The Impact of EU-Funded Educational Programs on the Socio-Economic Development of Romanian Students: A Multidimensional Analysis

Abstract

One of the central goals of the 2030 Agenda for Sustainable Development is represented by inclusive and equitable education. This study investigates the impact of the educational programs funded by the European Union on the socio-economic situation of Romanian students by focusing on eight key dimensions: poverty, social inequalities, juvenile crime, nutrition, discrimination, employability, quality of life, and health. The study is based on a quantitative descriptive research design. The data were collected from a representative sample of 1220 pre-university teachers. To identify the differences between students who benefited from the EU-funded educational project implementation and students who did not have this opportunity, t-Student and ANOVA tests were used. cluster analysis (k-means) was applied to classify cases based on the evolution of socio-economic indicators, and binary logistic regression was used to identify the factors influencing the probability that students belong to groups with better performance in relation to the analyzed dimensions. Our findings revealed that while EU-funded education projects have significantly contributed to the socio-economic development of students, a series of disparities still persist among students coming from low-income families. The findings underline the need for more targeted policies. The advanced statistical analyses revealed the importance of early educational interventions through EU-funded educational programs. Also, they revealed the need for integrated, targeted strategies to increase the chances of supporting social equity and reducing inequalities.

1. Introduction

Education plays a vital role in different aspects of life. It provides opportunities to improve the quality of life and to achieve a better standard-living. All individuals deserve a decent and high-quality education to become a smart, competent, and competitive workforce [1]. Education is a long-term investment, with significant effects on the economic and social development of society. However, the high cost of quality education limits access for people with limited financial resources; this might determine the increase in social divisions based on economic status [2].

1.1. Education and the Agenda 2030’s Sustainable Development Goals

Human rights in education represent a key issue that should be a top priority for meaningful improvement all over the world. The Declaration of the United Nation’s Economic and Social Council set nine fundamental human rights in the field of education, namely: guaranteeing and promoting equality in education; supporting and accelerating learning; allocating adequate financial resources to education; respecting cultural diversity in education; ensuring a safe environment that supports physical and mental health; developing modern and efficient infrastructure; creating safe and adequate conditions for teaching and learning; promoting gender equality; digital literacy; and encouraging international cooperation in education through the active involvement of the countries [3].

Romania adopted the 2030 Agenda for Sustainable Development, together with the 192 United Nations member states, at the September 2015 Summit. The Agenda includes 17 Global Goals that aim to eradicate extreme poverty, to reduce inequalities, and to protect the environment by 2030. The 2030 Agenda and the Sustainable Development Goals (SDGs) represent the global agenda for action in the field of sustainable development. They promote the balance between three dimensions—economic, social, and environmental.

Education brings benefits both to individuals and to society by playing a key role in achieving the 2030 Agenda for Sustainable Development. All the Sustainable Development Goals (SDGs) include educational components, as they represent the foundation of development. Many countries consider education a top priority; the United Nations included quality education as a Sustainable Development Goal (SDG) in the 2030 Agenda [4]. The 2030 Agenda highlights the particular importance of Goal 4 (SDG4) which refers to education [5]; it mentions the significant role that education plays in the transition to the new model of sustainable development [6].

By shaping global development policies and actions, it aims to provide strategic directions for addressing problems in the field of education, with the purpose of ensuring inclusive and equitable education for all [7] and developing long-life learning opportunities [8].

A crucial role in achieving the SDGs is educational institutions all over the world [9]. They integrate sustainable development values at all educational levels, from early childhood education to higher education [10]. The educational institutional support provides the necessary skills, knowledge, and perspectives needed to address sustainability challenges and opportunities [11,12]. This enhances the holistic development of students, and, also, contributes to the wider objectives of national development [13].

Achieving global sustainability is certainly linked to achieving the SDGs. However, the education of future generations for sustainability and the achievement of the SDGs through innovative educational models is limited and it is achieved through fragmented initiatives [14]. Even so, it creates significant challenges in educational management felt at all levels [15]: in the reconfiguration of curriculum, practices, and policies; in the management process; and in the content and the methodology of teaching [6]. In recent years, teachers expressed great concern about environmental, social, and economic issues [14]. A central element responsible for improving the quality of education in line with the Sustainable Development Goal (SDG4) is the school’s management [16].

At the macro-economic level, national strategies aim to ensure education for all, but significant inequalities persist, especially for children from disadvantaged groups. Studies looking at significant impediments to aligning education with the SDGs [17] highlight continuous challenges regarding inequalities in key education indicators: gaps in educational outcomes in the rural environment; socio-economic deprivation and reduced educational mobility in rural primary schools [18]; and low performance of children from disadvantaged groups or those with limited resources. Also, the existing data show insignificant progress in reducing economic barriers and in improving learning [19].

Although many educational institutions want to integrate sustainability into their curricula to achieve sustainability goals and to develop “education for the future” models, there are many impediments slowing down the process [20]. Addressing these challenges of the SDGs requires inclusive and sustainable economic growth [21].

The lack of well-defined strategies to support equal access to education for all children remains a major problem. Current educational programs fail to adequately respond to the needs of the most vulnerable children, including those with disabilities [19].

1.2. The Role of EU-Funded Education Programs in Achieving the Sustainable Development Goals (SDGs)

Studies focused on educational programs emphasize the importance of partnerships and informal learning for reflecting global sustainability issues in regional platforms [22] by highlighting that SDGs offer unparalleled opportunities in addressing disparities and promoting equal opportunities by helping countries advance the cause of sustainable development in their territories with direct benefits for their populations [23].

