Modeling the determining factors in career planning of sports science faculty students: A principal component analysis approach

Career refers to the professional activities individuals carry out. In the career planning process, individuals determine their goals by considering their abilities, interests, and values and work in a systematic and planned manner in line with these goals (Lent & Brown, 2013). While correct career planning can enable individuals to use their potential at the highest level, universities can guide individuals' career planning process. Universities can manage the lack of system-level policies and practices through the organizations they carry out and improve employability by providing individuals with the necessary knowledge and skills through education (Bradley et al., 2021). While many faculties in universities serve this purpose, one of these faculties is the Faculty of Sports Sciences. Sports science faculties are specifically designed to meet the needs of professionals in the sports industry. These faculties include special education programs such as physical education and sports, coaching training, exercise science, and sports psychology (Haff et al., 2010), and students graduating from these faculties can have career opportunities in various sectors (Emery et al., 2012). The demand for sports science graduates is increasing as the global sports industry grows. For example, the employment rate in the sports sector in European Union countries has increased by 2.35% in recent years (European Commission, 2018). Moreover, researchers have reported that the number of sports industry participants globally has reached 4.522 million, and the primary development number of the sports industry is 156,000 (Li et al., 2022). Although workforce needs in the sports industry are increasing daily, graduate labor markets are becoming increasingly complex, and students need sharpened skills to manage their careers effectively (Jackson & Wilton, 2017). However, researchers have reported that students have low levels of participation in career service activities at the university and poor career competency skills (Bradley et al., 2021). The career planning process of university students is a complex phenomenon affected by both internal and external factors. For example, gender may significantly affect the career planning process. Researchers provide empirical evidence that women are underrepresented in the business sector due to socialization and organizational context (Rocha & van Praag, 2020). Similarly, researchers state that ability and motivation change with age and may affect career planning (Kooij et al., 2014). Moreover, the career planning process can be affected by external factors such as employment status (Hirschi et al., 2017), university department (Porter & Umbach, 2006), and skills and certifications (Werthner & Trudel, 2009). It is crucial to identify the factors that influence the career planning process to provide practical career guidance and tailor educational programs to meet the needs and expectations of students. Considering that many internal and external factors affect the career planning process, there is a need for studies with larger samples and different populations regarding career planning in sports sciences (Spittle et al., 2021). Additionally, researchers claim that career planning processes may have different moderators in various countries (Jiang et al., 2019). Finally, the statistical and methodological procedures applied by existing studies may pose limitations in revealing the complex structure of the career planning process. Results obtained from qualitative studies may not be generalizable to large populations (Polit & Beck, 2010). Quantitative analyses, such as hypothesis testing, can lead to problems such as multicollinearity and noise (Creswell & Creswell, 2017). Moreover, tests based on group means may be insufficient to provide insight into the details of the data set. Therefore, the principal component analysis (PCA) approach can be a valuable tool in revealing the underlying structure of the career planning process. PCA can make the data structure more understandable by reducing multidimensional data sets into smaller components. In addition, revealing hidden structures in the data set can better explain the relationships between variables and eliminate the limitations in quantitative research (Jolliffe, 2002). To our knowledge, no PCA study in the literature regarding the career planning process in sports sciences exists. In addition, no study has been conducted on the moderators that affect the career planning processes of students at the faculty of sports sciences in Turkey. Therefore, the current study may offer a unique perspective to the literature. REFERENCE Bradley, A., Quigley, M., & Bailey, K. (2021). How well are students engaging with the careers services at university? Studies in Higher Education, 46(4), 663–676. https://doi.org/10.1080/03075079.2019.1647416 Commision, E. (2018). Study on the economic impact of sport through sport satellite accounts. Publications Office of the European Union. https://doi.org/10.2766/156532 Emery, P. R., Crabtree, R. M., & Kerr, A. K. (2012). The Australian sport management job market: an advertisement audit of employer need. Annals of Leisure Research, 15(4), 335–353. https://doi.org/10.1080/11745398.2012.737300 Haff, G. G., Bishop, D., Hoffman, J., Kawamori, N., Newton, R. U., Sands, B., & Stone, M. (2010). Sport science. Strength and Conditioning Journal, 32(2), 33–45. https://doi.org/10.1519/SSC.0B013E3181D59C74 Lent, R. W., & Brown, S. D. (2013). Social cognitive model of career self-management: Toward a unifying view of adaptive career behavior across the life span. Journal of Counseling Psychology, 60(4), 557–568. https://doi.org/10.1037/A0033446 Li, M., Shi, Y., & Peng, B. (2022). The Analysis and Research on the Influence of Sports Industry Development on Economic Development. Journal of Environmental and Public Health, 2022(1), 3329174. https://doi.org/10.1155/2022/3329174 Hirschi, A., Nagy, N., Baumeler, F., Johnston, C. S., & Spurk, D. (2017). Assessing Key Predictors of Career Success: Development and Validation of the Career Resources Questionnaire. Journal of Career Assessment, 26(2), 338–358. https://doi.org/10.1177/1069072717695584 Jackson, D., & Wilton, N. (2017). Perceived employability among undergraduates and the importance of career self-management, work experience and individual characteristics. Higher Education Research & Development, 36(4), 747–762. https://doi.org/10.1080/07294360.2016.1229270 Jiang, Z., Newman, A., Le, H., Presbitero, A., & Zheng, C. (2019). Career exploration: A review and future research agenda. Journal of Vocational Behavior, 110, 338–356. https://doi.org/10.1016/J.JVB.2018.08.008 Jolliffe, I. T. (2002). Principal Component Analysis. In Encyclopedia of Statistics in Behavioral Science (2nd ed., Issue 3). Springer Science & Business Media. https://doi.org/10.2307/1270093 Polit, D. F., & Beck, C. T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47(11), 1451–1458. https://doi.org/10.1016/J.IJNURSTU.2010.06.004 Porter, S. R., & Umbach, P. D. (2006). College major choice: An analysis of person-environment fit. Research in Higher Education, 47(4), 429–449. https://doi.org/10.1007/S11162-005-9002-3/TABLES/6 Rocha, V., & van Praag, M. (2020). Mind the gap: The role of gender in entrepreneurial career choice and social influence by founders. Strategic Management Journal, 41(5), 841–866. https://doi.org/10.1002/SMJ.3135 Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications. SAGE Publications. Kooij, D. T. A. M., Jansen, P. G. W., Dikkers, J. S. E., & de Lange, A. H. (2014). Managing aging workers: a mixed methods study on bundles of HR practices for aging workers. The International Journal of Human Resource Management, 25(15), 2192–2212. https://doi.org/10.1080/09585192.2013.872169 Spittle, M., Daley, E. G., & Gastin, P. B. (2021). Reasons for choosing an exercise and sport science degree: Attractors to exercise and sport science. Journal of Hospitality, Leisure, Sport & Tourism Education, 29, 100330. https://doi.org/10.1016/J.JHLSTE.2021.100330 Werthner, P., & Trudel, P. (2009). Investigating the Idiosyncratic Learning Paths of Elite Canadian Coaches. International Journal of Sports Science & Coaching, 4(3), 433–449. https://doi.org/10.1260/174795409789623946

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