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Comparative Analysis of Higher Education Financing Policies Used by OECD Member Countries and Financing Policy Proposal for Türkiye

Year 2024, Volume: 7 Issue: 1, 73 - 103, 29.05.2024
https://doi.org/10.53048/johass.1482714

Abstract

The Turkish higher education system has developed remarkably in parallel with the developments and changes in the world today. With the ease of access to higher education for students and the increase in the number of students, higher education costs are increasing. This situation puts the higher education system under financial pressure in countries that provide higher education financing from public sources. In this study, higher education financing methods used worldwide are compared and the most appropriate financing method for Türkiye is discussed. For this purpose, the Entropy method was used in weighting the criteria determined for the evaluation of financing policies, and the performance analysis of the alternatives was carried out with the TOPSIS method, which is one of the multi-criteria decision-making methods. Alternative decision options for financing higher education are based on "No Fee", "Pre-charging" and "Income-Contingent Loan-ICL" methods and the main criteria are enrollment, education expenditures and labor force. In this context, sub-criteria were created and the financing methods used by OECD countries were analyzed. Within the scope of the study, it has been determined that the financing methods used by Norway, the Netherlands and the United Kingdom in higher education systems are in the top three. In this context, it has been determined that the "Income-Contingent Loan" method used by the first and third ranked countries is the most preferred method in terms of performance.