The results of different studies indicate that developed countries obtain the greatest benefits by focusing on social and environmental aspects, while developing countries need to focus strategic policies on economic and social factors [24].

Governments and international organizations are still struggling to find effective and scalable interventions to reduce educational inequalities [25] through the development of effective policies and the development of programs whose impact can be found on the social, health, educational, and economic components [26].

The costs of education are essential parts of the educational operations. The educational process may not be effective without financial assistance; numerous studies have shown that school funding affects the quality of education [2]. Thus, together with other components, financing plays an important role in achieving educational objectives [1].

To meet the regional targets of sustainable economic growth, of social integration at European standards, and of high labor competitiveness, the European Union supports the actions of its members by offering various complementary financing instruments in the form of Structural Funds [27]. Considering the limited success of pre-existing policies impacting inequality and segregation, a significant number of pilot projects have been implemented with the support of external funding. They focused on factors with an impact on inequality, differential performance, a high level of self-segregation, and a persistent achievement gap for low-income students [28]. The existing studies provide evidence that the intervention programs and flexible educational models tailored to the needs of the community are a viable and successful alternative for reducing educational inequities in rural areas of developing countries [29]. There are, also, evidence that early interventions in a child’s life may be more productive than later interventions [30].

To improve educational policies through balanced funding that ensures equitable access to high-quality education and meets the evolving needs of students in a diverse socio-economic landscape, the European Union recommends identifying the best practices that succeed in harmonizing educational opportunities with the future economic and social requirements [31]. This involves assessing the impact of interventions on reducing socio-economic segregation and the gap between disadvantaged students to know whether funding should stop or would need a new focus [32]. Efficient, transparent, and accountable financial management plays an important role in improving the quality of education in schools. For a successful fund’s management, it is recommended to increase cooperation between the stakeholders involved in educational fund management, as well as to improve the budgeting process, to suit the real needs of students [33].

1.3. Measuring the Socio-Economic Situation of Students in the European Union Through Key Indicators

Socio-economic status represents a complex and multidimensional concept, frequently used in research to understand disparities in education. It has hierarchical and multiple effects on educational performance and well-being. Also, it is influenced by complex combinations of factors [34].

A series of studies reveal a negative association between family and contextual factors [35], such as family poverty, nutrition [36], social inequalities [37], juvenile delinquency [38,39], discrimination [40], employability, student’s life quality, health status [41], and educational performance. The increase in socio-economic inequalities can contribute to the observed inequalities in cognitive abilities, school results [42], and professional results [43].

The eight identified factors above are considered key dimensions on socio-economic fronts as prohibitive for the perseverance and persistence of vulnerable children.

To understand how these factors interact in shaping outcomes and in improving the performance of disadvantaged students, an integrated approach is needed. Understanding these factors is crucial to draw educational policies and to develop interventions that reduce educational disparities and support the academic and professional success of all students.

1.4. The Student’s Family Poverty

Over time, poverty and inequalities developed a series of gaps in education, which subsequently have been translated into significant differences in income, health, and overall well-being [44]. There is a long-standing link between poverty and low levels of education [45]. Some studies highlight that poverty negatively affects children’s cognitive, social, and emotional development and they influence educational and behavioral outcomes [18]. In addition, poor families often live in disadvantaged areas with limited access to quality schools [46]. The fact that poorer children are grouped into certain schools continues to be a problem by reducing social cohesion and individual aspirations [47,48].

To reduce these barriers, countries have taken various measures. In the United Kingdom, the “Pupil Premium” policy has been implemented since 2011, providing additional funding to schools to support socio-economically disadvantaged students. Analyses show that this initiative has led to improved school performance for poor pupils even in disadvantaged regions such as the north of England [32].

Social and educational integration plays a key role in this context. Studies show that ethnic and social mixing in schools promotes intergroup contact, improving attitudes and trust between groups [47]. Schools that encourage diversity help reduce biases and contribute to building positive relationships between students [48]. At the same time, excessive educational integration may cause more affluent parents to send their children to other less integrated schools; in this way, differences between schools might increase [49].

In addition to social effects, education has a direct impact on poverty. The existing studies clearly highlight the existence of a causal relationship between education and various aspects of poverty. An extra year of education reduces both the likelihood of living in poverty and the subjective perception of poverty [50]. This underlines the importance of investing in education as an effective strategy to reduce inequalities through targeted interventions, and support in the public and political discourse on ethnic and social integration is needed [51].

In conclusion, educational policies that combat poverty can significantly contribute to reducing social and economic inequalities. Continued commitment to integration and support for disadvantaged students remains essential for creating a fairer and more prosperous society.

1.5. Social Inequalities

Education plays a key role in shaping social inequalities, acting as both a cause and a consequence of them. The nature of educational inequalities is closely linked to other dimensions of social inequalities, such as income, gender, ethnicity, and geographical environment [41]. These disparities directly influence access to opportunities and the quality of life of individuals.

One of the most persistent forms of educational inequality is the difference in performance between children from different socio-economic backgrounds. Social background has a major impact on school results [37]. In rural areas, a lack of resources and educational opportunities exacerbates these disparities; this is reflected in poorer student performance in these regions [52]. At the same time, cultural processes play a significant role in producing and maintaining these inequalities, highlighting the need for a cultural perspective in the analysis of educational disparities [53].

While education systems can help reduce inequalities, they often increase them. Parents with higher incomes and an increased level of education invest in their children’s education, widening intergenerational gaps [54]. In developed economies, intergenerational mobility is higher, and education contributes to economic growth [55].

