In this study, we empolyed publicly available data from the Higher Education in Korea database to examine the impact of various factors on student dropout rates. This data represents an accurate and transparent available source of key university and college indicators, offering convenience and accessibility, and high reliability and validity.

The data demonstrated that smaller universities with an enrollment of less than 2,500 students exhibited a higher dropout rate than their larger counterparts. Furthermore, prior research has also demonstrated that larger universities tend to exhibit lower dropout rates [9,10]. And financial aid status and universities situated in metropolitan areas (Seoul, Gyeonggi-do, Incheon) exhibited reduced dropout rates as well. However, no statistically significant differences were identified between colleges and universities, location, and whether they received financial aid. This discrepancy is likely attributable to the proportion of dental hygiene students, rather than the overall university dropout rate, and other factors such as competition among first-year students, the availability of dormitories, academic performance, and satisfaction with the major, rather than location or financial aid [7,10,11].

The findings of this study indicate a positive correlation between dropout rates and graduate employment rates, research fund benefits, tuition fees, the total number of dental hygiene students. In a study conducted by Hwang & Jeon [9], a reduction in dropout rates was observed in correlation with an increase in the ratio of lectures conducted by faculty, student loan ratios, expenditure per student, and educational expenses per student. In the study by Hwang et al [10], a negative correlation was observed between dropout rates and higher employment rates, higher grades and lower tuition fees. In contrast, this study found that higher tuition fees and student loan rates were associated with lower dropout rates. These discrepancies may be attributed to several factors, including higher expectations of future earnings, parental support, loan deferment and long-term repayment schemes, and the social stigma associated dropping out.

A hierarchical regression analysis was conducted to investigate the factors influencing dropout rates. The analysis yielded the the result that only the graduate employment rate exhibited a significant predictive effect. In a previous study [9], the number of students, the financial aid, the ratio of lectures conducted by faculty, the number of students per faculty member, the research fund benefits, and the rate of student loans were identified as factors affecting the dropout rate. In the study conducted by Hwang et al. [10], the employment rate of graduates, the rate of scholarship benefits, and in the study conducted by Chung et al [7], the location of the university, the status of financial aid, the number of students per faculty member, and research fund benefits were identified as factors affecting dropout rates. These discrepancies are likely attributable to the fact that dental hygiene students’ expectations of employment are a significant factor in their school choice and retention [12–14]. In contrast to the findings of previous studies, our analysis did not identify any variables as significantly influential when moving from Model 2 to Model 4. This raises the question of whether this is due to the presence of correlations between variables, the specific institutions included in study, or differences in the influence of certain variables. While not a significant change, the progression to next model did contribute to a slight increase in explanatory power.

Despite tuition fees representing over 70% of the operating income of universities, the government’s policy of freezing tuition fees has prevented universities from raising tuition fees for the past 15 years. In recent times, a small number of universities, including those situated in metropolitan areas, have initiated an increase in tuition fees. Nevertheless, the financial pressures remain considerable, particularly for private universities, which rely heavily on tuition fees. In light of these circumstances, state support, such as the support program for university or college development, has become a crucial aspect of university operations. The decline in the school-age population is already occurring at an accelerated rate, which will present an even more significant challenge for universities. Consequently, there will be a greater focus on state-funded initiatives to address the shortfall in funding [15,16]. The nature of government-led financial support projects presents a challenge for universities seeking to diversify their financial sources in a short period of time. It is therefore essential to reinforce and sustain collaborative relationships with pivotal employers in the local community. This may entail initiatives such as on-the-job training and work placements, with the objective of enhancing employability and student retention, while concurrently reducing dropout rates.

This study utilized publicly accessible data on the academic environments of colleges and universities in South Korea, where dental hygiene departments are offered as a basis for analysis. The relationship between key indicators of school environment and dropout rates was subjected to analysis, and factors affecting dropout rates were identified. However, the analysis was unable to determine whether there were any changes in dropout rates change over time. Hierarchical regression analyses were conducted in order to control for moderating variables that alter the strength or direction of the relationship between variables. Nevertheless, no significant interactions were identified in the subsequent analyses conducted at the second stage. It is recommended that future studies analyze not only analyze the relationship between other publicly available indicators of the school environment and dropout rates but also examine longitudinal data in order to capture changes in dropout rates over time. It is recommended that future research consider the application of time-series or survival analyses, with a view to gaining a deeper understanding of the manner in which factors influencing dropout rates evolve and vary over time. Morever, an exploration of the range of potential moderators, including faculty-to-student ratios, academic support resources and student satisfaction, could facilitate the acquisition of insights into the specific factors influencing dropout rates.