students. Four additional items were taken from Noe’s instrument and one from London’s, with a few of the questions reworded slightly in order to make them for college students and to allow all items to be answered using the same scale. In addition, two original questions were PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 68 added to have the instrument better fit the population of this study. The items and their specific sources for the items can be found in Appendix I. For career identity and career resilience, all of Carson and Bedeian’s (1994) items were used. These items relate much better to college students than Noe et al.’s items (1990). For example, Noe et al.’s item, “Have you taken courses toward a job-related degree” does not make sense to use with current undergraduate college students. Nor does the item “Have you kept current on company affairs”. These items are clearly directed toward working professionals. For career insight, there is similarity between the items in Carson and Bedeian’s measure and Noe et al.’s measure. Four items from Noe were used in that they relate more directly to college students. For example, Carson and Bedeian’s item of “I do not often think about my personal development in this line of work/career field” has more relevance for career professionals than for students prior to career entry. A key piece of London’s definition of career insight is missing both Carson and Bedeian’s and Noe et al.’ measure, that of the feeling the career goal is attainable. Because that is an important attitude to be measured in college students, one item “My career goal is realistic and attainable” was added from London (1993). Variable: Intellectual Curiosity There are several available instruments for measuring intellectual curiosity, each having a slightly different approach to the construct. Powell, Nettelbeck, and Burns (2015) examined the Need for Cognition, Typical Intellectual Engagement, and Epistemic Curiosity scales. Typical Intellectual Engagement, a 59-item scale, was found PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 69 to be the most general of the three. Epistemic Curiosity was the narrowest, with over 50% of the items loading on one sub-construct. The Need for Cognition scale was found to focus on two sub-constructs, intellectual avoidance and problem solving, while still giving attention to the others. Although the general Typical Intellectual Engagement measure is attractive, because it is only one piece of the full questionnaire, 59-items will likely reduce the completion rate for individual participants. Because of this, intellectual curiosity will be measured by the Need for Cognition short form by Cacioppo et al. (1984). This is an 18- item instrument extracted from the longer 34-item Need for Cognition scale. The shorter version was used here for its efficiency of time for participants and can be seen in Appendix J. Variable: Proactive Career Behaviors Proactive career behaviors was measured using a combination of three sources. First, proactive career behaviors was measured with the Career Engagement Scale (Hirschi & Freund, 2014). They define career engagement as “the degree to which somebody is proactively developing his or her career as expressed by diverse career behaviors” (p. 577). It is a nine-item scale where participants are asked to indicate if they have engaged in any of the named career behaviors in the previous six months. It does not measure participant attitude, but rather the frequency of exhibited behaviors. The scale was previously evaluated using exploratory factor analysis and the results showed the items did capture a one-dimensional construct of career engagement (Hirshci, Freund, & Herrmann, 2014). Secondly, 10 additional items were added that are specific to this PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 70 particular study as it relates to undergraduate students. Third, thirteen items from Strauss et al. (2012) were also be used. These items were reworded slightly to better apply to a full-time college student instead of a full-time employee as was studied by Strauss et al. The full questionnaire can be seen in Appendix K. Demographic and Moderator Variables Additional items were included to better understand the sample. These include the following: email address (used for gift card incentive and separated from data file), major, approximate number of credits before entering the university, class standing, GPA, gender, ethnicity, first-generation college student, completed a required internship/practicum, past work experience, and knowledgeable support, and career influence will all be assessed through self-report items on the questionnaire. Each variable was measured with one item for a total of 12 items. The items can be seen in Appendix L. Data Analysis Procedure The survey data was analyzed in four ways. First, the instrumentation was analyzed for reliability and validity. Secondly, and analysis was using descriptive statistics and correlation analysis. The third step included a test of the regression assumptions, and the fourth was a testing of the hypotheses. Step one will be described in this chapter, and steps two through four will be described in Chapter 4, however, a brief overview of these analyses will be given here. Prior to conducting the analysis, any “Not applicable” response was removed so it would not influence the results. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 71 Reliability and Validity Testing of Instruments The career motivation scale was first tested using an exploratory factor analysis (EFA) to determine the number of factors explained in the model. It was conducted using Oblimin rotation with Kaiser normalization, as the variables were expected to correlate so an oblique rotation is preferred. The EFA returned four factors with Eigenvalues over 1. The model was, however, expected to have only three factors including career insight, career identity, and career resilience. A confirmatory factor analysis was conducted on a three-factor model. A chi-square difference test was then computed to show which of the two models best explained the variance. Cronbach’s alpha statistics were analyzed for each instrument. Finally, a common method variance test was conducted using Harman’s single-factor test. These analyses will be described in more detail later in this chapter. Descriptive Statistics and Correlation Analysis In order to analyze the variables for descriptive statistics, the minimums, maximums, means, and standard deviations were calculated. In addition, the dependent, independent, and moderator variables were analyzed for skewness and kurtosis in order to evaluate their distribution as compared to a normal distribution. In addition, frequency histograms were plotted as compared to a normal curve. Correlation analysis was conducted, developing Pearson correlation coefficients for all study variables. Regression Assumptions Tests Prior to conducting the regression analysis and hypothesis testing, the data was reviewed for homoscedasticity, linearity, normality, and multicollinearity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 72 Homoscedasticity was analyzed by a visual review of plots of the standardized residuals against the standardized predicted values. Homoscedasticity was also tested by evaluating the outliers using squared Mahalanobis distance. The linearity assumption was tested through bivariate plots using a Loess smoothing line and visual analysis. Normality assumption was tested through predicted probability plots of the regression predictors and residuals. Finally, multicollinearity was reduced by using mean-centered variables and by reviewing the resulting tolerance and variance inflation factors. Hypothesis Testing The hypotheses in this study were testing using hierarchical regression analysis. For each dependent variable, a regression was calculated using two steps. First, a main effect was calculated using the primary independent variables. In step two, an interaction effect was tested by including the moderator variables and interaction terms in the model. Reliability and Validity Testing of Instruments Career Motivation Components Because items were taken from multiple career motivation scales, it was important to explore whether or not the scales truly are measuring what was intended. In order to do so, an exploratory factor analysis (EFA) was conducted in order to determine the number of factors represented in the instrument. EFAs were conducted using principal component analysis (PCA) method for factor extraction using Oblimin rotation with Kaiser Normalization. The 19 total items from the career motivation instrument were included. The results indicated that there PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 73 were four components with eigenvalues over 1.0, which together explained 67.6% of the variance. Table 2: Eigenvalues and Total Variance Explained for Career Motivation Component Career Motivation Initial Eigenvalues Total % of Variance Cumulative % 1 4.995 33.297 3.297 2 2.326 15.572 49.869 3 1.676 11.172 60.040 4 1.139 7.591 67.341 5 .895 5.968 73.599 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 74 Table 3: Exploratory Factor Analyses of Career Motivation Item Factor 1 Factor 2 Factor 3 Factor 4 Career Insight 1 .865 -.154 .048 -.082 Career Insight 2 .896 -.132 -.018 .022 Career Insight 3 .770 .200 -.057 -.011 Career Insight 4 .224 .203 .111 .447 Career Insight 5 -.190 -.084 -.031 .899 Career Identity 1 -.030 -.133 .941 .029 Career Identity 2 -.026 -.077 .943 -.052 Career Identity 3 .164 -.030 .795 -.018 Career Identity 4 -.030 .302 .658 .054 Career Resilience 1 -.123 .765 .081 -.314 Career Resilience 2 .103 .707 .075 .214 Career Resilience 3 .119 .834 -.129 .067 Career Resilience 4 -.032 .836 -.020 .068 Career Resilience 5 .455 .238 .252 .138 Career Resilience 6 .665 .052 .053 -.052 Note. Extraction method: Principal component analysis. Rotation method: Oblimin with Kaiser Normalization Items one through five were expected to measure career insight. Items one (“I have a clear career goal”), two (“I’ve worked out a plan for achieving my career goal”), and three (“My career goal is realistic and attainable”) did load to a common factor. Item PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 75 18 (“I am satisfied with my choice of major”) and item 19 (“I am confident my major will prepare me for my next career-oriented step (e.g., finding a job, getting into grad school”) were originally expected to represent career resilience. However, the component analysis showed these items loaded with career insight items one through three. Subsequent analysis used career insight as a combination of these five items. Cronbach’s alpha of the five-item subscale is .824 and the largest inter-item correlation is between items one and two at .697. Items seven (“My major/career field is an important part of who I am”), eight (“My major/career field has a great deal of personal significance”), nine (“I strongly identify with my chosen major/career field”), and 10 (“I do not feel ‘emotionally attached’ to this major/career field”—reverse scored) were expected to represent career identity, and did indeed load to the same factor. However, items seven and eight were correlated at a level of 0.847, indicating they were essentially measuring the same thing. No other items in the career motivation scales correlated at a level above .74. In subsequent analysis, item seven was removed from the scale so career identity was calculated by items eight, nine, and 10. Number eight was chosen to remain as it has a slightly higher load factor in the exploratory factor analysis. This 3-item subscale had a Cronbach’s alpha of .780 and the highest inter-item correlation was .742. Items 14 (“The costs associated with my chosen major/career field seem too great”—reverse scored), 15 (“Given the problems I encounter in this major/career field, I sometimes wonder if I will ever get enough out of it”—reverse scored), 16 (“Given the problems I encounter in this major/career field, I sometimes wonder if the personal PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 76 burden is worth it”—reverse scored), and 17 (“The discomforts associated with my major/career field sometimes seem too great”—reverse scored) all loaded on the same principal component. These four items were used as the measure of career resilience. This four-item subscale had a Cronbach’s alpha of .822 and the highest inter-item correlation was .688. Items four (“I feel I have a good understanding of my strengths and weaknesses”) and five (“Since starting college, I’ve changed or revised my career goals based on new information I’ve received about myself or my situation”) did not load to the career insight factor as expected, but rather to a separate, fourth factor. The common theme in these two questions was about students’ knowledge of themselves. These two items were combined into a fourth career motivation variable and identified as self-knowledge. This 2-item subscale had a Cronbach’s alpha of .194 and the two items were correlated at 0.116. Table 4: Reliability Analysis of the Career Motivation Measure Career Insight Career Identity Career Resilience Self- Knowledge Number of Items 5 3 4 2 Cronbach’s α .824 .780 .822 .194 To compare the three- and four-factor models a chi-square difference test was used with a generalized least squares extraction. The chi-square of the null three-factor model (χ2 = 70.735, 63 df) and the four-factor model (χ2 = 48.957, 51 df) were compared. The difference of 21.778 with 12 degrees of freedom has a p-value of 0.040. That shows the PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 77 four-factor model can be accepted as it significantly improved on the null three-factor model. The study hypotheses were revised to include this new variable, identified as self- knowledge, in the model. Intellectual Curiosity The 18-item Need for Cognition-Short Form from Cacioppo et al. (1984) was used to measure intellectual curiosity (see Appendix J). Reliability was calculated for the intellectual curiosity instrument. This instrument had a Cronbach’s alpha of .892 and the highest inter-item correlation was .688. Proactive