In addition to financial investment, the time spent by parents with their children plays a crucial role in the development of cognitive and noncognitive skills; in return, they influence educational outcomes and opportunities in the labor market [54,56]. The lack of safe and stimulating environments, especially in disadvantaged areas, affects children’s physical, social, and cognitive development. Children growing up in slums are at high risk, highlighting the need for holistic interventions to address education and reduce the existing gaps [26]. Also, population dynamics, including differential fertility, contribute to the reduction in the resources available to each child, accentuating gaps in intergenerational mobility and economic development [57].

Education directly influences employment, income, and other aspects of life, such as health and civic participation [41]. However, its positive impact may be limited by the costs associated with education [58], reducing access for lower-income families. Increasing government spending on education has proven to be an effective measure to reduce income inequalities [59].

Educational programs adapted to local needs have demonstrated effectiveness in reducing educational inequalities. For example, Colombia’s “Rural Education Project-REP” has significantly reduced dropout rates and improved academic performance by applying flexible models and specialized teaching materials [29]. In addition, providing institutionalized after-school care can help reduce educational inequalities [60].

Education has the potential to reduce social inequalities, but its success depends on removing structural barriers and implementing equitable policies. Reforms in education systems and scalable programs, such as those implemented in rural areas, are essential to support the development of all children and promote a fairer society [25,41].

1.6. Juvenile Crime Rate

According to the literature, a negative correlation between education level and most types of crime can be mentioned [61]. Individuals with low levels of education are more likely to commit antisocial acts. This relationship is complex, and it is important to clearly establish causality in order to assess how investing in education can effectively reduce crime [62].

The rate of juvenile delinquency is influenced by a variety of factors, including overcrowding; access to education—especially between the ages of 16 and 18—the family’s financial situation; cultural and regional differences; and family criminal history [38]. Thus, the lack of education in critical periods increases the risk of deviant behaviors.

Empirical studies show that education has a strong causal effect in reducing crime. People who spent more time in school were less likely to commit crime; the effect is influenced by the level and quality of education, social context, and individual characteristics [62]. In addition, involvement in extracurricular activities was associated with a reduction in problematic behaviors—such as violence and substance use—with the engaged students exhibiting more positive behaviors [63].

Educational programs oriented to mentoring or other additional activities have proven effective in preventing risky behaviors. For example, mentoring programs for disadvantaged students have improved school performance and reduced risky behaviors; they created stable and lasting relationships that have contributed to social acceptance, improved attitudes toward school, and improved school outcomes [64]. Similarly, additional after-school programs improved children’s educational skills and had a positive impact on problematic behaviors [65].

In general, researchers argue that investing in education is an effective strategy for spending public funds to reduce delinquency [61,62]. Investing in improving the quality of education brings considerable social benefits by reducing juvenile crime. Even though the evidence regarding the direct effects of the quality of education is sometimes nonconclusive, increasing the level of education significantly reduces crime [61]. Researchers provide valuable insight regarding the importance of education and its influence on the development of future generations [38]; also, it can guide future practices and measures [66].

1.7. Students’ Nutrition

Students’ education and nutrition are interconnected through their mutual influence on school health and performance. Well-implemented school feeding programs have the potential to reduce social inequalities, improve health, and support children’s educational success.

One of the main challenges in terms of student nutrition is ensuring sufficient food and a correct distribution within school meal programs, especially in disadvantaged communities [67]. Social determinants and systemic biases contribute to inequalities in nutrition [68], especially by affecting children from low- and middle-income households, from rural areas, or children with less educated parents [69].

School nutritional programs represent effective tools in combating the effects of poverty [70]. They have demonstrated significant positive effects on children’s health and cognitive performance, as seen in South Africa and other regions [71,72]. In China, the Nutrition Improvement Program has increased the cognitive abilities of poor students by positively influencing their health, sense of belonging to school, and aspirations for the future [73]. In Peru, the implementation of a breakfast program in rural schools has led to increased school attendance and a decrease in school dropouts. Significant improvements in memory, arithmetic, and reading comprehension have also been observed, especially when feeding programs are supported by a supportive educational environment [74].

Adequate nutrition in schools is an important factor in stimulating economic development through the impact on school performance and health. It has been seen in Indonesia that involvement in these types of programs has led to increased cognitive performance and improved participation in school programs [72]. These initiatives also support school success by improving health, food safety, hygiene, and critical thinking skills [75].

The efficiency and maintenance of meal programs in schools are conditioned by the allocation of adequate budgets, community involvement [67], and the integration of technology, which contributes to good administration and transparency of the program [75]. There is, also, a need for an educational environment that supports learning complementing the positive effects of nutrition [74]. To become effective, these programs must be followed by policies in the field of education to promote healthy nutrition; they should include interventions to change consumption behavior, school initiatives, dietary guidelines, and other measures aimed at ensuring the well-being and health of students [68].

1.8. The Degree of Discrimination

The relationship between education and the degree of discrimination is complex, involving structural, cultural, and individual factors. Research shows that discrimination, based on race or gender, significantly interferes with the well-being of marginalized students; as a result, their educational outcomes and personal development might be affected [76]. In many countries, children from immigrant and ethnic minority groups lag behind majority peers in terms of skills acquired; these aspects suggest systemic inequalities [77,78].

Research highlights the interaction of various factors that contribute to the appearance of discriminatory processes in schools towards different categories of students. Inclusive education can mitigate these disparities by providing equal access to educational opportunities, but the current system often perpetuates inequalities, both in schools and in society [40].

