Higher education (HE) has received considerable attention due to its social, economic, and cultural returns for societies and individuals (Jerrim & Vignoles, 2015; Lochner, 2020). Particularly the benefits for individuals are closely coupled with increased social cohesion and economic return for countries in the long run (Altbach, 2000; O’Sullivan et al., 2017). As a result, the number of individuals demanding HE has increased exponentially, which has pushed governments to address this demand and provide opportunities for all. Türkiye is one of those countries which adopted an aggressive policy to expand its HE capacity since 2005 (Özoğlu et al., 2016) with the motto of “one university in each province.” More concretely, right after the policy was initiated, in two years, 41 public universities were established (Özoğlu et al., 2016). This policy aimed to fill the gap between supply and demand while making HE accessible to all, regardless of their geographical location and socio-economic status. However, the policy was not limited to the acceleration of establishing new universities. It also covered increasing the quota of already established ones and making public universities totally free of tuition fees.

Two opposing arguments emerged concerning the outcomes of the expansion of HE. While the proponents have a more neoliberal lens that highlights the key roles of a qualified labor force for the market and their economic return, the opponents questioned and raised their concerns about the growth in the number of graduates and resulting diploma inflation and uncontrollable unemployment (Teichler, 2020). Türkiye’s expansion policy seems to embrace a more optimistic perspective as the government and the existing scholarship refer to these universities as tools for regional and economic development (Polat, 2017), while HE is considered a means for better and more prosperous living conditions by higher income and wellbeing (Ma et al., 2016). 

The aim of promoting available and accessible HE to whoever aspires has been confirmed by the statistics offered by the Council of Higher Education (HEC, 2023). These statistics demonstrate that between 2006 and 2014, the gap between the number of students who applied for the university entrance examination (a competitive nationwide examination taken by around three million students) and the ones who enrolled was getting lower. However, this gap has started to expand since then and reached a peak in 2022 in the lifetime of the HE, which has caused a serious supply and demand imbalance in student applications and enrollments. Considering the relatively young population of the country, this situation may create an illusion that Türkiye needs further higher education institutions (HEIs) to address this increasing imbalance. Yet, the filled quota rates of the most recently founded HEIs are extremely low, which is even the case for the lucrative fields, including engineering (Kaya-Kaşıkcı, 2023). Thus, it can be concluded that there is no reception by the target groups despite the oversupply of available quotas. This contradiction in what the expansion policy promised and what was accomplished suggests a need for a closer look at the underlying factors that make HEIs more attractive and demanded.

Against this background, this study aims to investigate the predictive roles of key institutional-level variables for access to HE in Türkiye. Such an investigation aims to give insight into the extent to which the government’s expansion policy has accomplished its primary goal of increasing access to HE over time. With this purpose in mind, the study utilizes the year of foundation, geographical location, and the student-instructor ratio of the public universities as variables to document how well they predict the HE access measured in the form of the rate of used quota spanning from 2019 to 2021.

This research was designed as a correlation study and a group of constant and time-varying predictors were used to predict the time-varying outcome of the rate of filled quota. There are a couple of reasons for choosing the predictors: (1) year of foundation was selected to study the potential year effect stemming from the variation in the degree of institutionalization and cumulative capacity and experience across the institutions (Doğan, 2013), (2) geographical location was picked as an indicator of the degree of regional development, (3) student-instructor ratio was chosen as an indicator of quality (Zayim-Kurtay & Kaya-Kasikci, 2022) as it is the reference for how the teaching resources and time are allocated (OECD, 2021). The data utilized in this study were retrieved from the YOK ATLAS of Türkiye, a database of HE quota and enrollment statistics for undergraduate degrees (HEC, 2023​​). The data spanning three years, from 2019 to 2021, was utilized as the system offers complete statistics only for the last three years. Thus, longitudinal data for the public university population was used in this study (n = 129). The ages of the universities range from 5 to 90 years, with a mean of 28,26 (SD = 18.49). The number of institutions in the population established before 2006 was 58. When it comes to the geographical distribution, the number of HEIs located in the Central Anatolia region is 27, the Marmara region is 27, the Mediterranean region is 14, the Eastern-Anatolia region is 16, the Aegean region is 15, the Black Sea region is 20, and South-Eastern region is 10.

The analysis will be conducted with fixed effect regression for longitudinal data using SPSS 28. The results are expected to show that although there are many universities established after 2005 and available for students, the demand for these universities has always been at a minimum level. Thus, we expect a change between the filled quota rate of the HEIs established before and after 2005 in a way that the ones founded earlier than 2006 may have higher rates. Moreover, the rate of filled quota is expected to show no change over the years (no within difference over the three-year period), but the region, year of foundation, and student-instructor ratio are expected to contribute to the prediction of filled quota rate significantly.

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