Uygulamalı Eğitim Modeli İçin Firma Seçim Kriterlerinin Belirlenmesi ve Bir Sanayi Üniversitesinde Vaka Çalışması

Abstract

Günümüzde tecrübeli mezun kavramı, mezuniyet sonrası firmaların öğrencilerden beklentilerindeki ve işsizlik oranındaki artış nedeniyle son derece önemli bir araştırma konusu haline gelmiştir. Bu durum eğitimde uygulamalı eğitim modelinin geliştirilmesini beraberinde getirmektedir. Uygulamalı eğitim kapsamında üniversitelerle firmalar arasında “Üniversite-Sanayi İş birliği” anlaşmaları yapılmaktadır. Ancak uygulamalı eğitim modelinin yeni bir kavram olması, literatürde firmaların adayları ve öğrencileri seçmeleri konularına ağırlık verilmesi, uygulamalı eğitim modelinden beklenen çıktının azalmasına sebep olmaktadır. Bu kapsamda çalışmada, sanayi üniversitesinde uygulamalı eğitim modelinde, öğrencilerin eğitim görecekleri firmaların belirlenebilmesi için uzman görüşü alınarak, firma seçimi için kriter havuzu oluşturulmuştur. Kriter havuzundan nihai kriterlerin belirlenebilmesi için farklı sektörlerden uzmanlarla saha çalışması gerçekleştirilmiştir. Saha çalışması sonucunda kriterler ana ve alt kriterler şeklinde sınıflandırılarak kapsamlı bir kriter havuzu oluşturulmuştur. Çok kriterli karar verme yöntemi olan Analitik Hiyerarşi Prosesi yöntemi kullanılarak uzman görüşlerinden elde edilen veriler ile kriterlerin önem ağırlıkları nicel olarak değerlendirilmiştir. Yapılan nicel analizler sonucunda en yüksek önem ağırlığına sahip kriterler, firmaların gelişmiş bilişim alt yapısı, firmalarda daha önce uygulamalı eğitime alınmış veya stajyer olarak bulunmuş öğrencilerin ilgili firmada istihdam edilme oranı, firmaların Türkiye’nin önde gelen sanayi kuruluşları ile yürütmüş olduğu proje sayısı ve firmada çalışan beyaz yaka sayısının / toplam çalışan sayısına oranı şeklinde tespit edilmiştir.

Keywords

• : Firma seçimi
• Uygulamalı eğitim
• Çok kriterli karar verme
• Üniversite-sanayi işbirliği
• AHP yöntemi
• AHP method
• Multi-criteria decision making
• Company selection
• Applied education
• University-industry cooperation

Determination of Company Selection Criteria for an Applied Education Model and a Case Study at an Industrial University

Abstract

Nowadays, the concept of experienced graduates has become an extremely important research topic due to the increase in the expectations of companies from students and the unemployment rate after graduation. This situation brings with it the development of an applied educational model in education. Within the scope of applied education, “University-Industry Cooperation” agreements are made between universities and companies. However, the fact that the applied education model is a new concept, the emphasis in the literature on the issues of companies choosing candidates and students, leads to a decrease in the expected output from the applied education model. In this context, in the study, in the applied education model at the industrial university, a criteria was created for the selection of companies by taking the expert opinion in order to determine the companies that students will be education in. Field work was carried out with experts from different sectors in order to determine the final criteria from the criteria. As a result of the field work, criteria were classified into main and sub-criteria and a comprehensive criteria was created. Using the Analytical Hierarchy Process method, which is a multi-criteria decision-making method, the data obtained from expert opinions and the importance weights of the criteria were quantitatively evaluated. Quantitative analysis was performed with high importance weights of the criteria found in advanced ICT infrastructure companies or firms as an intern students received practical educaton in the relevant company before the employment rate of Turkey's leading industrial companies and companies number of projects working at the company that are conducted with the number of white-collar / total ratio of the number of employees in the form have been identified.

Keywords

• AHP method
• Multi-criteria decision making
• Company selection
• Applied education
• University-industry cooperation

References

1. [1] S. Meredith and M. Burkle, “Building bridges between university and industry: Theory and practice,” Education and Training, vol. 50, no. 3, pp. 199–215, 2008.
2. [2] Z. King, “New or traditional careers? A study of UK graduates’ preferences,” Human Resource Management Journal, vol. 13, no. 1, pp. 5–26, Jan. 2003.
3. [3] N. M. Breakey, R. N. S. Robinson, and L. G. Beesley, “Students Go a ‘Waltzing Matilda’—A regional tourism knowledge exchange through ınnovative ınternships,” Journal of Teaching in Travel & Tourism, vol. 8, no. 2–3, pp. 223–240, 2009.
4. [4] J. P. Dickerson, “The realistic preview may not yield career satisfaction,” International Journal of Hospitality Management, vol. 28, no. 2, pp. 297–299, Jun. 2009.
5. [5] J. M. Nunley, A. Pugh, N. Romero, and R. A. Seals, “College major, internship experience, and employment opportunities: Estimates from a résumé audit,” Labour Economics, vol. 38, pp. 37–46, Jan. 2016.
6. [6] M. v. Hejmadi, K. Bullock, V. Gould, and G. D. Lock, “Is choosing to go on placement a gamble? Perspectives from bioscience undergraduates,” Assessment & Evaluation in Higher Education, vol. 37, no. 5, pp. 605–618, Aug. 2011.
7. [7] J. M. Luo and C. F. Lam, “Qualitative analysis of satisfying and dissatisfying factors in a university–ındustry cooperation programme,” Education Sciences, vol. 9, no. 1, pp. 56, Mar. 2019.
8. [8] L. H. N. Fong, H. A. Lee, C. Luk, and R. Law, “How do hotel and tourism students select internship employers? A segmentation approach,” Journal of Hospitality, Leisure, Sport & Tourism Education, vol. 15, no. 1, pp. 68–79, Jul. 2014.