The lack of exposure to different cultures and religious differences also contributes to discrimination against students, especially in communities unfamiliarized with diversity [79]. In addition, social class plays as important a role as ethnicity in predicting educational performance; teachers’ biased expectations exacerbate these inequalities. The practice of ranking students according to performance contributes to increasing educational inequalities and reinforces socio-economic differences, and teachers’ recommendations are often biased against students from disadvantaged socio-economic backgrounds [80].

Another discriminatory mechanism comes from teacher stereotypes, which negatively influence the assessment of students from disadvantaged backgrounds—especially in the case of Roma students and immigrants [81,82]. Studies suggest that interventions that bring to attention stereotypes can partially reduce this type of discrimination [82]. However, the effects of discrimination in grading negatively affect the self-confidence and future opportunities of marginalized students [81].

To combat these problems, research stresses the need to integrate equality and anti-discrimination perspectives into teaching methods [83], as well as the transition from a segregated to an inclusive educational system [84]. Changing stereotypes and raising awareness of structural racism remain key priorities for reducing discrimination in education [85].

1.9. Students’ Ability to Find a Job After Completing Their Studies

The relationship between education and students’ ability to find a job is a complex one and it influences numerous dimensions of integration into the labor market. Inequalities in the labor market are noticed in various forms, such as differences in employment opportunities, wages, working hours, and job security [86].

Educational inequalities attract the attention of public policies because of their profound impact on later life outcomes; the most obvious are employment and earnings but, also, other aspects such as health, happiness, or civic participation might influence this relationship [41]. Skills developed through education influence employee performance; they demonstrate a direct link between competence, self-efficacy, and professional success [87]. People with a higher level of education have more chances for employment and higher earnings; at the same time, education contributes to several indirect long-term benefits [41].

Moreover, skills developed during education are strongly influenced by parents’ level of education, with a significant contribution to the labor market performance of the next generations [56]. Parents with a higher level of education invest more time and resources in their children’s development; this attitude affects intergenerational mobility and wage inequality [54]. Population dynamics influences intergenerational mobility by changing the composition of the workforce; so, there is a link between education, economic development, and equal opportunities [57]. Intergenerational mobility encountered in developed economies is positively correlated with equal pay, which underlines the importance of education in reducing economic gaps [55].

Education policies and financial support initiatives—such as those offered by the EU through the European Social Fund—aim to reduce early school drop-out, to improve citizens’ skills, and to facilitate the transition of young people into an increasingly dynamic labor market [88]. Vocational education and training (VET) has also been shown to support an easier integration of young people into the labor market and it provides benefits in terms of earnings and job autonomy [89].

In addition, the decentralization of education through an adapted curriculum can contribute to reducing school dropout and developing students’ professional and economic skills, with a positive impact on economic inclusion [90]. The importance of education in developing general skills is starting to become more and more evident, as it ensures the adaptability of workers to the changing demands of the labor market [91].

Accelerated digitalization brings into question the need for multidimensional vocational training that allows workers to respond to new economic and technological challenges. A closer connection between the education system and labor market requirements becomes essential in ensuring economic competitiveness [92]. Financial education is also essential for promoting economic resilience and social inclusion, especially for the vulnerable population, contributing to social mobility [93]. Financial incentives can increase academic effort and, implicitly, success in the job market [94].

1.10. The Student’s Life Quality

The relationship between education and students’ life quality is a profound one and it is addressed by a variety of studies. By analyzing the impact of education on shaping students’ life quality, some authors have considered the influence of education on various dimensions of students’ existence, from physical and emotional health to social relationships and personal achievements (in key areas such as personal achievement, material well-being and standard of living, emotional resilience, physical health, community integration, and personal safety). Their conclusions highlighted some positive effects of education on improving their quality of life [95].

Research shows that students with access to an equitable education have a higher health-related quality of life. This aspect is more pronounced among girls and students from disadvantaged backgrounds, underlining the importance of an accessible education system [96]. Favorable school environments also help reduce health problems [97].

The school climate is an essential element for a holistic approach to improving the student’s quality of life. It contributes to the reduction in depressive symptoms; suicidal ideas; and tobacco, alcohol, and drug use while having a positive impact on school performance [98]. At the same time, a positive school climate was associated with reduced internalization problems and the risk of poor mental health [99].

The quality of the educational environment influences the socio-emotional development of children. The existing studies reveal that a positive school climate is associated with better socio-emotional functioning, encouraging healthy relationships between students and teachers, as well as positive behaviors [100,101], and it provides a sense of safety and support, which improves academic performance and reduces discipline problems [102]. The school climate is becoming an important aspect of educational policy, and it is necessary to identify and implement effective strategies to improve it [103].

Extracurricular educational programs—such as after-school programs—have a significant positive impact on children’s well-being, providing them with opportunities to develop self-control, social skills, and leisure-time satisfaction [104,105]. In rural areas, social and emotional learning programs strengthen students’ socio-emotional skills and relationship skills, having a particular effect on those from vulnerable communities [106].

The so-called “Second-chance education programs” are, also, an essential component in institutions that aim to ensure access and equity for socio-economically disadvantaged groups. These programs’ success comes especially from their contribution to the participants’ social and personal development [107]. This type of initiative shows that education can be a transformative tool in increasing the quality of life for all students regardless of their social or economic context.