References

  • Agrawal, V. P., Kohli, V., & Gupta, S. (1991). Computer aided robot selection: the ‘multiple attribute decision making’approach. The International Journal of Production Research, 29(8), 1629-1644. https://doi.org/10.1080/00207549108948036
  • Akça, H. (2012). "Yükseköğretimin Finansmanı ve Türkiye İçin Yükseköğretim Finansman Modeli Önerisi". Yönetim ve Ekonomi Dergisi, 19 (1), 91-104
  • ATO, Australian Taxation Office (2024). (Study and training loan indexation rates | Australian Taxation Office (ato.gov.au) online,22.03.2024)
  • Australian Goverment (2024). 2024 Commonwealth Supported Places and HECS-HELP İnformation,. (https://www.studyassist.gov.au/system/files/documents/2023-12/Final%202024%20CSP%20and%20HECS-HELP%20booklet.pdf , online,22.03.2024)
  • Aydın, M. S. (2014). Türkiye'de Yükseköğretimin Finansmanı. Marmara Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, İstanbul.
  • BAföG.(2024). Bundesgesetz über individuelle Förderung der Ausbildung (Bundesausbildungsförderungsgesetz - BAföG) , "Bundesausbildungsförderungsgesetz in der Fassung der Bekanntmachung vom 7. Dezember 2010 (BGBl. I S. 1952; 2012 I S. 197), das zuletzt durch Artikel 3 des Gesetzes vom 21. Dezember 2022 (BGBl. I S. 2847) geändert worden ist" [Online: https://www.gesetze-im-internet.de/baf_g/BJNR014090971.html#BJNR014090971BJNG000201310], Date of Access:03.03.2024.
  • Benjamin, K., Wen, X., Nketia, E. B., & Kweitsu, G. (2019). A Comparative Analysis on Efficiency of the Student Loan Repayment Policy in Ghana, Kenya, Tanzania, Rwanda and Nigeria. https://doi.org/10.18535/ijsrm/v7i2.em03
  • Britton, J., van der Erve, L., & Higgins, T. (2019). Income contingent student loan design: Lessons from around the world. Economics of Education Review, 71, 65-82. https://doi.org/10.1016/j.econedurev.2018.06.001
  • Chapman, B. (2014). "Income Contingent Loans: Background". B. Chapman, T. Higgins, & J. E. Stiglitz(Ed.), Income Contingent Loans:Background, Income Contingent Loans; Theory,Practice and Prospects (s. 26-39). London: Palvarage, ISBN: 9781137413208. https://doi.org/10.1057/9781137413208
  • Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114(1), 1-9. https://doi.org/10.1016/S0165-0114(97)00377-1
  • Cheng, S., Chan, C. W., & Huang, G. H. (2003). An integrated multi-criteria decision analysis and inexact mixed integer linear programming approach for solid waste management. Engineering Applications of Artificial Intelligence, 16(5-6), 543-554. https://doi.org/10.1016/S0952-1976(03)00069-1
  • Despard, M. ., Perantie, D., Taylor, S., Grinstein-Weiss, M., Friedline, T., & Raghavan, R. (2016). Student debt and hardship: Evidence from a large sample of low- and moderate-income households. Children and Youth Services Review, 70, 8–18. https://doi.org/10.1016/j.childyouth.2016.09.001
  • Dezhina, I. G., & Nafikova, T. N. (2019). Tuition fees as a source of funding and a policy instrument: international experience. Университетское управление: практика и анализ, 23(5), 22-30. https://doi.org/10.15826/umpa.2019.05.038
  • Ergen, Z. (2006). Yükseköğretim Finansmanında Öğrenci Borçlanma Yöntemi. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi,15(1),133-150
  • Gölpek, F. (2011). Yükseköğretim Finansman Politikasında Yeni Bir Yaklaşım:Maliyet Paylaşımı . Yükseköğretim Dergisi, I (1), 25-33.
  • Gölpek, F. (2013). Yükseköğretimin Finansmanında Güncel Yaklaşımlar:Borçlanma ile Finansman. Derin Yayınları, İstanbul.
  • Grave, B. S., & Sinning, M. (2014). Why don’t we just give them the money? Financing living expenses of students in Germany. In Income Contingent Loans: Theory, Practice and Prospects (pp. 109-124). London: Palgrave Macmillan UK. https://doi.org/10.1057/9781137413208_10
  • JASSO (Japan Student Services Organization) (2022). JASSO Outline 2022’2023. [Online: https://www.jasso.go.jp/en/gakusei/index.html ], Date of access: 10.03.2023.
  • Jee, D. H., & Kang, K. J. (2000). A method for optimal material selection aided with decision making theory. Materials & Design, 21(3), 199-206. https://doi.org/10.1016/S0261-3069(99)00066-7
  • Jiménez, D., & Glater, J. D. (2020). Student debt is a civil rights issue: The case for debt relief and higher education reform. Harv. CR-CLL Rev., 55, 131. https://doi.org/10.2139/ssrn.3475224
  • Johnstone, B. (2009). Financing higher education: Who pays and other issues. The American university in the 21st century: Social, political, and economic challenges, 347-369.
  • Johnstone, D. B., & Marcucci, P. (2007). Student loans in international context: A primer.
  • Jongbloed, B. (2004). Tuition fees in Europe and Australasia: theory, trends and policies. In Higher education: Handbook of theory and research (pp. 241-310). Springer, Dordrecht. https://doi.org/10.1007/1-4020-2456-8_7