Career Behaviors A total of 31 items were used to measure proactive career behaviors (see Appendix K). Items one through nine were from the instrument developed by Hirschi and Freund (2014). This scale was behavioral in that participants are asked to indicate how frequently they have done a certain activity in the previous six months and was answered on a scale of Often, Sometimes, Rarely, and Not at All. Items 10 through 18 were added specifically in this study as they were additional activities relevant to the particular population of interest here, but are not included in Hirschi and Freund’s instrument. Items 19 through 31 were from Strauss et al. (2012). This instrument measured agreement with given statements about what they are doing, but did not ask about frequency. In this study, this 13-item scale from Strauss et al. (2012) had a Cronbach’s alpha of .901. Items 19 (“I am planning what I want to do in the next few years of my career”) and 20 (“I am thinking ahead to the new few years and planning what I want to do with my career”) correlated at 0.826. This high correlation makes sense as the items are PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 78 worded very similarly. In subsequent analyses, item #20 was not used. The new, 12-item scale showed a Cronbach’s alpha of .889 and no items were correlated above .8. The 18-item scale based on Hirschi and Freund (2014) showed a Cronbach’s alpha of .898 and the highest inter-item correlation was .720. Common Method Variance Test Because all variables were obtained from the same source (the participant) in the same method (an online survey) it is important to understand the amount of variance due to this common method. Using exploratory factor analysis, Harman’s single-factor test was conducted. All of the items used for the dependent and independent variables were combined into one EFA. The results showed 16 factors with Eigenvalues greater than 1, with the first factor explaining 21.97% of the variance. Because more than one factor was present and the first factor was not substantial, it indicates that it was unlikely that the variance due to the common method was substantial. Therefore, the common method variance factor was not included in the hypothesized regression models. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 79 Table 5: Eigenvalues and Total Variance Explained Component All Dependent and Independent Variables Initial Eigenvalues Total % of Variance Cumulative % 1 14.058 21.966 21.966 2 6.116 9.556 31.521 3 4.656 7.274 38.796 4 4.034 6.302 45.098 5 2.396 3.743 48.481 6 2.203 3.442 52.284 7 2.037 3.183 55.466 8 1.896 2.963 58.429 9 1.658 2.590 61.109 10 1.609 2.515 63.534 11 1.484 2.318 65.852 12 1.391 2.173 68.025 13 1.332 2.081 70.106 14 1.242 1.940 72.046 15 1.131 1.767 73.813 16 1.092 1.705 75.518 17 .984 1.537 77.055 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 80 Chapter 4: Results This chapter presents the results from the examination of career behavior in undergraduate students. It begins by providing descriptive statistics, and then turns to an analysis of the results in light of each of the research questions in the study. All data was analyzed using IBM SPSS Statistics software (version 26). Descriptive Statistics This section will review the descriptive statistics from the study’s variables in order to understand the data patterns. First, the demographics of the sample will be analyzed to see if they are a good fit with the demographics of the population. The demographics of the sample varied slightly from the demographics of the population, as provided by the sampled university’s Office for Institutional Data and Research. As can be seen in Table 1, the sample was more likely to contain respondents from the professionally-oriented majors as compared to the population. This may be due to a higher career-orientation in those majors which led to the students being more willing to spend time to answer a survey about careers. The sample also contained a slightly higher percentage of white respondents than did the population (87.5% to 83.3%). The biggest difference, though, was in the gender distribution. Females represented 75.8% of the respondents, but only 61.7% of the population. It is possible that the demographics of the sample were influenced by the demographics of the researcher. Because the researcher is a white female in a professionally-oriented department, perhaps participants who saw themselves as similar to the researcher were more likely to respond. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 81 Table 6: Demographics of Sample and Population Demographics of Sample Demographics of Population Gender Male: 23.3% Female: 75.8% Did not provide: 0.8% Male: 38.3% Female: 61.7% Ethnicity Asian American/Asian = 4.2% Hispanic/Latino/a = 2.5% Native American/ Alaskan Native = 0.8% White = 87.5% Other = 1.7% Prefer not to respond = 3.3% Asian American/Asian = 4.9% Hispanic/Latino/a = 4.5% Native American/ Alaskan Native = 0.3% White = 83.3% Black = 3.1% Native Hawaiian/ Pacific Islander = 0.1% Two or more: 3.8% First Generation No = 87.5% (105) Yes = 12.5% (15) No = 81% Yes = 19% Major Professional Programs = 56.4% Natural and Behavioral Sciences = 23.5% Arts and Humanities = 20.1% Professional Programs = 48.0% Natural and Behavioral Sciences = 25.9% Arts and Humanities = 26.2% Independent and dependent variables. Second, the descriptive statistics of the independent variables were analyzed. All of these scales were measured using a 5-point scale of strongly disagree to strongly agree. Some items were reverse-scored, but regardless of how the question was asked, a higher number indicated a more positive response. The highest mean in the set was for self- knowledge (M = 4.17, SD = .74), followed by career insight (M = 4.09, SD = .76), career identity (M = 3.89, SD = .89), intellectual curiosity (M = 3.55, SD = .60), and finally career resilience was the lowest (M = 3.23, SD = .90). Histograms of the dependent and independent variables may be seen in Appendix M. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 82 Next, the descriptive statistics of the dependent variables, the 2 forms of proactive career behavior, were analyzed. The proactive career behavior—activity variable was measured using a 5-point scale of strongly disagree (1) to strongly agree (5). This means that with a higher value, the student was indicating that they have proactively engaged in the identified career behaviors. The mean of this scale was 3.91 (SD = .61) showing that the tendency was for students to show agreement with these activities. The proactive career behaviors—frequency scale was measured on a scale of 1 to 4. The lead-in question asked “Not including activities that are required for a class, to what extent have you in the past 6 months…” and participants answered not at all (1), rarely (2), sometimes (3), or often (4). This means that the higher the score on this scale the more often students had engaged in that activity in the last 6 months. The overall mean for this scale was 2.89 (SD = .55), indicating the tendency for students to sometimes participate in these activities. Table 7: Descriptive Statistics of Dependent and Independent Variables Mean SD Min Max Skew- ness Kurto- sis Career Insight 4.09 .76 2.00 5 -.697* -.364 Career Identity 3.89 .89 1.67 5 -.836* -.123 Career Resilience 3.23 .90 1.00 5 -.323 -.571 Self-Knowledge 4.17 .74 1.50 5 -.926* .597 Intellectual Curiosity 3.55 .60 1.72 5 -.109 .358 Proactive Career Behaviors-Activity 3.91 .61 2.58 5 -.193 -.515 Proactive Career Behaviors— Frequency 2.89 .55 1.50 4 -.328 -.230 Note: * = skewness or kurtosis statistic more than twice the standard error, which indicates a non-normal distribution Skewness standard error = .221 Kurtosis standard error = .438 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 83 As presented in Table 7, analysis of the skewness and kurtosis of the data indicate the distribution of some variables might not have been normal. The career insight, career identity, and self-knowledge scales had a negative skew, more than twice their standard error, indicating a non-normal curve. A skewness coefficient such as these, between -.5 and -1, indicate a moderate skew where the tail to the left of the curve is longer than the tail to the right. This indicates that the participants in this study had higher levels of career insight, career identity, and self-knowledge than would be expected in a normal population. The distribution of the data may be seen in the frequency histograms in Figure 3. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 84 Figure 3: Frequency Histograms for Dependent and Independent Variables Moderator variables. Lastly, descriptive statistics were analyzed for the three moderator variables. These variables include whether a student has completed a required internship or practicum, the student’s current class standing, and the division of their major. First, participants were asked if they have already completed a career-related such as an internship or practicum as part of their required coursework. All 120 participants answered this question with 69% answering yes (0 = no, 1 = yes). It contained a mean of PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 85 .57, and a standard deviation of 0.496. A skewness statistic of -.0307 and a kurtosis statistic of -1.938. indicated that although not significantly skewed, the data had a higher amount of responses in the tails and a lower peak than a normal distribution. This is to be expected with an item with only two possible responses. Sampling was conducted based on student enrollment during spring semester 2019 and conducted during October of 2019. Participants were asked to indicate their class standing as of the point in time of survey completion. Of the 120 participants, 1.7% (2) were freshmen, 10% (12) were sophomores, 30.8% (37) were juniors, 35.0% (42) seniors, and 22.5% (27) had graduated. The data contained a mean of 3.67 (between junior and senior year), standard deviation of .990, skewness of -.342 and kurtosis of - .439, indicating a normal distribution. Participants were given the opportunity to identify both a primary and a secondary major. 120 participants identified their primary major, and no participants identified as Exploratory, the title the university uses for students who are still undecided in their major. 29 students identified a second major for a total of 149 reported majors. The 149 majors can be combined to represent 23 different academic major groupings at the university in 3 different divisions. The number of respondents in each area can be seen in Appendix G. It was expected that the business major would show the highest sample participation. First, the business major is the largest major in the sampled population, representing approximately 19% of total student enrollment. In addition, this study was conducted by a faculty member in the business department. Students who know the PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 86 researcher may have been more likely to complete the survey. Because of the small sample size for some of the majors, subsequent analysis was done at the division level of their first major (n=120). The distribution of the data may be seen in the frequency histograms in Figure 4. Figure 4: Frequency Histograms for Moderator Variables Correlations among Variables Correlation among the variables was analyzed with Pearson correlation coefficients which can be seen in table 8. As expected, there was significant correlation between the three career motivation sub-constructs including: career insight and career identity (r = .520; p <.01), career insight and career resilience. (r = .344; p <.01), and career identity and career resilience ((r = .280; p <.01). The fourth component of the model added in this study, self-knowledge correlated to a lesser extent to the main components of career insight ((r = .206; p <.05) and career resilience ((r = .192; p <.05), but did not significantly correlated with career identity. Intellectual curiosity correlated significantly with career insight (r = .284; p <.01), career identity (r = .229; p <.05), and career resilience (r = .249; p <.01), but not with self-knowledge. The moderator variables showed only slight correlation with the study variables, but they did show significant correlation with each other. The division of a student’s PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 87 major had a significant correlation with career insight (r = -.183; p <.05), and students with higher class standings tend to show higher levels of self-knowledge ((r = .226; p <.05). As expected, students who have already completed a required internship were significantly more likely to be later in their college years (r = .393; p <.01) and from the Professional Programs division (r = -.255; p <.01). The dependent variables of proactive career behaviors-activity and proactive career behaviors-frequency did show significant correlation with the independent variables and with each other (r = .599; p <.01), although neither showed correlation with career resilience. The correlations between the dependent and independent variables does show a relationship between the variables as hypothesized which will be analyzed through regression analysis in the next section. Table 8: Pearson Correlation Coefficients among the Variables Variable 1 2 3 4 5 6 7 8 9 10 1. Career Insight 1 2. Career Identity .520** 1 3. Career Resilience .344** .280** 1 4. Self-Knowledge .206* .155 .192* 1 5. Intellectual Curiosity .284** .229* .249** .273 1 6. Proactive Career Behaviors- Activity .497** .402** .139 .240** .271** 1 7. Proactive Career Behaviors- Frequency .231* .223* .032 .294** .229* .599** 1 8. Internship .073 .045 .083 .023 -.095 .128 .201* 1 9. Class Standing -.172 -.064 -.017 .226* .084 .015 .293** .393** 1 10. Division of Major -.183* -.012 -.055 .070 -.013 -.173 -.142 -.255** .052 1 Note: * p < .05 ** p <.01 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 88 Regression Assumptions Tests Prior to conducting the regression analysis, the assumptions first needed to be tested including homoscedasticity, linearity, and normality. In this study, seven hypotheses