1.11. Students’ Health Status

The absence of safe, stimulating, and health-promoting environments in schools can hinder the harmonious development of children, affecting their progress [26]. Social and territorial health inequalities are also reflected in students’ health indicators and behaviors [108]. The most important factors influencing teenagers’ health globally are structural factors—such as national wealth, income inequality, and access to education [109].

Children living in poverty are at higher risk of health problems [18]; this aspect suggests that education policies must also address these issues to reduce vulnerabilities. On the other hand, research shows that educational attainment has positive effects on health [95,110] by leading to greater awareness and accessibility of health services, and adults with higher education have a longer lifespan and a better quality of life [111].

Education influences thinking patterns and decision making, so each additional year of education brings significant health benefits [112]. This effect is more visible among girls and students from disadvantaged areas [96]. Education can also prevent depression and other mental health conditions, suggesting that educational opportunities should be expanded to have a positive long-term impact on health [113,114] mental health conditions being more common in people with low education [115]. Higher educational attainment is associated with better health, reduced risk of depression and obesity, and longer lifespan [116].

Socio-economic factors such as the combination of education and income influence health-related quality of life [117]. Well-funded educational programs can reduce health disparities [118] and they can help reduce inequality in income distribution [59]. For example, in China, nutrition programs implemented for poor students have significantly improved their health and cognitive performance [73]. In Norway, strengthening subjects such as “Food and Health” and increasing teachers’ skills can positively influence students’ food choices [119].

The school approach that promotes health literacy has a direct impact on students’ behaviors: it reduces social inequalities [108]. Supportive school environments contribute to improved mental health and positive functioning in young people [97]. The so-called “Before and after school” programs support students’ physical activity and emotional well-being [120], while food programs ensure their daily needs with a significant impact on the health and educational success of students [75].

Public authorities should invest more in education as a public health strategy, as educational policies can have a considerable effect on the health of the population [96,112].

2. Research Context and Methodology

In Romania, educational interventions supported by the European Union have played a key role in reducing socio-economic gaps and promoting inclusion. This section provides an overview of the context and methodological approach used to assess the impact of these initiatives on the development of students from disadvantaged backgrounds.

2.1. Research Context

Education in Romania is supported by European programs that aim to improve the quality of education and to assure equitable access to educational services. Projects funded by the European Union in Romania were aimed at reducing socio-economic gaps by reducing segregation, promoting equal opportunities, preventing discrimination, ensuring inclusion, and supporting lifelong learning, especially for vulnerable groups, such as children from the Roma minority, rural areas, or socio-economically disadvantaged communities, through complementary educational programs and community partnerships.

According to EU’s Cohesion Open data Platform [121], between 2014 and 2020, Romania was the beneficiary of structural and investment funds of more than EUR 1.5 billion for educational programs, to be implemented until 2023. The main financing programs for education in Romania were the following: “Operational Program Human Capital” (OPHC)—with the aim of improving the quality of education and equitable access to education through prevention of school dropout, assuring equal chances to education, reducing discrimination, school integration, and long-life education [122]; “Regional Operational Program”—the most important program for education with the established objectives of rehabilitation, modernization, and infrastructure development [123]; “Erasmus+”—the most important EU funding program for education and training, with the aim of supporting priorities and activities leading to social inclusion, green transition, transition to digital education and democracy, offering opportunities for mobility and cooperation [124]; and “The European Economic Area (EEA) and Norway Grants” and “Horizon 2020”—aimed at supporting research and innovation, strengthening international collaboration in education, promoting social inclusion [125,126].

Similarly, Romania benefited from the “Sectoral Operational Program for the Development of Human Resources” (SOPDHS)—between 2007 and 2013—[127], and, also, the funding programs “Education and Employment Program” [128] and the “National Recovery and Resilience Plan”—between 2021 and 2027 (NRRP) [129].

Projects financed by the European Union in the field of education generally have a multi-regional character; they are implemented extensively throughout the national territory [130].

Accessing European funds for education is possible for all schools in Romania; the process is carried out through a competitive procedure [123,124,125] which involves identifying funding calls, drafting the project according to the requirements of the funding program, and submitting it for evaluation. The selection of the beneficiary schools is based on criteria such as educational impact, the needs of the school community, and alignment with the objectives of the funding program.

The assessment of the interventions financed from European Union funds and the national budget in the field of vocational education and training in Romania through these financing programs [131] positions education as the most important factor for the sustainability of personal development and integration into the labor market in disadvantaged areas.

As understanding the results in European policymaking gives the importance of the financial interventions’ impact, the European Union is paying increasing attention to impact assessments [132]; thus, it has its own regulations for that [133].

In this context, special emphasis is placed on identifying the tangible improvements brought by the educational programs funded by the European Union in the socio-economic situation of Romanian students and their impact on the sustainability and inclusion of the educational system in Romania so that their effective implementation is no longer a challenge.

2.2. Methodology

The research approach was guided by the following main question: What is the impact of educational programs financed by EU funds on the socio-economic situation of Romanian students? In addition, the researchers tried to answer other questions: What is the impact of EU fundings in terms of socio-economic development? To what extent the progress of each socio-economic component can be related to EU financial intervention through educational programs? What other factors had a positive influence on the evolution of students’ socio-economic indicators?

Considering the research problem and the purpose of this study, the following objectives have been established:

O1.

Determining the teachers’ perspective about the improvements of components relevant to the students’ socio-economic situation;

O2.

Determining the extent to which the EU intervention determines progress in education;

O3.

Determining the extent to which the evolutions in the socio-economic level of students are related to students’ family income;

O4.

Identifying the factors with a positive influence on the evolution of students’ socio-economic indicators.