9. [9] T. Dornan, “Workplace learning,” Perspectives on Medical Education, vol. 1, no.1, pp. 15–23, 2012.
10. [10] S. Kitto, J. Goldman, M. H. Schmitt, and C. A. Olson, “Examining the intersections between continuing education, interprofessional education and workplace learning,” J Interprof Care, vol. 28, no. 3, pp. 183–185, 2014.
11. [11] A. Nederveld and Z. L. Berge, “Flipped learning in the workplace,” Journal of Workplace Learning, vol. 27, no. 2, pp. 162–172, Mar. 2015.
12. [12] B. Murray-Davis, M. Marshall, and F. Gordon, “From school to work: Promoting the application of pre-qualification interprofessional education in the clinical workplace,” Nurse Education in Practice, vol. 12, no. 5, pp. 289–296, Sep. 2012.
13. [13] P. Tynjälä, “Perspectives into learning at the workplace,” Educational Research Review, vol. 3, no. 2, pp. 130–154, Jan. 2008.
14. [14] A. Roberts, “Reflective practice ınternational and multidisciplinary perspectives encouraging reflective practice in periods of professional workplace experience: the development of a conceptual model,” Reflective Practice, vol. 10, no. 5, pp. 633-644, 2009.
15. [15] M. Clarke, “Rethinking graduate employability: the role of capital, individual attributes and context,” Studies in Higher Education, vol. 43, no. 11, pp. 1923–1937, Nov. 2017.
16. [16] G. Feijoo et al., “Potential impact on the recruitment of chemical engineering graduates due to the industrial internship,” Education for Chemical Engineers, vol. 26, pp. 107–113, Jan. 2019.
17. [17] W. Schulz, I. Maas, and M. H. D. van Leeuwen, “Employer’s choice – Selection through job advertisements in the nineteenth and twentieth centuries,” Research in Social Stratification and Mobility, vol. 36, pp. 49–68, Jun. 2014.
18. [18] J. O. Ekwoaba, U. U. Ikeije, and N. Ufoma, “The impact of recruitment and selection criteria on organizational performance,” Global Journal of Human Resource Management, vol. 3, no. 2, pp. 22–33, 2015.
19. [19] T. Moore and J. Morton, “The myth of job readiness? Written communication, employability, and the ‘skills gap’ in higher education,” Studies in Higher Education, vol. 42, no. 3, pp. 591–609, Mar. 2015.
20. [20] U. J. Wiersma and R. Kappe, “Selecting for extroversion but rewarding for conscientiousness,” European Journal of Work and Organizational Psychology, vol. 26, no. 2, pp. 314–323, Mar. 2016.
21. [21] H. L. Clark, R. E. Cole, and L. L. K. Funderburk, “US military dietetic ınternship and graduate program: retrospective analysis of selection criteria and student success,” Journal of the Academy of Nutrition and Dietetics, vol. 118, no. 6, pp. 1057–1064, Jun. 2018.
22. [22] R. M. Sladek, C. Burdeniuk, A. Jones, K. Forsyth, and M. J. Bond, “Medical student selection criteria and junior doctor workplace performance,” BMC Medical Education, vol. 19, no. 1, pp. 1–8, Oct. 2019.
23. [23] Z. Dugger, G. Halverson, B. McCrory, and D. Claudio, “Principal component analysis in MCDM: An exercise in pilot selection,” Expert Systems with Applications, vol. 188, pp. 115984, Feb. 2022.
24. [24] F. A. F. Ferreira, D. Kannan, I. Meidutė-Kavaliauskienė, and I. M. T. Vale, “A sociotechnical approach to vaccine manufacturer selection as part of a global immunization strategy against epidemics and pandemics,” Annals of Operations Research 2021, pp. 1–30, Jan. 2022.
25. [25] A. Bakalo, “The role of employee recruitment and selection on the organizational performance (Acase Mızan Aman Town),” Academy of Marketing Studies Journal, vol. 26, no. 1, pp. 1–7, 2022.
26. [26] E. Triantaphyllou, “Multi-criteria decision making methods,” Applied Optimization, 1rd ed., vol. 44, Boston, MA: Springer, 2000, pp. 5–21.
27. [27] M. Beynon, “DS/AHP method: A mathematical analysis, including an understanding of uncertainty,” European Journal of Operational Research, vol. 140, no. 1, pp. 148–164, Jul. 2002.