were originally modeled. However, results of the reliability and validity testing of the career motivation components indicate that an additional variable, self- knowledge should be added. In addition, although there was significant correlations between the two proactive career behaviors scales (r = .599, p <.01), evaluating them separately would show if there the hypothesized relationships are different when measured by the frequency of actions instead of an agreement scale. In addition, by keeping the measures separately, future researchers can compare this study with others using Strauss et al.’s instrument (2012). The revised hypotheses are as follows: Hypothesis 1a: Student career insight will be positively related to proactive career behaviors-activity. Hypothesis 1b: Student career insight will be positively related to proactive career behaviors-frequency. Hypothesis 2a: Student career identity will be positively related to proactive career behaviors-activity. Hypothesis 2b: Student career identity will be positively related to proactive career behaviors-frequency. Hypothesis 3a: Student career resilience will be positively related to proactive career behaviors-activity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 89 Hypothesis 3b: Student career resilience will be positively related to proactive career behaviors-frequency. Hypothesis 4a: Student self-knowledge will be positively related to proactive career behaviors-activity. Hypothesis 4b: Student self-knowledge will be positively related to proactive career behaviors-frequency. Hypothesis 5a: Student intellectual curiosity will be positively related to proactive career behaviors-activity. Hypothesis 5b: Student intellectual curiosity will be positively related to proactive career behaviors-frequency. Hypothesis 6a: Having completed a required internship/practicum will moderate the relationship between career identity (6a1), career insight (6a2), career resilience (6a3), self-knowledge (6a4), intellectual curiosity (6a5), and proactive career behaviors-activity. Hypothesis 6b: Having completed a required internship/practicum will moderate the relationship between career identity (6b1), career insight (6b2), career resilience (6b3), self-knowledge (6b4), intellectual curiosity (6b5), and proactive career behaviors-frequency. Hypothesis 7a: The division of student’s major will moderate the relationship between career identity (7a1), career insight (7a2), career resilience (7a3), self-knowledge (7a4), intellectual curiosity (7a5), and proactive career behaviors-activity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 90 Hypothesis 7b: The division of a student’s major will moderate the relationship between career identity (7b1), career insight (7b2), career resilience (7b3), self-knowledge (7b4), intellectual curiosity (7b5), and proactive career behaviors-frequency. Hypothesis 8a: A student’s class standing will moderate the relationship between career identity (8a1), career insight (8a2), career resilience (8a3), self-knowledge (8a4), intellectual curiosity (8a5), and proactive career behaviors-activity. Hypothesis 8b: A student’s class standing will moderate the relationship between career identity (8b1), career insight (8b2), career resilience (8b3), self-knowledge (8b4), intellectual curiosity (8b5), and proactive career behaviors-frequency. Homoscedasticity assumption. One assumption of a regression model is that the variance around the regression line is the same at all points along the X axis which is referred to as homoscedasticity. To test for it, plots showing the standardized residuals against the standardized predicted values were created. For the assumption to be met, the dots should be evenly dispersed around zero. The plots are presented in Figure 5. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 91 Proactive Career Behaviors - Activity Proactive Career Behaviors - Frequency C ar ee r In si g h t C ar ee r Id en ti ty C ar ee r R es il ie n ce S el f- K n o w le d g e In te ll ec tu al C u ri o si ty Figure 5: Scatter plots of standardized residuals for dependent and independent variables PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 92 To further test the assumption of homoscedasticity, potential outliers were evaluated two ways. First, a 5% trimmed mean was calculated. This is done by removing the highest and lowest 5% of the responses and calculating a new mean. If the trimmed mean is similar to the full mean, there is not a concern for outliers. The greatest difference between the mean and the 5% trimmed mean is for the variable career insight, and was a difference 0.05. This low difference does not give concern. In addition, for each variable, the 5% trimmed mean was in the 95% confidence interval for the mean. Secondly, specific outliers were evaluated using squared Mahalanobis distance. A total of six potential outliers were present with a p-value between .01 and .05. No outliers were present with a p-value less than .01. These outliers were participants number 12, 40, 43, 81, 112, and 120. These six outliers were evaluated based on their response to the moderator variables. Of the six, three had completed an internship and three had not. There were no freshmen, one sophomore, one junior, three seniors, and one graduate. Two were from the Professional Programs division, one from the Natural and Behavioral Sciences division, and one from the Arts and Humanities. These six outliers did not seem to have anything in common nor are they concentrated in one area that might have skewed the data. Because of this, all participants’ responses were included. Linearity assumption. To test the linearity assumption, scatterplots were created between the dependent and independent variables and can be seen in Figure 6. In each bivariate plot, a Loess smoothing line was drawn using at least 50% of the data. A visual examination shows most bivariate relationships could be considered linear. The results did suggest, though, PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 93 that a curvilinear regression model may be a better fit for the relationship between proactive career behaviors-frequency and career identity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 94 Proactive Career Behaviors - Activity Proactive Career Behaviors - Frequency C ar ee r In si g h t C ar ee r Id en ti ty C ar ee r R es il ie n ce S el f- K n o w le d g e In te ll ec tu al C u ri o si ty Figure 6: Scatterplots for linearity assumption PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 95 Normality assumption. The third test was to evaluate the data for normality. For this test, a predicted probability plot of the predictor and standardized residual was generated for each regression model and can be seen in Figure 7. The plots results showed strong congruence with a diagonal normality line, therefore, linear regression was be used. Figure 7: P-P Plot Multicollinearity. As the moderator variables were tested through interaction terms created by multiplying two variables together, the interaction terms could have caused multicollinearity. To reduce multicollinearity, independent and interaction variables were standardized by centering on the mean. In addition, tolerance and variance inflation factors (VIF) were reviewed. Tolerance statistics should be more than .1, and variance inflation factors (VIF) should be less than 10. In this study, tolerance statistics ranged between .342 and .899 and the highest VIF was 2.924. This shows there was not significant concern for multicollinearity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 96 Hypotheses Tests As described, a total of 16 hypotheses were tested, labeled 1a and 1b through 8a and 8b. These hypotheses were tested using hierarchical regression analysis at two stages. The first stage tests for the main effect of the independent and dependent variables. The second stage added the moderator variables to the model. Result of Hierarchical Regression Analysis The results of the hierarchical regression analyses are presented in Tables 9 and 10. Table 9 summarizes the results of the model using proactive career behaviors-activity as the dependent variable. In the main effect, two independent variables were shown to significantly influence the dependent, those of career insight and career identity. Career insight (B = .227, β = .374, p = .000) showed the strongest indicator with a positive coefficient of .300, which was the highest coefficient in the main effect apart from the constant. Also strongly significant was the relationship between career identity and proactive career behaviors-activity (B = .115, β = .190, p = .042). Career insight (B = .201, β = .331, p = .003) and career identity (B = .124, β = .205, p = .043) also showed a significant relationship with proactive career behaviors-activity in the interaction model which included the moderator variables. Career resilience, self-knowledge, and intellectual curiosity did not show a significant relationship in the analysis. Therefore, H1a and 2a were supported, but 3a, 4a, and 5a were not. In evaluating interaction effects, the regression analysis showed a significant contribution to two of the moderators. The division of a student’s major did moderate the relationship between career resilience and proactive career behaviors-activity (B = -.123, PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 97 β = -.212, p = .039). In addition, the student’s class standing moderated the relationship between intellectual curiosity and proactive career behaviors-activity (B = -.116, β = - .218, p = .043). The resulting relationships can be seen in Figures 8 and 9. Therefore, H7a3 and 8a5 are supported, but all other hypotheses in 6a, 7a, and 8a are not. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 98 Table 9: Regression Results for Proactive Career Behaviors-Activity Dependen t Variable Predictor Variable Step 1 (Main effect) Step 2 (Interaction effect) B SE B β t p B SE B β t p Proactive Career Behaviors - Activity Career Insight .227 .508 .374 3.92 .000 .201 .065 .331 3.10 .003 Career Identity .115 .056 .190 2.06 .000 .124 .060 .205 2.05 .043 Career Resilience -.057 .052 -.094 -1.10 .273 -.061 .055 -.101 -1.11 .268 Self- Knowledge .073 .050 .121 1.47 .145 .087 .062 .143 1.41 .163 Intellectual Curiosity .068 .051 .112 1.33 .187 .077 .059 .128 1.30 .196 Internship .075 .057 .123 1.30 .197 Class Standing -.005 .051 -.008 -.08 .933 Division -.043 .051 -.072 -.85 .399 C Insight x Internship -.013 .073 -.021 -.18 .860 C Insight x Standing -.047 .070 -.075 -.68 .501 C Insight x Division .121 .066 .187 1.8 .071 C Identity x Internship .092 .077 .156 1.20 .235 C Identity x Standing .048 .076 .076 .64 .526 C Identity x Division .007 .065 .013 .11 .911 C Resilience x Internship -.119 .065 -.195 -1.83 .071 C Resilience x Standing .084 .061 .146 1.39 .169 C Resilience x Division -.123 .059 -.212 -2.09 .039 Self- Knowledge x Internship -.012 .058 -.021 -.21 .834 Self- Knowledge x Standing .017 .058 .034 .30 .766 Self- Knowledge x Division -.019 .063 -.035 -.31 .757 Intellectual Curiosity x Internship .070 .068 .111 1.04 .303 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 99 Intellectual Curiosity x Standing -.116 .057 -.218 -2.06 .043 Intellectual Curiosity x Division .069 .061 .211 1.14 .255 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 100 Figure 8: A Moderator Relationship of Division between Career Resilience and Proactive Career Behaviors-Activity Figure 9: A Moderator Relationship of Class Standing between Intellectual Curiosity and Proactive Career Behaviors-Activity PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 101 Table 10 summarizes the results of the model using proactive career behaviors- frequency as the dependent variable. In the main effect, only one independent variable was shown to significantly influence the dependent, self-knowledge (B = .130, β = .237, p = .010), however this relationship was not significant in the interaction model (B = .071, β = .131, p = .222). Conversely, career insight showed a significant relationship in the interaction model (B = .130, β = .237, p = .036), but not in the main effect model (B = .066, β = .120, p = .257). Career identity, career resilience, and intellectual curiosity did not show a significant relationship in the analysis of either model. Therefore, H1b and 4b were partially supported, but 2b, 3b, and 5b were not. In evaluating interaction effects on the proactive career behaviors-frequency, the regression analysis showed a significant contribution of only one the moderators, that of class standing. Class standing had a significant impact on the dependent variable by itself (B = .145, β = .267, p = .012), and also when moderating the relationship between intellectual curiosity and the dependent variable (B = -.114, β = -.238, p = .034). The resulting relationships can be seen in Figure 10. No other relationships were significant. Therefore, 8b5 is supported, but all other hypotheses in 6b, 7b, and 8b are not. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 102 Table 10: Regression Results for Proactive Career Behaviors-Frequency Dependent Variable Predictor Variable Step 1 (Main effect) Step 2 (Interaction effect) B SE B β t p B SE B β t p Proactive Career Behaviors- Frequency Career Insight .066 .058 .120 1.14 .257 .130 .061 .237 2.13 .036 Career Identity .070 .056 .129 1.26 .210 .049 .057 .090 .87 .389 Career Resilience -.067 .051 -.124 -1.31 .192 -.081 .052 -.148 -1.56 .122 Self- Knowledge .130 .050 .237 2.61 .010 .071 .058 .131 1.23 .222 Intellect. Curiosity .072 .051 .131 1.40 .164 .081 .056 .148 1.45 .152 Internship .048 .054 .088 .89 .379 Class Standing .145 .057 .267 2.57 .012 Division -.039 .048 -.071 -.80 .425 C Insight x Internship -.039 .069 -.071 -.56 .575 C Insight x Standing -.039 .066 -.068 -.59 .558 C Insight x Division .055 .062 .094 .88 .383 C Identity x Internship -.002 .073 -.004 -.03 .976 C Identity x Standing .122 .072 .213 1.70 .092 C Identity x Division .038 .062 .072 .61 .543 C Resilience x Internship -.025 .061 -.045 -.40 .688 C Resilience x Standing -.041 .057 -.079 -.72 .476 C Resilience x Division -.073 .055 -.140 -1.32 .190 Self- Knowledge x Internship -.046 .055 -.086 -.83 .408 Self- Knowledge x Standing .074 .055 .161 1.36 .176 Self- Knowledge x Division -.068 .059 -.135 -1.15 .252 Intellect. Curiosity x Internship -.027 .064 -.047 -.42 .673 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 103 Intellect. Curiosity x Standing -.114 .053 -.238 -2.15 .034 Intellect. Curiosity x Division -.001 .057 -.001 -.01 .990 Figure 10: A Moderator Relationship of Class Standing between Intellectual Curiosity and Proactive Career Behaviors-Frequency Finally, the overall models were evaluated for their significance and fit. All four of the regression models show a p-value such that we can reject the null that the models explain no more variance than an intercept-only model. Based on the adjusted r2, the full interaction model explained 30.5% of the variance in the activity measure, but only 24.3% of the variance in the frequency measure. These statistics can be seen in Table 11. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 104 Table 11: Regression Analysis Model Summaries Proactive Career Behaviors - Activity Proactive Career Behaviors - Frequency Main Effect Interactions Main Effect Moderators r .556 .663 .390 .624 Adjusted r2 .278 .305 .115 .243 F 10.180 3.273 4.095 2.659 p .000 .000 .002 .000 df 114 96 114 96 Sig. F Change .000 .242 .002 .013 Summary of Findings This section contains a summary of each hypothesis and whether or not it was supported. Additionally, all significant relationship can be seen in Figure 11. Hypothesis 1a: Student career insight will be positively related to proactive career behaviors-activity. SUPPORTED Hypothesis 1b: Student career insight will be positively related to proactive career behaviors-frequency. PARTIALLY SUPPORTED Hypothesis 2a: Student career identity will be positively related to proactive career behaviors-activity. SUPPORTED Hypothesis 2b: Student career identity will be positively related to proactive career behaviors-frequency. NOT SUPPORTED PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 105 Hypothesis 3a: Student career resilience will be positively related to proactive career behaviors-activity. NOT SUPPORTED Hypothesis 3b: Student career resilience will be positively related to proactive career behaviors-frequency. NOT SUPPORTED Hypothesis 4a: Student self-knowledge will be positively related to proactive career behaviors-activity. NOT SUPPORTED Hypothesis 4b: Student self-knowledge will be positively related to proactive career behaviors-frequency. PARTIALLY SUPPORTED Hypothesis 5a: Student intellectual curiosity will be positively related to proactive career behaviors-activity. NOT SUPPORTED Hypothesis 5b: Student intellectual curiosity will be positively related to proactive career behaviors-frequency. NOT SUPPORTED Hypothesis 6a: Having completed a required internship/practicum will moderate the relationship between career identity (6a1), career insight (6a2), career resilience (6a3), self-knowledge (6a4), intellectual PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 106 curiosity (6a5), and proactive career behaviors-activity. NOT SUPOPRTED Hypothesis 6b: Having completed a required internship/practicum will moderate the relationship between career identity (6b1), career insight (6b2), career resilience (6b3), self-knowledge (6b4), intellectual curiosity (6b5), and proactive career behaviors-frequency. NOT SUPPORTED Hypothesis 7a: The division of student’s major will moderate the relationship between career identity (7a1), career insight (7a2), career resilience (7a3), self-knowledge (7a4), intellectual curiosity (7a5), and proactive career behaviors-activity. ONLY 7a3 SUPPORTED Hypothesis 7b: The division of a student’s major will moderate the relationship between career identity (7b1), career insight (7b2), career resilience (7b3), self-knowledge (7b4), intellectual curiosity (7b5), and proactive career behaviors-frequency. NOT SUPPORTED Hypothesis 8a: A student’s class standing will moderate the relationship between career identity (8a1), career insight (8a2), career resilience (8a3), self-knowledge (8a4), intellectual curiosity (8a5), and proactive career behaviors-activity. ONLY 8a5 SUPORTED PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 107 Hypothesis 8b: A student’s class standing will moderate the relationship between career identity (8b1), career insight (8b2), career resilience (8b3), self-knowledge (8b4), intellectual curiosity (8b5), and proactive career behaviors-frequency. ONLY 8b5 SUPPORTED NOTE: Solid lines indicate a significant relationship was found. Dashed lines indicate a significant relationship between those independent and dependent variables was only found with the interaction of a moderator. Figure 11: Summary of Variable Relationships Proactive Career Behaviors- Attitude Division of Major Proactive Career Behaviors- Frequency Class Standing Intellectual Curiosity Career Insight Self-Knowledge Career Resilience Career Identity PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 108 Chapter 5: Discussion and Conclusion The following section will discuss the results provided in the previous chapter. Then, the theoretical and practical implications of the study are reviewed. Lastly, the limitations of this study and directions for future research are provided, and final conclusions are drawn. Discussion There is currently a gap in the literature explaining the voluntary engagement students demonstrate toward their career. This study closes part of that gap by identifying what impacts a student’s decision to proactively engage in career-related behaviors. The purpose of this study was to identify the relationships between career insight, career identity, career resilience, intellectual curiosity, and proactive career behaviors such as career exploration and networking in undergraduate college students. If these relationships are understood, future research can be conducted to develop interventions for increasing the frequency of proactive career behaviors. This is important as career self-management is an increasing necessity for today’s workforce. Beginning to develop career-focused engagement will benefit students in the long term. This study contributes to the gap in literature by showing that student’s engagement level in proactive career behaviors is influenced most by their level of career insight, second by their level of career identity, and supplementally by their level of self-knowledge and intellectual curiosity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 109 The results are discussed in three parts. First, the discussion is focused on the significant effects of the independent variables. Secondly, the moderator variables are reviewed, and lastly, the effects that weren’t supported in this study are discussed. Effects of Career Insight, Career Identity, and Self-Knowledge The most significant finding of this study was the clear relationship career insight had with proactive career behaviors. This relationship was significant in both the main and interaction model for proactive career behaviors-activity and in the interaction model for proactive career behaviors-frequency. Career insight is defined as “the ability to be realistic about oneself and ones’ career and to put these perceptions to use in establishing goals” (London & Noe, 1997, p. 62). In this study, career insight was measured using five items including: “I have a clear career goal”, “I’ve worked out a plan for achieving my career goal”, “My career goal is realistic and attainable”, “I am satisfied with my choice of major”, and “I am confident my major will prepare me for my next career-oriented step”. In a motivation model, career insight is viewed as the arousal component. Undergraduate college students who have clear career goals are much more likely to voluntary take steps toward that end. Further, they are more likely to think ahead about their career, develop the knowledge and skills necessary for their career even if not relevant now, and seek advice from others about their career. And they engage in these behaviors more often. These results make sense in light of an arousal component of motivation. Students’ interest and attention must first be initiated toward something in PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 110 order for it to motivate their behavior. Career insight provides that first spark toward their career activities, and if nurtured, that spark has significant potential to influence behavior. Career identity was found to be significantly related to the activity-based scale of proactive career behaviors, but not the frequency scale. Career identity is defined as “the extent to which one defines oneself by work. It consists of job, organizational, and professional involvement and needs for advancement, recognition, and a leadership role” (London & Noe, 1997, p. 62). In this study, career identity was measured using three items: “My major/career field has a great deal of personal significance”, “I strongly identify with my chosen major/career field”, and “I do not feel ‘emotionally attached’ to this major/career field” (reverse scored). When individuals internalize career as part of their identity, they are more likely to take proactive steps to prepare and care for the development of their career. Students who are able to see themselves as a nurse, or teacher, or business person while still in school, will be more likely to proactively take steps to make the future identity come to be. In this way, who they are becoming becomes part of who they are today as career plays a role to shape individual identity. It is interesting to note that although both career insight and career identity were significantly related to the proactive career behavior-activity scale (p = .000 and .000), they had only an insignificant effect on the frequency scale (career insight p = .257, career identity p = .210). The difference in these two scales was more about the scales used than the questions asked. The activity scale asked participants to state to what extent they agree with statements like “I am thinking ahead to the next few years and planning PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 111 what I need to do for my career”. In contrast, the frequency scale asked participants to indicate how often, in the previous 6 months, they had done things like “developed plans and goals for your future career”. This means that although career insight and career identity predicted if a student agreed that they have proactively cared for their career, there wasn’t a meaningful relationship with the frequency of those behaviors. The final independent variable that showed a significant relationship with proactive career behaviors was the two-item scale defined in this study as self- knowledge. It included the items including: “I feel I have a good understanding of my strengths and weaknesses” and “Since starting college, I’ve changed or revised my career goals based on new information I’ve received about myself or my situation”. This variable only showed a significant relationship with the frequency scale, meaning that although there wasn’t a significant impact on whether or not they proactively cared for their career, it did have an impact on the frequency. The results of the independent variables in this study showed that if educators want to increase the degree to which students voluntarily engage in career-related activities, they will get the greatest impact from helping students explore and define their career goals. Next to that, helping students gain a better understanding of themselves and internalizing their career as part of their overall identity will also show positive results. Effects of Division of Major and Class Standing There were two moderator variables in this study that influenced the strength of the hypothesized relationships. The division of the participant’s major influenced the size of the relationship between career resilience and proactive career behaviors-activity and PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 112 class standing influenced the size of the relationship between intellectual curiosity and proactive career behaviors, in both the activity and frequency model. It was expected that a student’s major would influence their career motivation, but it was shown to only influence the relationship with career resilience. This is the only place in the either of the models where career resilience had a significant impact—when the divisional interaction was added. Majors in the traditional undergraduate college at the university are divided into three divisions: one containing professionally related majors, one those in arts and humanities, and a third containing science-related majors. Of these, the professional programs majors (e.g. Nursing, Education, Business) are the most career focused and as such were expected to show higher connections in the study. The career resilience items included the following: “The costs associated with my chosen major/career field seem too great”, “Given the problems I encounter in this major/career field, I sometimes wonder if I will ever get enough out of it”, “Given the problems I encounter in this major/career field, I sometimes wonder if the personal burden is worth it”, and “The discomforts associated with my major/career field sometimes seem too great”. The lower participant’s score on career resilience, the more likely they were to agree with these statements. The sciences division showed the lowest level of proactive career behaviors regardless of their career motivation score, arts and humanities was in the middle, and the division showing the highest level of voluntary activities was in fact the professional programs. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 113 The slope of the regression line was also greatest with professional programs, showing a greater increase in proactive career behaviors with an increase in career resilience than in the other divisions. The questions for career resilience asked participants to weigh the burden of their major with the possible benefits. It is possible that the respondents in science-related majors perceived the burden of their field as higher than others—perhaps because of time commitments to labs or the high likelihood that graduate school will also be necessary to continue their chosen path causing them to put less effort into voluntary career care. It is also possible that respondents in the professionally-oriented majors such as business and nursing perceived the future benefits as greater in knowing well-paying jobs will likely be available when they graduate. Perhaps the clearer direct connection between their major and the job market was encouraging this higher slope. When participants in the professional majors saw the burdens as a worthwhile investment, they were much more likely to do something proactively to care for and nurture that career. This result can be informative for faculty in professionally-oriented majors. Faculty may not need to require students to network or seek mentoring relationships, rather they can provide help for students to see why the burdens of their education will be worth it for the benefit of their future career as this will increase the likelihood of students being motivated and working toward their career goals. However, faculty who teach in the arts or sciences may need to realize that even students with a high level of career resilience, probably won’t take these needed extra steps on their own. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 114 The other place in the studied models where a moderator variable significantly impacted a relationship was with the combination of intellectual curiosity and class standing, with both measures of proactive career behavior. An interesting result with activity scale was the clear groupings of differences in slopes by class standing. The slope of the line between intellectual curiosity and proactive career behaviors was much greater for freshmen, sophomores, and seniors than it was for juniors and graduates. For example, in the regression equation for freshman, the slope was 1.24, but for juniors, it was actually -.05. Meaning, for freshman, the more intellectually curious the student was the much more likely they were to engage in career behaviors on their own, with seniors and sophomores following a similar pattern. The slope for graduates was almost zero, showing their level of career activity had little to do with the intellectual curiosity. But the junior respondents’ negative slope meant that the more curious a student was, the less likely they were to engage in activities. It is important to note, however, that only two freshmen participated in this study and therefore caution is required when evaluating them as an independent group. The pattern was still there in the frequency scale, but the two groupings were not quite as distinct from each other. The slopes of the line were the highest from freshmen and sophomores, with seniors a bit more in between groups than as aligned freshmen and sophomores in the activity scale. In the frequency scale, the graduate slope was the one that was negative, meaning the frequency of their behaviors went down with increased curiosity. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 115 These differing slopes do have a lot to tell us about students in their career pathways. Freshmen and sophomores who are inherently curious about things will likely show higher levels of self-directed behaviors toward their career, and they’ll do it more frequently. This is during the stage when they are exploring options and choosing their majors. A curious under-class student was more actively engaging in this process than their non-curious counterparts. Similarly, senior year is a time of great exploration as students are preparing to graduate and looking for jobs. The intellectually curious senior initiated more and more frequent career activities as they are managing their transition to work, than a non-curious senior. So why then do juniors and graduates have such low to negative slopes? To start to explain this finding, it is important to note that the career behaviors of intellectually curious respondents were quite high regardless of their class standing (i.e., all the lines end high). What seems to set the juniors and graduates apart is where the lines begin. Even juniors and graduates who aren’t that intellectually curious, engaged in high levels of career behaviors. It is likely that these are the two periods of time when career behaviors are more necessary. For many, junior year is when students begin turning their mind toward professional expectations. They build resumes, they develop their first LinkedIn profile, and they start networking to find an internship or relevant summer job. The non-curious junior may not have the luxury of waiting to engage in these things like the non-curious freshman or sophomore. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 116 Similarly, because participants were surveyed in October and only those enrolled the previous spring were sampled, all working graduates had spent no more than five months in their job, and may still have been looking for a job. The frequency of career behaviors in those with low curiosity scores was much higher for graduates than any other class standing. It is likely that those graduates needed to do a lot of things for their career at that point, precisely because they weren’t likely to have done them when they were still a student. The intellectually curious graduate had a lower frequency rate of actions than any of the students, quite probably because they had already networked, built their resume, and gone on informational interviews as a student. An interesting follow-up study may be to what extent intellectual curiosity contributes to job placement. The results of this study would suggest that it is likely high. Non-Supported Effects It is also interesting to note the effects that weren’t supported by this study. Although career insight and career identity did have significant impact on proactive career behaviors, the impact of career resilience was only significant when moderated by students’ major. Statistically, as compared to the other three career motivation variables, career resilience had the lowest mean, the widest standard deviation, and was the only variable not significantly skewed toward the higher end of the scale. Educators may see this as a call to help build resilience in their students—to help them see their education as an investment that will have a return no matter how burdensome it may seem right now. Although, based on this study, that isn’t likely to motivate students to engage in career PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 117 behaviors, it may increase their level of persistence and hope which would benefit the students greatly. In addition, although intellectual curiosity had an effect when moderated by class standing, it had no other effect on its own or with any other moderator. By this we can learn that motivation to engage in career behaviors seems to be driven by career specific characteristics. A general intellectual curiosity, on its own, it not likely enough to initiate career behaviors. Another interesting finding is that whether or not a student had completed a required internship (or similar experience) was the only studied variable to show no significant impact anywhere in the model. 57.5% of survey participants had completed an internship or similar requirement, and 42.5% had not. This study indicates that if educators want to see more students voluntarily engaging in career behaviors, increasing internship requirements is unlikely to make a difference. This is similar to Carless and Prodan’s (2003) results who found no significant relationship between extensive practicum experience and career motivation in graduate students. Theoretical Implications This study provides several theoretical implications for the existing body of career development literature. Implications for the Theory of Career Motivation First, this study supports, and builds on, the existing literature of career motivation. In a 2006 literature review of career motivation in HRDR, Lopes wrote “The breadth of these publications illustrate that there has been, and continues to be, a good PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 118 deal of interest in career motivation” (p. 483). The literature reviewed in this study shows Lopes’s statement continues to be true. While previous literature has explored career motivation in various ways, it has also used various instruments, including ones by London (1983), Carson and Bedeian (1994), and Noe, Noe, and Bachhuber (1990). Consistency in instrumentation would make replication and analysis across studies more feasible. This study confirms the three- construct model of career insight, career identity, and career motivation has validity in the construct, however, it indicates a fourth construct of self-knowledge should be added to more clearly represent the theory. This fourth construct should be added to future instrumentation with greater intentionality and repetition than the two items found here. Future researchers would benefit from a clear instrument geared toward college students that did not have to be adapted from an employee-orientated measure. Further refinement of a theory of career motivation is necessary as this study confirms its importance. Career motivation, including career insight, career identity, and career resilience, has previously been shown to have positive effects in both employees and students alike. This study supports the literature steam by demonstrating that career motivation has an effect on students’ career engagement. Implications for the Theory of Proactive Career Behaviors Claes and Ruiz-Quintanilla argued in 1998 that “We know little about the influences on young workers’ proactive career behaviors” (p. 357). Subsequent research has shed some light on the topic. Research into proactive career behaviors now indicates its importance as individuals’ active engagement in career behaviors has positive results PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 119 for gaining employment (Greenleaf, 2014) especially after a job loss (Zikic & Klehe, 2006), as well as for career success in early career (De Vos et al, 2009), and has helped produce a higher ability of college students to find meaning in life (Shin et al., 2018). Research to date has identified a variety of things that influence proactive career behaviors including future work self salience (Strauss et al., 2012), directional hope (Hirschi, 2014), and exposure to a successful role model (Buunk et al., 2007). Because of their importance, career development literature would benefit from a more intentional exploration of a theory for proactive career behaviors. There are a wide range of similar constructs, three of which were reviewed in this study, but not clear salience in the field about what a theory of proactive career behavior is, how it is defined, or how it is measured. The majority of research done using the construct has been conducted in Europe. Replication and expansion of the theory in a US-based population will continue to be valuable. An interesting result of this study was the difference in relationship significance between the variables when proactive career behavior was measured by asking respondents to respond to statements of what they do, and when asking them to indicate how frequently they have engaged in those behaviors in the recent past. This shows that how the instrument asks the questions can influence the results. Additional salience as to whether each instrument is equally valid in measuring the same construct would be beneficial to the field. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 120 Implications for Related Theories in Career Development Career and vocational indecision is an important construct of study in career development literature. Ng and Feldman (2009) wrote about the need to understand vocational indecision. They argued: “vocational indecision can have major short-term and long-term effects on individuals and their employers. For example, vocational indecision in college may lower students’ sense of self-efficacy about their career management skills and the quality of their employment options” (pp. 309-310). The current study indicates the importance of career insight for students’ active engagement in career behaviors. Career insight and career indecision are likely two sides of the same coin. Further theory-building research could bridge the gap between these two constructs, potentially bringing together two bodies of literature. Practical Implications This study has practical results for higher education, including undergraduate faculty and career-oriented offices, and for HRD and career development professionals. Implications for Higher Education Previous literature has demonstrated that proactive career behaviors lead to positive outcomes for students. They lead to desired career outcomes and feelings of career success (De Vos et al., 2009), and explain both objective and subjective measures of employability during the school-to-work transition (Okay-Somerville & Scholarios, 2017). They can also significantly improve students’ perceived employability (Clements & Kamau,2017) and their actual chance of gaining employment (Greenleaf, 2014). PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 121 This study argued that educators should encourage proactive career behaviors. Okay-Somerville and Scholarios came to a similar conclusion and wrote “For those involved in career counseling, the findings suggest that students/graduates should be encouraged to engage in positive career management” (2017, p. 1287). The results of this study showed that if educators want to increase the degree to which students voluntarily engage in career-related activities, they will get the greatest impact from helping students explore and define their career goals. This is good news for educators because this is already a strong body of literature about vocational interests and career decision making. Numerous instruments and diagnostic tools also exist to help students explore their interests and then translate the results into career goals. In the interest of cost savings, it may be tempting for universities to cut career services departments or career-oriented curriculum from classes. This study shows that may be short sighted as the benefits received from the insight gained by students is the first step in a valuable journey to career success. Instead, career activities should be added to the curriculum, integrating career services into existing learning outcomes. In addition to establishing career goals, helping students gain a better understanding of themselves and internalizing their career as part of their overall identity will also show positive results. Additional research would need to be conducted to best understand how to do that. For example, does career identity increase with nursing majors when they wear scrubs to class or for science students through wearing personalized lab coats? This and other relationships could be explored. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 122 Additionally, this study has implications for internships which are common fixtures in higher education. Significant research has demonstrated positive outcomes for students who had participated in internship experiences. Nghia and Duyen (2019) summarize the literature of these benefits into 5 categories: 1) internships expand student’s professional knowledge, 2) internships facilitate the opportunity to practice what students learn in the classroom, 3) internships facilitate connections to key stakeholders such as employers and mentors, 4) internships advance students’ view of their career choices and fit, and 5) internships improve students’ attitude toward learning. Although internship experiences are highly valuable, they argued that they are seldom evaluated, largely because of a lack of instrumentation with which to do so. They then developed and tested a measure for internship effectiveness using multiple studies in multiple stages. The result was a 3-factor, 8-item student self-report instrument. Evaluating internships, with this or a similar instrument, would provide educators valuable feedback about the efficacy of their program. If, after evaluation, the internship experience seems to be falling short of the goal, Knouse and Fontenot (2008) offer 6 suggestions for improving the effectiveness of internships based on a review of the literature. They recommend internships include: 1) active student participation in the process, 2) active employer participation in the process, 3) clear expectations, 4) changing the prerequisites to reflect the predictors more closely related to intern success, 5) building mentoring into the internship program, and 6) having students keep a journal to reflect on their experiences. Educators who supervise PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 123 internship experiences and curricula would benefit from reviewing their programs to ensure these pieces are represented. Implications for Practitioners Additionally, this study has implications for organizational HRD practitioners and for career services practictioners. The need for career motivated employees is clear. The engagement of workers is declining, and this is costing employers billions of dollars each year (Saks & Gruman, 2014). At the same time, the rapid change in the contemporary business environment has made careers more complex and demands employees engage in proactive career self-management behaviors in order to keep pace (Akkermans, Brenninkmeijer, Hibers, & Blonk, 2012). Because of this, career counseling is increasingly concerned with getting clients engaged in proactive career management (Greenhaus, Callanan, & Godshalk, 2010). Understanding the engagement of the future workforce also begins with understanding the motivation of college students because they are a significant source of new employees for organizations (Polach, 2004). The moderator variable of class standing showed interesting results for understanding the new entrants into the workforce, specifically by looking at the class standing of graduate. Graduates did show a higher level of engagement with proactive career behaviors than most students. However, because graduates were sampled within approximately five months of their final semester and were asked about activities over the previous six months, the behaviors reported here were likely those the engaged in to get job. Additional research would need to be conducted to see if they sustained a higher level of career behaviors PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 124 over time, after they had been in their job for more than six months. This would be important as employees must engage in proactive career self-management behaviors in order to just keep pace with a rapidly changing work environment (Akkermans et al., 2012). This research also has implications for career services practitioners and departments. Most significantly, this study reinforces that the efforts taken to help students identify and articulate their career goals has positive outcomes. This study showed that the clearer the students’ goals, the more likely they were to voluntarily engage in activities to further that career, outside of the curriculum regardless of major, class standing, or whether or not they had completed an internship. Career counseling is increasingly concerned with getting clients engaged in proactive career management (Greenhaus, Callanan, & Godshalk, 2010) and helping students gain insight will spur them to higher levels of proactive engagement. Limitations Limitations were expected in this study and will be described in this section. First, limitations due to participant characteristics will be described. Then, limitations due to methods and due to measures will be discussed. Finally, limitations due to the underlying assumptions will be addressed. Limitations Due to Participant Characteristics Although the invited participants were selected through a random sample of the population, it is unlikely that each invited participated was equally likely to respond. Because of the voluntary nature of the survey, the time it took to complete, and the fact PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 125 that it was identified as a career-oriented survey, those who responded to the survey were likely to be a biased sample of students at least generally interested in careers. This was likely reflected in the higher response rate from participants in professionally-oriented majors, as described in Chapter 3. Additionally, because of the relatively homogenous nature of the university as a private, faith-based, liberal arts college in the suburban Midwest, the results may have been influenced by the homogeneity and demographics of the population and the sample. Because it is a private school, tuition costs, even with financial aid, may be higher than for other undergraduate options. That likely narrows the ranges of socio-economic backgrounds represented in the population and sample. The tuition costs also likely increase the utility with which they look upon their degree in gaining a future return on their investment. Almost half of the population (48%) and over half of the sample (56.4%) were from professionally-oriented majors. Because of this, there is likely an increased ethos of career-mindedness as this university that may not be as present at other schools. The lack of impact shown by career resilience may be an artifact of the population. The population under study was a traditional undergraduate college where 96.5% of students are under the age of 25. It is likely that they have not yet experienced career-based upheaval, which typically builds career resilience. Further, the faith-tradition of the university may have influenced the results of career identity. The Protestant tradition, such as at this university, often speaks of a person’s identity coming from God and God alone. This may have led to respondents PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 126 being less likely to say they identify with their career than would be seen if other universities were sampled. Finally, the population of this university is very homogenous in geographic background with over 80% of students reporting being from the state in which the university is located. Because of a low percentage of students from other parts of the country and world, a westernized view of career is likely most prevalent among the sample. Because of these limitations, the results would not be generalizable to students at other schools across the US or globe. Conducting this research in only one university may limit generalization to a broader population, especially because the studied university is not representative of all universities. It is possible a study conducted at a large public university would see very different results. Limitations Due to Method One limitation of the current research is that it was a cross-sectional, survey design conducted in only one method at only one university. The cross-sectional designed limited the ability to see how the variables under consideration grow and change over time. The current study is also limited in its ability to show causality, which is better studied through an experimental design. This study was also limited by the requirements of the sampled university’s Institutional Review Board. First, the IRB required the invitation email to students to be sent by the Office of the Registrar instead of by the researcher. This may have influenced who read the email as students may have been less likely to read an email coming from an office than they would have been if it had come from a person. Second, the response PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 127 rate was lower for graduates (10.8%) than for current students (12.4%). It is possible that graduates were less likely to check their university email post-graduation and did not see the invitation. Additionally, the IRB required that the invitation was only offered once and non-respondents were not allowed to be reminded about the survey. It is likely that more respondents would have participated with a reminder. Limitations Due to Measures All items in this study were self-reported, and has such have inherent limitations. Respondents may not have been objective in their responses, perhaps attempting to answer as they thought was socially desirable or expected in the situation. Additionally, responses may not accurately reflect the institutional records of variables such as GPA or class standing. Method bias may also have occurred as all sampling was done through one common method and all at the individual level. One measure, the frequency of proactive career behaviors, required participants to think back over the past 6 months and remember how often they had engaged in certain activities. This is an approximation, and unlikely to be accurate. Asking participants to record their activity over time in a log would have been a more accurate measure. Limitations Due to Underlying Assumptions As discussed previously, this study approached careers from a predominately Western view of careers that situates careers in a context of individual choice and autonomy. This traditional view of career has underlying assumptions in opportunity and privilege that doesn’t take into consideration the inequities experienced due to sexism, racism, sexual orientation, disability, and socio-economic status (Blustein, 2013). Views PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 128 of careers, due in part to the gig economy, are rapidly changing and our view of careers in the future will likely look very different from our views of the past. These underlying assumptions limit this current study and weakens its generalizability over time and contexts. Recommendations for Future Research There are multiple avenues that could be explored through further research. The first would be to explore the same questions but at multiple levels of analysis. Additional understanding could be gained by replicating the same questions at a variety of different universities in a variety of cultural settings to see if similar results are obtained, widening the breadth of the population. Conversely, the study could be replicated with different populations within the university. The current study only evaluated bachelor degree seeking students in one college within the university, the college focused on a traditional, typically 18-23 years old, full-time student in a residential environment. The university also has a college for adult students seeking bachelor degrees, a graduate school, and a seminary. Further research within a greater population of the university would be informative. It will be important for other researchers to replicate and test the phenomenon under a variety of contexts to see if the results described here are reliable and to extend their generalization to a wider population. A second avenue for future research could be to use different methods to measure the frequency of proactive career behaviors. In the current study, participants were asked to indicate how often they had done certain career-related tasks in the past six months. As such, this study was limited by participants’ accurate memory and estimation, as well as PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 129 likely different connotations of the descriptors such as “often” and “rarely”. This could be overcome by having participants keep a log over the course of time where they record the activities they do as they do them. This could also differentiate between a participant who “often” spends a few minutes on career behaviors and the participant who “often” spends hours. Additionally, the analysis could be conducted at a more detailed level of proactive career behaviors, exploring if there is any particular behavior (such as networking or reading trade publications) that is most affected by the independent variables. A third avenue for future research could be to explore the relationships through an experimental or quasi-experimental design, gaining more insight into causality. One option could be to collaborate with The Office of Career Development and Calling to identity students who are actively participating in their programs and services. Stratified sampling could then be conducted using two groups, those who are engaging with the career development office and those who are not to explore the difference