To achieve these objectives, a quantitative, descriptive marketing research was carried out through a survey among teachers who teach in primary, secondary, and high school classes in Romania.

The researched population was represented by 171,477 teachers from primary, secondary, and high schools in Romania, except pre-school education, during the study period. The sample size (1537 people) was determined starting from the method of calculating the confidence interval [134,135]. The confidence interval was set at 95%, (α = 0.05), for this level the corresponding value in the table of the normal distribution zα/2 being 1.96 and an error, E = ±2.5%. Given that the standard deviation is unknown, it was estimated by considering the maximum value of the standard deviation in the situation where there is equality between the number of favorable responses and the number of unfavorable responses according to the Cochran method [136,137,138].

After data collection, each response was checked for the respondents’ eligibility and the sample’s representativeness. This process was followed by the recovery phase of the sample by randomly eliminating the responses that would have led to the over-representation of some schools or categories of schools. After completing these stages, the sample volume reached 1220 people, which led to a recalculation of the maximum error, reaching a value of 2.8%.

For sampling, several sampling methods were combined. To determine the schools and the selected teachers, two random sampling methods were used, namely the proportionally stratified sampling method and the simple random sampling. As it was not possible to implement a random sampling method for the selection of responding teachers from the selected schools, a non-random sampling method, namely the volunteer-based method, was used at this stage. Although a certain number of respondents from each school was not imposed, to avoid the situation of over-representation in the process of data verification and sample recovery, a maximum of six questionnaires from each school were kept in the research, coming from teachers who teach at different educational cycles. The sample was validated from the perspective of its representativeness in terms of the characteristic levels of education at which they teach and the residency environments.

The share of respondents who work in urban areas was 61.39% and of those who work in rural areas was 38.61%. As for the levels of education that the interviewed subjects teach, the distribution was the following: teachers who teach in primary schools 29.8%, in secondary schools 37.8%, in high schools and colleges 27.4%, and in vocational schools 5.2%.

To determine the degree to which the structure of the sample is the same as the researched population’s structure in terms of characteristics, residence environment, and levels of education, we verified it with the Student t-test for comparing the differences between percentages, applied with the IBM SPSS system. The significance levels (Sig.−2 tailed) of 0.124 for the average residence variable, 0.627 for the primary and secondary education level, and 0.631 for the primary and secondary education level showed that it can be guaranteed with a probability of 95% that there are no significant differences between the percentages obtained at the level of the sample and at the level of the researched population. Considering the results, the sample was considered representative of the population of Romanian teachers. No sample recovery was required.

A sample of experienced teachers was considered relevant to achieve the research objectives. To meet this condition, a filter question regarding the seniority of the subjects in the school they represent was applied; it was considered that only experienced teachers (at least three years of experience) are able to observe and assess the changes that occurred at the level of the variables submitted to the research during the analyzed period. The number of respondents who fulfilled this condition and answered the questions meant to lead to meeting the research objectives was 1090 teachers.

All the participants were informed about the purpose of the research, and they gave their informed consent. The questionnaires were accompanied by a letter that provided the subjects with information related to informed consent, the subject of the research, the method of data collection, and the anonymity and confidentiality of responses. Before starting to fill out the questionnaire, each participant expressed informed consent for participating in this study by going through a special section. Data confidentiality was ensured throughout the data collection and the analysis process. The research questionnaire was drafted so that it can be self-administered by the subjects.

The teachers’ opinion regarding the changes in the socio-economic students’ situation was measured with the numerical semantic differential scale of the interval type, from 1 (the situation became a lot worse) to 5 (the situation has improved a lot), for eight aspects considered as defining for the measurement of the socio-economic situation: the level of poverty of the students’ families, social inequalities, the juvenile delinquency rate, students’ nutrition, degree of discrimination, students’ abilities to find a job (when appropriate), students’ quality of life, and students’ health status. The questionnaire included a question related to the implementation of EU-funded projects in the considered period (2014–2022) measured on a dichotomous scale. The aspects related to the economic situation of the families from which most of the students come (families with good or very good economic situations, families with medium economic situations, or families with precarious economic situations) and the education cycle taught by the interviewed teacher (primary, secondary, vocational, and high school) were measured by means of nominal scales with a single answer option. In the end, the questionnaire included some questions to characterize the respondents regarding the environment and the development region in which the school they represent is located and seniority in the education of the interviewed teachers.

Data collection was carried out between 31 March and 1 May 2023 using the computer-assisted interviewing method (CAWI) [139] due to the multiple advantages it confers [140,141,142]. Data were processed with the IBM SPSS—Statistical Package for Social Sciences, version 28.0.1.0

The analysis began with the assessment of the internal consistency of the scale by Cronbach’s Alpha coefficient. To identify the general trends and variations between the analyzed aspects, the average values and standard deviations were calculated for each item. To analyze the influence of EU-funded projects, we tested the differences between the group of schools where EU-funded projects were implemented and the group of schools where such projects were not implemented by using the Student t-test for independent samples.