  • Karaatlı, M. (2016). ENTROPİ-GRİ ilişkisel analiz yöntemleri ile bütünleşik bir yaklaşım: Turizm sektöründe uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(1), 63-77.
  • KYK (Kredi ve Yurtlar Genel Müdürlüğü), (2024a). “Tarihçe” [Online: https://kygm.gsb.gov.tr/Sayfalar/2397/3193/Tarihce]. Date of access: 20.04.2024.
  • KYK (Kredi ve Yurtlar Genel Müdürlüğü), (2024b). “Burs ve Kredi” [Online: https://kygm.gsb.gov.tr/HaberDetaylari/1/267069/burs-kredi-odemeleri-basladi.aspx]. Date of access: 20.05.2024.
  • Martin, C. (2016). Should Students Have to Borrow?Autonomy,Wellbeing and Student Debt. Journal of Philosophy of Education, 50 (3), 351-370. https://doi.org/10.1111/1467-9752.12133
  • Mbah, R. E. (2021). Expanding the theoretical framework in student debt research by connecting public policy theories to the student debt literature. Advances in Social Sciences Research Journal, 8(11), 211-219. https://doi.org/10.14738/assrj.811.11196
  • Mbah, R. E., Forcha, D. F., & Mende, C. M. (2020). Assessing the relationship between Pell Grant and Federal Student Loan at Louisiana four-year public institutions [Abstract]. Journal of Education and Practice, 11(9), 40- 44. https://doi.org/10.7176/JEP/11-9-04
  • Monjezi, M., Dehghani, H., Singh, T. N., Sayadi, A. R., & Gholinejad, A. (2012). Application of TOPSIS method for selecting the most appropriate blast design. Arabian journal of geosciences, 5(1), 95. https://doi.org/10.1007/s12517-010-0133-2
  • Murto, M. J. (2024). Student Loans and College Majors: The Role of Repayment Plan Structure. Consumer Financial Protection Bureau Office of Research Working Paper, (24-01). https://doi.org/10.2139/ssrn.4744213
  • OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.
  • OECD (2024). “Data” [Online: https://data.oecd.org/]. Date of access: 10.01.2024.
  • Özekicioğlu, S. (2013). Yükseköğretimin Finansmanında Güncel Yaklaşımlar: Borçlanma İle Finansman. İstanbul: Derin Yayınları.
  • Shen, H., & Ziderman, A. (2009). Student loans repayment and recovery: international comparisons. Higher education, 57, 315-333. https://doi.org/10.1007/s10734-008-9146-0
  • SLC.(2024a). Student Loans Company [Online: https://www.gov.uk/government/organisations/student-loans-company/about#about-us], Date of access: 10.03.2024.
  • SLC.(2024b). Student Loans Company, [Online: https://www.gov.uk/student-finance/new-fulltime-students], Date of access: 10.03.2024.
  • SLC.(2024c). Student Loans Company, [Online: https://www.gov.uk/repaying-your-student-loan/what-you-pay], Date of access: 10.03.2024.
  • The World Bank (2024). “Data” [Online: https://www.worldbank.org/en/search?q=data]. Date of access: 05.01.2024.
  • Tulip, P. (2007). Financing higher education in the United States.
  • URL-1. “Studentaid”, [Online: https://studentaid.gov/understand-aid/types/loans/subsidized-unsubsidized], Date of acces: 20.05.2024.
  • URL-2. “Studentwerke/Göttingen”, [Online https://www.studentenwerk-goettingen.de/studienfinanzierung/bafoeg-fuer-studierende], Date of acces: 10.03.2023.
  • Vossensteyn, H. (2000). Sharing The Cost Of Higher Education İn Europe And Australia-Who Pays?. Journal Of İnstitutional Research, 9(2), 54-66.
  • Wang, Y. M., & Elhag, T. M. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert systems with applications, 31(2), 309-319. https://doi.org/10.1016/j.eswa.2005.09.040
  • Woodhall, M. (2007). Funding higher education: The contribution of economic thinking to debate and policy development.
  • Woodhall, M., & Richards, K. (2008). "Student and Unıversıty Fundıng ın Devolved Governments ın The UK". P. N. Teixeira, B. D. Johnstone, M. J. Rosa, & H. Vossensteyn (Eds.), Higher Education Dynamics; Cost-Sharing andAccessibility in Higher Education: A Fairer Deal?[E-Book] (Cilt 14, s. 189-212). The Netherlands: Springer. ISBN: 978-1-4020-4660-5.
  • Xia, Z., Yue, X., Niu, F., & Hu, Z. (2022). Prediction of higher education cost and analysis of sharing ability based on artificial neural network. Security and Communication Networks, 2022. https://doi.org/10.1155/2022/7649918
  • YÖK. (2007). Türkiyenin Yükseköğretim Stratejisi. Ankara: Meteksan A.Ş.
  • Zhang, H., Gu, C. L., Gu, L. W., & Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy–A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451. https://doi.org/10.1016/j.tourman.2010.02.007
  • Chapman, B., & Ryan, C. (May 2002). Income-Contingent Financing of Student Charges for Higher Education: Assessing the Australian Innovation. Centre for Economic Policy Research, Australian National University, Discussion Papers No:449.
  • 2547 Sayılı YÖK Kanunu. (1981). T.C. Resmi Gazete. 17506 . 06 Kasım 1981
Year 2024, Volume: 7 Issue: 1, 73 - 103, 29.05.2024
https://doi.org/10.53048/johass.1482714