between the two groups in their career motivation and intellectual curiosity. Another collaboration could be with the Office of Student Life which is responsible for all new student orientations. Sampling could be conducted as students enter the school, in contrast to the current sampling where students had already completed at least one year. Career-oriented interventions could then be designed to increase career motivation over a student’s degree path, longitudinally studying how and when career motivation grows. A fourth avenue for research would be to look for other possible moderator variables. The moderators identified in the current study had very little impact on the relationships of concern. Additional items were included in the current study to help PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 130 understand the population, but were not included in the scope of the research questions. A follow-up study could be conducted looking at age, gender, ethnicity, if the student is a first-generation college student, if they have related work experience, if they feel they have knowledgeable support for their career questions, and if they feel their career choice has be influenced by someone else to see if these variables explain additional variance when included in the present model. Fifth, additional research into the theories of career motivation and proactive career behaviors is warranted. The body of literature would benefit from clarity of career motivation from similar constructs such as career commitment and career indecision and clarity of proactive career behaviors from similar constructs of career readiness, self- directed learning, and continuous professional development. Additionally, further research into the reliability and validity of the instrumentation for these variables would contribute to research comparison and replication and well as potential for future meta- analyses. Sixth, interventions could be designed to increase student career insight and career identity and to see if that also increases proactive career behaviors. For example, at the end of each class students could be required to complete a career-related reflection. It could include questions like, “Something I’ve learned about myself in this class is…”, “This class has made me more/less interested in a career in…”. By recording their thoughts and reflecting on the class’s implications for their career, it is expected that students’ career insight would increase and, therefore, so would their proactive career behaviors. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 131 Finally, as recommended earlier, this study indicates additional research into what extent intellectual curiosity contributes to job placement would be meaningful. Conclusion The rapid change in the contemporary business environment has made careers more complex and demands employees engage in proactive career self-management behaviors in order to keep pace (Akkermans, Brenninkmeijer, Hibers, & Blonk, 2012). The current study explored the relationship between proactive career behaviors with career motivation as defined by London (1983) and intellectual curiosity as measured by the Need for Cognition short form by Cacioppo, Petty, and Kao (1984). The results indicate that there is a positive relationship between the career motivation components of career identity and career insight with proactive career behaviors, but not with the component of career resilience unless it is moderated by the student’s major. Additionally, student’s self-knowledge has positive relationships with proactive career behaviors, as does intellectual curiosity when moderated by class standing. The implications for practice are that educators who want to encourage students to increase their voluntary participation in proactive career behaviors may be able to do so by focusing primarily on student’s career insight and career identity, and secondarily their self-knowledge and intellectual curiosity. Further research could be done developing interventions and measuring their impact on students’ career behaviors. And if resources limit the scope of future interventions for either research or practice, an emphasis on career insight will likely make the most impact on students’ career behaviors PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 132 References Agbor-Baiyee, W. (1997). A cyclical model of student career motivation. College Student Journal, 31, 467-472. 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PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 155 Appendix A: London’s (1983) Conceptualization of Career Motivation Individual Characteristics Situational Characteristics Career Decisions and Behaviors Career Identity How central one’s career is to one’s identity Job involvement Job challenge Demonstrating job involvement Professional orientation Encouragement of professionalism Professional behavior Commitment to managerial work Importance of managing Managerial striving Identification with the organization Press for organizational commitment Demonstrating organizational commitment Primacy of work Work priority Showing devotion to work Need advancement Advancement opportunities Striving for advancement Need recognition Potential for recognition Seeking recognition Need dominance Leadership opportunities Trying to lead Financial motivation Potential for monetary gain Striving for money Ability to delay gratification Advancement controls Accepting slow progress Goal clarity Support for goal setting Establishing career goals Path goal clarity Path goal structure Establishing a career path Goal flexibility Organizational flexibility Changing goals Need to change Opportunity for change Making changes Social perceptiveness Visibility of organizational processes Responsiveness to social conditions Self-objectivity Feedback processes Self-monitoring Realism of expectations Realistic job information Forming and expressing realistic expectations Career decision making Favorability of decision context Decision making behavior Future time orientation Organization’s emphasis on long-term Instrumental behavior PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 156 Individual Characteristics Situational Characteristics Career Decisions and Behaviors Career Resilience The person’s resistance to career disruption in less than optimal environment Self-esteem Positive reinforcement Showing belief in oneself Need autonomy Encouragement of autonomy Striving for autonomy Adaptability Organizational change Demonstrating adaptability Internal control Amount of individual control Taking control Need achievement Opportunity for achievement Striving to achieve Initiative Opportunity for input Taking action for self- benefit Need creativity Support for creativity Creative behavior Inner work standards Demands for quality Quality of work Development orientation Support for development Seeking development Risk taking tendency Opportunity for and value of risk taking Taking risks Fear of failure Consequence of failure Response to failure Need security Job security Seeking security Tolerance of uncertainty and ambiguity Organizational uncertainty and ambiguity Seeking structure Competitiveness (negative relationship) Competitive situations Competing Career dependency (negative relationship) Paternalism Waiting for career direction Need supervisor approval (negative relationship) Supervisor’s consideration and control Deferent behavior Need for peer approval (negative relationship) Group cohesiveness Relying on others PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 157 Appendix B: Carson and Bedeian’s (1994) Instrument 1 My line of work/career field is an important part of who I am. Career Identity 2 This line of work/career field has a great deal of personal meaning to me. Career Identity 3 I do not feel “emotionally attached” to this line of work/ career field. (reverse scored) Career Identity 4 I strongly identify with my chosen line of work/ career field. Career Identity 5 I do not have a strategy for achieving my goals in this line of work/career field. (reverse scored) Career Insight 6 I have created a plan for my development in this line of work/career field. Career Insight 7 I do not identify specific goals for my development in this line of work. (reverse scored) Career Insight 8 I do not often think about my personal development in this line of work/career field. (reverse scored) Career Insight 9 The costs associated with my line of work/career field seem too great. (reverse scored) Career Resilience 10 Given the problems I encounter in this line of work/career field, I sometimes wonder if I get enough out of it. (reverse scored) Career Resilience 11 Given the problems I encounter in this line of work/career field, I sometimes wonder if the personal burden is worth it. (reverse scored) Career Resilience 12 The discomforts associated with my line of work/career field sometimes seems too great. (reverse scored) Career Resilience All items used a 5 point response from (1) strongly disagree to (5) strongly agree. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 158 Appendix C: Noe, Noe, and Bachhuber’s (1990) Instrument To what extent... 1 Do you have a specific career goal? Career Insight 2 Do you have a specific plan for achieving your career goal? Career Insight 3 Do you feel you are aware of your skill strengths and weaknesses? Career Insight 4 Do you ask co-workers you respect for feedback on your performance? Career Insight 5 Have you changed or revised your career goals based on new information you have received regarding yourself or your situation? Career Insight 6 Have you sought job assignments that will help you obtain your career goal? Career Insight 7 Have you taken the initiative to discuss your career goals with your boss? Career Insight 8 Have you asked your boss to discuss your specific skill strengths and weaknesses? Career Insight 9 Do you spend your free time on activities that will help your job? Career Identity 10 Have you taken courses toward a job-related degree? Career Identity 11 Have you joined professional organizations related to your career goal? Career Identity 12 Have you kept current on company affairs? Career Identity 13 Do you stay abreast of developments in your line of work? Career Identity 14 Do you accept compliments rather than discount them? Career Resilience 15 Do you believe other people will tell you that you have done a good job? Career Resilience 16 Do you reward yourself when you complete a project? Career Resilience 17 Do you take the time to do the best possible job on a task? Career Resilience 18 Do you set difficult but not impossible work goals? Career Resilience 19 Have you designed better ways of doing your work? Career Resilience 20 Have you accepted a job assignment for which you have little or no experience? Career Resilience 21 Have you made suggestions to others even though they may disagree? Career Resilience 22 Do you look for opportunities to interact with influential people in your organization? Career Resilience 23 Do you help co-workers with projects? Career Resilience 24 Have you made and maintained friendships with people in different departments? Career Resilience PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 159 25 Have you outlined ways of accomplishing jobs without waiting for your boss? Career Resilience 26 Have you evaluated your job performance against personal standards rather than comparing it with what others do? Career Resilience PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 160 Appendix D: London’s (1993) Instrument Please rate the extent to which you…. 1 Are you able to adapt to changing circumstances Career Resilience 2 Are you willing to take risks (actions with uncertain outcomes) Career Resilience 3 Welcome job and organizational changes (e.g. new assignments) Career Resilience 4 Can handle any work problems that come your way Career Resilience 5 Look forward to working with new and different people Career Resilience 6 Have clear career goals Career Insight 7 Have realistic career goals Career Insight 8 Know your strengths (the things you do well) Career Insight 9 Know your weaknesses (the things you are not so good at) Career Insight 10 Recognize what you can do well and cannot do well Career Insight 11 Define yourself by your work Career Identity 12 Work as hard as you can, even if it means frequently working long days and weekends Career Identity 13 Are you involved in your job Career Identity 14 Are proud to work for your organization Career Identity 15 Believe that your success depends on the success for your employer Career Identity 16 Are loyal to your employer Career Identity 17 See yourself as a professional and/or technical expert Career Identity PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 161 Appendix E: IRB Approval Letters PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 162 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 163 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 164 Appendix F: Participant Invitations ---------- Forwarded message --------- From: ** University Registrar Date: Fri, Oct 11, 2019 at 8:48 AM Subject: Fill Out a Career Survey for Chance to Win a $10 Amazon Gift Card To: ** University Registrar Dear Student, I am sending you this invitation on behalf of a doctoral student at the University of Minnesota who is doing research and is inviting you to participate. Because ** University's practice is not to give out your email address to third parties, I am sending the message, and the researcher does not have your name or contact information. You have been randomly selected from our current CAS students. If you agree to participate, you can follow the instructions she includes below. Her message to you is as follows: - - - - - - - - Hello, my name is Bethany Opsata, and I am an Associate Professor of Business here at **. I am currently conducting research about career attitudes and actions in undergraduate students at ** and would value your input. I am conducting this study as a student researcher in a doctoral program at the University of Minnesota. You were selected for this study as you were enrolled in the College of Arts and Sciences at ** during spring semester 