To assess the impact of students’ socio-economic developments according to family income and their participation in educational projects funded by the European Union (EU), two statistical tests were applied. The ANOVA test was used to identify the differences between groups of students based on family income (low-, medium-, and high-income families) for the 8 aspects of socio-economic development. The t-test for two independent samples was used to compare the progress of students from low-income families and those from high- and middle-income families who participated in EU-funded educational projects versus those who did not. The group averages and the differences between them were analyzed for a detailed understanding of the impact of educational interventions on students from various socio-economic groups. The results were interpreted in a statistical significance context by setting the significance thresholds at p < 0.05

Next, an analytical approach was carried out to classify the analyzed cases according to the evolution of students’ socio-economic indicators. Thus, a k-means cluster analysis was computed which returned two clusters with significant differences between the means obtained for the analyzed indicators: a group characterized by a lower evolution (Cluster 1) and another characterized by a higher evolution (Cluster 2). The number of clusters was decided after applying a Hierarchical Cluster method. The k-means cluster analysis was also successively applied for more than two clusters, but the convergence was not obtained in less than ten iterations. Therefore, the two clusters were retained, for which the convergence was obtained after 3 iterations.

To identify the factors influencing membership to the group with a higher evolution (EVOL), a binary logistic regression was computed using as independent factors the implementation of EU-funded projects (FIN) and the educational cycle of the students that were evaluated: primary education (ISCED1), lower secondary education (ISCED2), vocational education (ISCED3.1), and high-school education (ISCED3.2). The binary logistic regression was computed because a binary scale was used for all the analyzed variables. The regression equation was the following:

$$P \left(EVOL=1\right)={\displaystyle \frac{e^{\alpha +{\beta }_{1}FIN+{\beta }_{2}ISCED1+{\beta }_{3}ISCED2+{\beta }_{4}ISCED3.1+{\beta }_{5}ISCED3.2}}{1+e^{\alpha +{\beta }_{1}FIN+{\beta }_{2}ISCED1+{\beta }_{3}ISCED2+{\beta }_{4}ISCED3.1+{\beta }_{5}ISCED3.2}}}$$

where

• FIN—an independent variable representing funding, a factor influencing the evolution (EVOL).
• ISCED1—an independent variable indicating the level of primary education according to the ISCED (International Standard Classification of Education).
• ISCED2—an independent variable indicating the level of lower secondary education according to ISCED.
• e—constant.

By applying the Forward Stepwise (Conditional) selection procedure, the variables selected in the model were FIN and ISCED 3.2 but due to a strong negative influence of the variable ISCED 3.2 on the dependent variable, this one was excluded, and the model was repeated with the rest of variables. Finally, the following factors with a positive influence on the evolution of students’ socio-economic indicators (EVOL) were retained: EU-funded projects (FIN), primary education (ISCED1), and lower secondary education (ISCED2).

3. Results

3.1. O1 Determining the Teachers’ Perspective About the Improvements of Components Relevant to the Students’ Socio-Economic Situation

Eight items were analyzed to measure the improvements regarding the socio-economic situation from the teacher’s perspective. The internal consistency of the used items within the scale was estimated by calculating Cronbach’s Alpha reliability coefficient. The Cronbach’s Alpha value was over 0.9 (0.931 for Q4, which confirms the reliability of the internal consistency of the items).

Data analysis revealed that the average of all the aspects analyzed is 3.219. For most aspects, the module is determined by the choice “The situation has improved” (4). The averages ranged from 3.410 for the degree of discrimination to 3.009 for the juvenile crime rate, as shown in

Table 1. The averages for the evolution of the aspects that outline the student’s socio-economic situation.

Changes in the Socio-Economic Situation of Pupils	Number of Respondents (n)	Mode	Mean	Std. Deviation
V5—degree of discrimination	1090	4	3.410	0.910
V7—students’ quality of life	1090	4	3.362	0.966
V8—students’ health status	1090	4	3.303	0.952
V4—students’ nutrition	1090	4	3.231	1.016
V6—students’ ability to find a job	1090	4	3.221	0.974
V2—social inequalities	1090	4	3.113	0.949
V1—students families’ poverty level	1090	3	3.105	0.914
V3—juvenile delinquency rate	1090	3	3.009	1.019

Source: the SPSS database.

. The results indicate that overall, for the Romanian students, most of the analyzed aspects had a very slight positive evolution; only the juvenile delinquency rate remained constant.

3.2. O2 Determining the Extent to Which the EU Intervention Determines Progress in Education

The research aimed to determine the influence of the intervention of funding programs on teachers’ assessment regarding the student’s socio-economic status. In this sense, we tested the difference between the averages for the following variables: family poverty level, social inequalities, juvenile crime rate, nutrition, degree of discrimination, students’ ability to find a job, students’ quality of life, and students’ health status, both in schools where EU-funded projects have been implemented and schools where these type of projects have not been implemented (Figure 1). Improvements were recorded to a great extent in schools where EU-funded projects were implemented. The biggest differences were recorded in terms of nutrition and the quality of students’ lives.

The results were tested using the Student t-test for independent samples (

Table 2. Results for Student t-test.

Changes in the Socio-Economic Situation of Pupils	Mean		t	Sig.
	Schools Where EU-Funded Projects Have Been Implemented	Schools Where no EU-Funded Projects Have Been Implemented
V1—students’ families’ poverty level	3.152	2.959	2.932	0.004
V2—social inequalities	3.154	2.985	2.475	0.014
V3—juvenile delinquency rate	3.028	2.951	1.059	0.290
V4—students’ nutrition	3.270	3.109	2.240	0.026
V5—degree of discrimination	3.458	3.260	3.015	0.003
V6—students ability to find a job	3.290	3.008	4.137	<0.001
V7—students’ quality of life	3.425	3.166	3.728	<0.001
V8—students’ health status	3.371	3.091	4.108	<0.001

Source: the SPSS database.

).

The results of the Student t-test revealed statistically significant differences (Sig. (2-tailed) <0.05) for the considered variables (the differences between the averages for the aspects related to the socio-economic students’ situation in schools where EU-funded projects have been implemented and schools where EU-funded projects have not been implemented); the only exception referred to the juvenile delinquency rate, for which the progress was very small.