Abstract

Türk yükseköğretim sistemi günümüzde dünya genelinde yaşanan gelişme ve değişimlere paralel olarak olağanüstü bir biçimde gelişme sağlamıştır. Öğrencilerin yükseköğretime erişiminin kolaylaşması ile öğrenci sayılarındaki artışla birlikte yükseköğretim maliyetlerin artışına sebep olmaktadır. Bu durum yükseköğretim finansmanı kamusal kaynaklardan sağlayan ülkelerde, yükseköğretim sistemini maddi olarak baskı altına sokmaktadır. Bu çalışmada dünya genelinde kullanılan yükseköğretim finansman yöntemleri karşılaştırılmış olup, Türkiye için en uygun finansman yönteminin belirlenmesi ele alınmıştır. Bu amaç doğrultusunda finansman politikalarının değerlendirilmesine yönelik olarak belirlenen kriterlerin ağırlıklandırılmasında Entropi yönteminden faydalanılmış olup, alternatiflerin performans analizi çok kriterli karar verme yöntemlerinden biri olan, TOPSİS yöntemi ile yapılmıştır. Alternatif karar seçenekleri olarak yükseköğretim finansmanında kullanılan; “Ücret alınmayan”, “Ön ücretlendirme” ve “Gelire Bağlı Borçlanma” yöntemleri esas alınmış olup, ana kriterler kayıt, eğitim harcamaları ve işgücü olarak belirlenmiştir. Bu bağlamda alt kriterler oluşturulup, OECD’ye ülkelerin kullanmış oldukları finansman yöntemleri analiz edilmiştir. Çalışma kapsamında Norveç, Hollanda ve Birleşik Krallığın yükseköğretim sistemleri içindeki kullanmış oldukları finansman yöntemlerinin ilk üç sırada olduğu tespit edilmiştir. Bu bağlamda birinci ve üçüncü sırada yer alan ülkelerin kullanmış oldukları “Gelire Bağlı Borçlanma” yönteminin performans bakımından en çok tercih edilen yöntem olduğu tespit edilmiştir.