2019. The survey is for research purposes only and will not be used in decision making. Please be assured that your responses will be kept completely confidential and any results will only be used in aggregate ways where individual responses cannot be identified. The survey should take you around 10 minutes to complete. Your participation in this research is voluntary, and you have the right to withdraw at any point during the study, for any reason, and without any negative effects on your relationship with me or with **. Participants who provide their email at the end of their completed survey will be entered to win a $10 Amazon gift certificate. For every 25 completed surveys, one winner will be randomly selected. (That means YOU have a 1/25 chance of winning!) Your email address will be used for the drawing purposes only, and will be separated from your responses during analysis. PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 165 Please feel free to contact me if you have any questions, or to discuss this research further. You may also contact **'s Institutional Review Board, who has approved this research, if you have questions, concerns, or complaints about this research or your rights as a participant. By completing this survey, you are granting consent to participate in this research. An information sheet about this study, including your rights as a participant, is provided here. Feel free to print a copy of this information for your records. To participate in the survey: Please click here. Thank you, Bethany Opsata - - - - - - [Name removed] Registrar [Contact information removed] PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 166 Appendix G: Participants by Major Academic Divisions n = 149 Professional Programs 84 Business and Economics 34 Education 17 Human Kinetics and Applied Health Sciences 10 Nursing 18 Social Work 5 Natural and Behavioral Sciences 35 Biological and Environmental Sciences 8 Chemistry 5 Computer Science 3 Mathematics 3 Neuroscience 4 Physics and Engineering 3 Psychology 9 Arts and Humanities 30 Art and Design 2 Biblical and Theological Studies 2 Communication Studies 9 Digital Humanities 0 English and Journalism 2 History 1 Music 1 Philosophy 1 Political Science 3 Reconciliation Studies 1 World Languages and Cultures 8 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 167 Appendix H: Demographics of Survey Participants Variables n Min Max Mean SD Skew Kurtosis Credits prior to matriculation 116 0 180 25.0 25.17 3.05* -.44 Current GPA 113 2.1 4.0 3.57 .402 -1.32* 1.62* Current Class Standing 120 Freshman = 1.7% (2) Sophomore = 10.0% (12) Junior = 30.8% (37) Senior = 35.0% (42) Graduate = 22.5% (27) Gender 120 Male = 23.3% (28) Female = 75.8% (91) Prefer not to respond = 0.8% (1) Ethnicity 120 Asian American/Asian = 4.2% (5) Hispanic/Latino/a = 2.5% (3) Native American/ Alaskan Native = 0.8% (1) White = 87.5% (105) Other = 1.7% (2) Prefer not to respond = 3.3% (4) First Generation 120 No = 87.5% (105) Yes = 12.5% (15) Completed a Required Internship 120 No = 42.5% (51) Yes = 57.5% (69) Related Work Experience 120 No = 19.2% (23) Yes = 80.8% (97) They Have Knowledgeable Support 120 No = 9.2% (11) Yes = 90.8% (109) Someone has Influenced their Career Choice 120 Not at all = 9.2% (11) A little = 53.3% (64) Quite a bit = 26.7% (32) Greatly = 10.8% (13) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 168 Appendix I: Instrument used for career identity, career insight, and career resilience Item responses through a 5-point Likert scale of Strongly Disagree to Strongly Agree Item Description Variable Source 1 I have a clear career goal. Career Insight Noe et al. (1990) 2 I’ve worked out a plan for achieving my career goal. Career Insight Noe et al. (1990) 3 My career goal is realistic and attainable. Career Insight Noe et al. (1990) 4 I feel I have a good understanding of my strengths and weaknesses. Career Insight Noe et al. (1990) 5 Since starting college, I’ve changed or revised my career goals based on new information I’ve received about myself or my situation. Career Insight Noe et al. (1990) 7 My major/career field is an important part of who I am. Career Identity Carson & Bedeian (1994) 8 My major/career field has a great deal of personal significance. Career Identity Carson & Bedeian (1994) 9 I strongly identify with my chosen major/career field. Career Identity Carson & Bedeian (1994) 10 I do not feel “emotionally attached” to this major/ career field. (reverse scored) Career Identity Carson & Bedeian (1994) 14 The costs associated with my chosen major/ career field seem too great. (reverse scored) Career Resilience Carson & Bedeian (1994) 15 Given the problems I encounter in this major/career, I sometimes wonder if I will ever get enough out of it. (reverse scored) Career Resilience Carson & Bedeian (1994) 16 Given the problems I encounter in this major/career field, I sometimes wonder if the personal burden is worth it. (reverse scored) Career Resilience Carson & Bedeian (1994) 17 The discomforts associated with my major/career field sometimes seem too great. (reverse scored) Career Resilience Carson & Bedeian (1994) 18 I am satisfied with my choice of major. Career Resilience Opsata PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 169 19 I am confident my major will prepare me for my next career-oriented step (e.g., finding a job, getting into grad school). Career Resilience Opsata PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 170 Appendix J: Instrument used for intellectual curiosity (Need for cognition scale – short form) Item responses through a 5-point Likert scale of Strongly Disagree to Strongly Agree * - This item is reverse scored Item Description Variable Source 1 I would prefer complex to simple problems. Intellectual Curiosity Cacioppo et al., (1984) 2 I like to have the responsibility of handling a situation that requires a lot of thinking. Intellectual Curiosity Cacioppo et al., (1984) 3 Thinking is not my idea of fun.* Intellectual Curiosity Cacioppo et al., (1984) 4 I would rather do something that requires little thought than something that is sure to challenge my thinking abilities.* Intellectual Curiosity Cacioppo et al., (1984) 5 I try to anticipate and avoid situations where there is likely a chance I will have to think in depth about something.* Intellectual Curiosity Cacioppo et al., (1984) 6 I find satisfaction in deliberating hard and for long hours. Intellectual Curiosity Cacioppo et al., (1984) 7 I only think as hard as I have to.* Intellectual Curiosity Cacioppo et al., (1984) 8 I prefer to think about small, daily projects to long-term ones.* Intellectual Curiosity Cacioppo et al., (1984) 9 I like tasks that require little thought once I’ve learned them.* Intellectual Curiosity Cacioppo et al., (1984) 10 The idea of relying on thought to make my way to the top appeals to me. Intellectual Curiosity Cacioppo et al., (1984) 11 I really enjoy a task that involves coming up with new solutions to problems. Intellectual Curiosity Cacioppo et al., (1984) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 171 12 Learning new ways to think doesn’t excite me too much.* Intellectual Curiosity Cacioppo et al., (1984) 13 I prefer my life to be filled with puzzles I must solve. Intellectual Curiosity Cacioppo et al., (1984) 14 The notion of thinking abstractly is appealing to me. Intellectual Curiosity Cacioppo et al., (1984) 15 I would prefer a task that is intellectual, difficult, and important to one that is somewhat important but not does not require much thought. Intellectual Curiosity Cacioppo et al., (1984) 16 I feel relief rather than satisfaction after completing a task that required a lot of mental effort.* Intellectual Curiosity Cacioppo et al., (1984) 17 It’s enough for me that something gets the job done; I don’t care how or why it works.* Intellectual Curiosity Cacioppo et al., (1984) 18 I usually end up deliberating about issues even when they do not affect me personally. Intellectual Curiosity Cacioppo et al., (1984) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 172 Appendix K: Instrument used for proactive career behaviors (career engagement scale) Items 1-19 responses through a frequency scale of “Not including activities that are required for a class, to what extent have you in the past 6 months…. 1) Not at all, 2) Rarely, 3) Sometimes, 4) Often. Items 20-32 responses through a 5-point Likert scale of 1) Strongly Disgree, 2) Disagree, 3) Neutral, 4) Agree, 5) Strongly Agree Item Description Variable Source 1 Actively sought to design your professional future Proactive Career Behaviors Hirschi & Freund (2014) 2 Undertaken activities to achieve your career goals Proactive Career Behaviors Hirschi & Freund (2014) 3 Cared for the development of your career Proactive Career Behaviors Hirschi & Freund (2014) 4 Developed plans and goals for your future career Proactive Career Behaviors Hirschi & Freund (2014) 5 Sincerely thought about personal values, interests, abilities, and weaknesses Proactive Career Behaviors Hirschi & Freund (2014) 6 Collected information about employers, professional development opportunities, or the job market in your desired area Proactive Career Behaviors Hirschi & Freund (2014) 7 Established or maintained contacts with people who can help you professionally Proactive Career Behaviors Hirschi & Freund (2014) 8 Voluntarily participated in training or attended events to support your career Proactive Career Behaviors Hirschi & Freund (2014) 9 Voluntarily accepted roles or positions that will help you progress professionally Proactive Career Behaviors Hirschi & Freund (2014) 10 Voluntarily read books related to your field Proactive Career Behaviors Opsata PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 173 11 Paid attention to current events and developments in your field through reading newspapers, journals, or other periodicals Proactive Career Behaviors Opsata 12 Initiated a conversation with your advisor about your career Proactive Career Behaviors Opsata 13 Initiated a conversation with a professor to better understand careers in a field, outside of the requirements of a class Proactive Career Behaviors Opsata 14 Actively discussed your future career goals with your friends Proactive Career Behaviors Opsata 15 Actively discussed your future career goals with your family Proactive Career Behaviors Opsata 16 Built or revised your resume Proactive Career Behaviors Opsata 17 Looked for current job openings Proactive Career Behaviors Opsata 18 Built or revised a professional profile on LinkedIn or similar website Proactive Career Behaviors Opsata 19 I am planning what I want to do in the next few years of my career. Proactive Career Behaviors Strauss et al. (2012) 20 I am thinking ahead to the next few years and planning what I need to do for my career. Proactive Career Behaviors Strauss et al. (2012) 21 I engage in career path planning. Proactive Career Behaviors Strauss et al. (2012) 22 I have recently begun to think more about what I would like to accomplish in my career. Proactive Career Behaviors Strauss et al. (2012) 23 I develop skills which may not be needed so much now, but will be in future positions. Proactive Career Behaviors Strauss et al. (2012) 24 I gain experience in a variety of areas to increase my knowledge and skills. Proactive Career Behaviors Strauss et al. (2012) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 174 25 I develop knowledge and skills in tasks critical to my future work life. Proactive Career Behaviors Strauss et al. (2012) 26 I seek advice from others about additional training or experience I need in order to improve my future work prospects. Proactive Career Behaviors Strauss et al. (2012) 27 I initiate talks with others about training or work assignments I need to develop skills that will help my future work prospects. Proactive Career Behaviors Strauss et al. (2012) 28 I make my advisor aware of my work aspirations and goals. Proactive Career Behaviors Strauss et al. (2012) 29 I am building a network of contacts and friendships with other students to obtain information about how to do my work or determine what is expected of me. Proactive Career Behaviors Strauss et al. (2012) 30 I am building a network of contacts or friendships to provide me with help or advice that will further my work chances. Proactive Career Behaviors Strauss et al. (2012) 31 I am building a network of colleagues I can call on for support. Proactive Career Behaviors Strauss et al. (2012) PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 175 Appendix L: Instrument used for variables to understand the population Item Description Possible Answers Variable Type 1 Email Address (voluntary question used for gift card winners) Nominal 2 Major Varies Nominal 3 Approximately how many credits had you completed prior to entering **? 0- Ratio 4 Current Class Standing Freshman Sophomore Junior Senior Graduate Ordinal 5 Self-Report Current Cumulative GPA 0-4.0 Ratio 6 Gender Male Female Non-binary/third gender I prefer not to respond Nominal 7 Of the following, please mark the one racial or ethnic group with which you most identify. African American/ Black Asian American/ Asian Hispanic/Latino/a Middle Eastern/ North African Native American/ Alaskan Native Native Hawaiian/ Other Pacific Islander White Other I prefer not to respond Nominal 8 Are you a first generation college student? Yes No I prefer not to respond Nominal PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 176 9 Have you already completed a career- related internship or practicum as part of your required coursework? Yes No Nominal 10 Have you had past work experience outside of a school requirement that you consider relevant to your future career? Yes No Nominal 11 Do you feel you have access to knowledgeable support to answer questions about your career? Yes No Nominal 12 To what extent has someone else (e.g., family or friends) influenced your career choice? Greatly Moderately A little Not at all Ordinal PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 177 Appendix M: Histograms of Key Variables PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 178 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 179 PROACTICE CAREER BEHAVIORS IN COLLEGE STUDENTS 180