References

  • Agrawal, V. P., Kohli, V., & Gupta, S. (1991). Computer aided robot selection: the ‘multiple attribute decision making’approach. The International Journal of Production Research, 29(8), 1629-1644. https://doi.org/10.1080/00207549108948036
  • Akça, H. (2012). "Yükseköğretimin Finansmanı ve Türkiye İçin Yükseköğretim Finansman Modeli Önerisi". Yönetim ve Ekonomi Dergisi, 19 (1), 91-104
  • ATO, Australian Taxation Office (2024). (Study and training loan indexation rates | Australian Taxation Office (ato.gov.au) online,22.03.2024)
  • Australian Goverment (2024). 2024 Commonwealth Supported Places and HECS-HELP İnformation,. (https://www.studyassist.gov.au/system/files/documents/2023-12/Final%202024%20CSP%20and%20HECS-HELP%20booklet.pdf , online,22.03.2024)
  • Aydın, M. S. (2014). Türkiye'de Yükseköğretimin Finansmanı. Marmara Üniversitesi Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, İstanbul.
  • BAföG.(2024). Bundesgesetz über individuelle Förderung der Ausbildung (Bundesausbildungsförderungsgesetz - BAföG) , "Bundesausbildungsförderungsgesetz in der Fassung der Bekanntmachung vom 7. Dezember 2010 (BGBl. I S. 1952; 2012 I S. 197), das zuletzt durch Artikel 3 des Gesetzes vom 21. Dezember 2022 (BGBl. I S. 2847) geändert worden ist" [Online: https://www.gesetze-im-internet.de/baf_g/BJNR014090971.html#BJNR014090971BJNG000201310], Date of Access:03.03.2024.
  • Benjamin, K., Wen, X., Nketia, E. B., & Kweitsu, G. (2019). A Comparative Analysis on Efficiency of the Student Loan Repayment Policy in Ghana, Kenya, Tanzania, Rwanda and Nigeria. https://doi.org/10.18535/ijsrm/v7i2.em03
  • Britton, J., van der Erve, L., & Higgins, T. (2019). Income contingent student loan design: Lessons from around the world. Economics of Education Review, 71, 65-82. https://doi.org/10.1016/j.econedurev.2018.06.001
  • Chapman, B. (2014). "Income Contingent Loans: Background". B. Chapman, T. Higgins, & J. E. Stiglitz(Ed.), Income Contingent Loans:Background, Income Contingent Loans; Theory,Practice and Prospects (s. 26-39). London: Palvarage, ISBN: 9781137413208. https://doi.org/10.1057/9781137413208
  • Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114(1), 1-9. https://doi.org/10.1016/S0165-0114(97)00377-1
  • Cheng, S., Chan, C. W., & Huang, G. H. (2003). An integrated multi-criteria decision analysis and inexact mixed integer linear programming approach for solid waste management. Engineering Applications of Artificial Intelligence, 16(5-6), 543-554. https://doi.org/10.1016/S0952-1976(03)00069-1
  • Despard, M. ., Perantie, D., Taylor, S., Grinstein-Weiss, M., Friedline, T., & Raghavan, R. (2016). Student debt and hardship: Evidence from a large sample of low- and moderate-income households. Children and Youth Services Review, 70, 8–18. https://doi.org/10.1016/j.childyouth.2016.09.001
  • Dezhina, I. G., & Nafikova, T. N. (2019). Tuition fees as a source of funding and a policy instrument: international experience. Университетское управление: практика и анализ, 23(5), 22-30. https://doi.org/10.15826/umpa.2019.05.038
  • Ergen, Z. (2006). Yükseköğretim Finansmanında Öğrenci Borçlanma Yöntemi. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi,15(1),133-150
  • Gölpek, F. (2011). Yükseköğretim Finansman Politikasında Yeni Bir Yaklaşım:Maliyet Paylaşımı . Yükseköğretim Dergisi, I (1), 25-33.
  • Gölpek, F. (2013). Yükseköğretimin Finansmanında Güncel Yaklaşımlar:Borçlanma ile Finansman. Derin Yayınları, İstanbul.
  • Grave, B. S., & Sinning, M. (2014). Why don’t we just give them the money? Financing living expenses of students in Germany. In Income Contingent Loans: Theory, Practice and Prospects (pp. 109-124). London: Palgrave Macmillan UK. https://doi.org/10.1057/9781137413208_10
  • JASSO (Japan Student Services Organization) (2022). JASSO Outline 2022’2023. [Online: https://www.jasso.go.jp/en/gakusei/index.html ], Date of access: 10.03.2023.
  • Jee, D. H., & Kang, K. J. (2000). A method for optimal material selection aided with decision making theory. Materials & Design, 21(3), 199-206. https://doi.org/10.1016/S0261-3069(99)00066-7
  • Jiménez, D., & Glater, J. D. (2020). Student debt is a civil rights issue: The case for debt relief and higher education reform. Harv. CR-CLL Rev., 55, 131. https://doi.org/10.2139/ssrn.3475224
  • Johnstone, B. (2009). Financing higher education: Who pays and other issues. The American university in the 21st century: Social, political, and economic challenges, 347-369.
  • Johnstone, D. B., & Marcucci, P. (2007). Student loans in international context: A primer.
  • Jongbloed, B. (2004). Tuition fees in Europe and Australasia: theory, trends and policies. In Higher education: Handbook of theory and research (pp. 241-310). Springer, Dordrecht. https://doi.org/10.1007/1-4020-2456-8_7
  • Karaatlı, M. (2016). ENTROPİ-GRİ ilişkisel analiz yöntemleri ile bütünleşik bir yaklaşım: Turizm sektöründe uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(1), 63-77.
  • KYK (Kredi ve Yurtlar Genel Müdürlüğü), (2024a). “Tarihçe” [Online: https://kygm.gsb.gov.tr/Sayfalar/2397/3193/Tarihce]. Date of access: 20.04.2024.
  • KYK (Kredi ve Yurtlar Genel Müdürlüğü), (2024b). “Burs ve Kredi” [Online: https://kygm.gsb.gov.tr/HaberDetaylari/1/267069/burs-kredi-odemeleri-basladi.aspx]. Date of access: 20.05.2024.
  • Martin, C. (2016). Should Students Have to Borrow?Autonomy,Wellbeing and Student Debt. Journal of Philosophy of Education, 50 (3), 351-370. https://doi.org/10.1111/1467-9752.12133
  • Mbah, R. E. (2021). Expanding the theoretical framework in student debt research by connecting public policy theories to the student debt literature. Advances in Social Sciences Research Journal, 8(11), 211-219. https://doi.org/10.14738/assrj.811.11196
  • Mbah, R. E., Forcha, D. F., & Mende, C. M. (2020). Assessing the relationship between Pell Grant and Federal Student Loan at Louisiana four-year public institutions [Abstract]. Journal of Education and Practice, 11(9), 40- 44. https://doi.org/10.7176/JEP/11-9-04
  • Monjezi, M., Dehghani, H., Singh, T. N., Sayadi, A. R., & Gholinejad, A. (2012). Application of TOPSIS method for selecting the most appropriate blast design. Arabian journal of geosciences, 5(1), 95. https://doi.org/10.1007/s12517-010-0133-2
  • Murto, M. J. (2024). Student Loans and College Majors: The Role of Repayment Plan Structure. Consumer Financial Protection Bureau Office of Research Working Paper, (24-01). https://doi.org/10.2139/ssrn.4744213
  • OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.
  • OECD (2024). “Data” [Online: https://data.oecd.org/]. Date of access: 10.01.2024.
  • Özekicioğlu, S. (2013). Yükseköğretimin Finansmanında Güncel Yaklaşımlar: Borçlanma İle Finansman. İstanbul: Derin Yayınları.
  • Shen, H., & Ziderman, A. (2009). Student loans repayment and recovery: international comparisons. Higher education, 57, 315-333. https://doi.org/10.1007/s10734-008-9146-0
  • SLC.(2024a). Student Loans Company [Online: https://www.gov.uk/government/organisations/student-loans-company/about#about-us], Date of access: 10.03.2024.
  • SLC.(2024b). Student Loans Company, [Online: https://www.gov.uk/student-finance/new-fulltime-students], Date of access: 10.03.2024.
  • SLC.(2024c). Student Loans Company, [Online: https://www.gov.uk/repaying-your-student-loan/what-you-pay], Date of access: 10.03.2024.
  • The World Bank (2024). “Data” [Online: https://www.worldbank.org/en/search?q=data]. Date of access: 05.01.2024.
  • Tulip, P. (2007). Financing higher education in the United States.
  • URL-1. “Studentaid”, [Online: https://studentaid.gov/understand-aid/types/loans/subsidized-unsubsidized], Date of acces: 20.05.2024.
  • URL-2. “Studentwerke/Göttingen”, [Online https://www.studentenwerk-goettingen.de/studienfinanzierung/bafoeg-fuer-studierende], Date of acces: 10.03.2023.
  • Vossensteyn, H. (2000). Sharing The Cost Of Higher Education İn Europe And Australia-Who Pays?. Journal Of İnstitutional Research, 9(2), 54-66.
  • Wang, Y. M., & Elhag, T. M. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert systems with applications, 31(2), 309-319. https://doi.org/10.1016/j.eswa.2005.09.040
  • Woodhall, M. (2007). Funding higher education: The contribution of economic thinking to debate and policy development.
  • Woodhall, M., & Richards, K. (2008). "Student and Unıversıty Fundıng ın Devolved Governments ın The UK". P. N. Teixeira, B. D. Johnstone, M. J. Rosa, & H. Vossensteyn (Eds.), Higher Education Dynamics; Cost-Sharing andAccessibility in Higher Education: A Fairer Deal?[E-Book] (Cilt 14, s. 189-212). The Netherlands: Springer. ISBN: 978-1-4020-4660-5.
  • Xia, Z., Yue, X., Niu, F., & Hu, Z. (2022). Prediction of higher education cost and analysis of sharing ability based on artificial neural network. Security and Communication Networks, 2022. https://doi.org/10.1155/2022/7649918
  • YÖK. (2007). Türkiyenin Yükseköğretim Stratejisi. Ankara: Meteksan A.Ş.
  • Zhang, H., Gu, C. L., Gu, L. W., & Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy–A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451. https://doi.org/10.1016/j.tourman.2010.02.007
  • Chapman, B., & Ryan, C. (May 2002). Income-Contingent Financing of Student Charges for Higher Education: Assessing the Australian Innovation. Centre for Economic Policy Research, Australian National University, Discussion Papers No:449.
  • 2547 Sayılı YÖK Kanunu. (1981). T.C. Resmi Gazete. 17506 . 06 Kasım 1981
There are 51 citations in total.

Details

Primary Language English
Subjects Other Fields of Education (Other)
Journal Section Research Article
Authors

Reşit Çetinkaya 0000-0001-9997-7986

Ertuğrul Çavdar 0000-0002-1522-8775

Publication Date May 29, 2024
Submission Date May 12, 2024
Acceptance Date May 28, 2024
Published in Issue Year 2024 Volume: 7 Issue: 1

Cite

APA Çetinkaya, R., & Çavdar, E. (2024). Comparative Analysis of Higher Education Financing Policies Used by OECD Member Countries and Financing Policy Proposal for Türkiye. Journal of Human and Social Sciences, 7(1), 73-103. https://doi.org/10.53048/johass.1482714

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