3.3. O3 Determining the Extent to Which the Evolutions in the Socio-Economic Level of the Students Were Related to Students’ Family Income

The analysis continued with the ANOVA test to identify the differences between the eight items of the students’ socio-economic development considering the families with high or very high incomes, the families with medium incomes, and the families with low incomes.

The results generated by the comparison of means and the ANOVA test (

Table 3. ANOVA results in the case of the socio-economic situation of families.

		n	Mean	Std. Deviation	F	p
V1—students’ families’ poverty level	Most of the students come from families with good or very good economic situation	99	3.4141	0.78259	12.267	0.000
	Most of the students come from families with average economic situation	600	3.1533	0.8857
	Most of the students come from families with poor economic situation	391	2.9514	0.96087
V2—social inequalities	Most of the students come from families with good or very good economic situation	99	3.2424	0.89318	4.086	0.017
	Most of the students come from families with average economic situation	600	3.1600	0.9323
	Most of the students come from families with poor economic situation	391	3.0077	0.98055
V3—juvenile delinquency rate	Most of the students come from families with good or very good economic situation	99	3.1010	1.1019	3.397	0.034
	Most of the students come from families with average economic situation	600	3.0633	0.98875
	Most of students come from families with poor economic situation	391	2.9028	1.03566
V4—students’ nutrition	Most of the students come from families with good or very good economic situation	99	3.4848	0.96218	4.653	0.010
	Most of the students come from families with average economic situation	600	3.2467	0.99035
	Most of the students come from families with poor economic situation	391	3.1432	1.05731
V5—degree of discrimination	Most of the students come from families with good or very good economic situation	99	3.5253	0.90738	3.006	0.050
	Most of the students come from families with average economic situation	600	3.4467	0.91755
	Most of the students come from families with poor economic situation	391	3.3248	0.89407
V6—students’ ability to find a job	Most of the students come from families with good or very good economic situation	99	3.5556	0.92827	12.316	0.000
	Most of the students come from families with average economic situation	600	3.2717	0.95186
	Most of the students come from families with poor economic situation	391	3.0588	0.99182
V7—students’ quality of life	Most of the students come from families with good or very good economic situation	99	3.6364	0.86254	9.750	0.000
	Most of the students come from families with average economic situation	600	3.4150	0.93679
	Most of the students come from families with poor economic situation	391	3.2123	1.01196
V8—students’ health status	Most of the students come from families with good or very good economic situation	99	3.4949	0.92993	5.436	0.004
	Most of the students come from families with average economic situation	600	3.3450	0.94205
	Most of the students come from families with poor economic situation	391	3.1893	0.96076

Source: the SPSS database.

) revealed significant differences between groups of students based on their families’ incomes. The students from high- and middle-income families registered the greatest progress, while the students from low-income families appeared to see moderate improvements, and they remained vulnerable compared to the other groups.

Regarding the poverty level, the evolution presents an average of 3.41 points for students coming from high-income families, 3.15 points for those coming from medium incomes, and 2.95 points for those from low-income families; the differences are significant (F = 12.267, p < 0.001). These results suggest that the students from high- and middle-income families benefited from a more visible decrease in poverty compared to those from low-income families.

Social inequalities’ decreasing progress was perceived as having an average of 3.24 points for the students coming from high-income families, 3.16 points for those from middle-income families, and 3.00 points for low-income students, with significant differences between these averages (F = 4.086, p = 0.017). These results indicate a moderate improvement for students who come from wealthy or average families. Students from low-income families remain vulnerable to the effects of social inequalities.

The juvenile delinquency rate had an average of 3.10 points for the students coming from high-income families, 3.06 points for those from middle-income families, and 2.90 points for those from low-income families, the differences being significant (F = 3.397, p = 0.034). This result suggests a modest decrease in juvenile delinquency for students from high- and middle-income families; students from low-income families are perceived as more disposed to criminal behavior.

Regarding the students’ nutrition, the results revealed an average of 3.48 points for the students coming from high-income families, 3.24 points for those from middle-income families, and 3.23 points for those from low-income families, the differences being significant (F = 4.653 p = 0.010). All the categories appear to have benefited from better nutrition and access to regular meals; the improvements appeared to be more pronounced for the students from wealthy families. The evolution of the degree of discrimination (progress in reducing this phenomenon) had an average of 3.52 points for the students coming from high-income families, 3.44 points for those with medium incomes, and 3.32 points for those from low-income families; the differences are significant (F = 3.006, p = 0.050). This result suggests progress in reducing discrimination, but students from low-income families are still facing discriminatory experiences compared to other categories of students.

According to the analysis, the students’ ability to find a job had an average of 3.56 points for the students coming from high-income families, 3.27 points for those with medium incomes, and 3.06 points for those from low-income families, the differences being significant (F = 12.316, p = 0.000). These data could suggest that students from higher-income families have easier access to educational resources, traineeships, or professional contacts that can facilitate their integration into the labor market, while those from lower-income families face more obstacles, such as the lack of access to similar opportunities or a narrower support network.

The student’s quality of life analysis indicated an average of 3.63 points for the students coming from high-income families, 3.41 points for those with medium incomes, and 3.21 points for those from low-income families; the differences are significant (F = 9.750, p < 0.001). The results suggest that students from high-income families have a higher perceived quality of life improvement, reflecting greater economic stability and access to resources.

The students’ health status analysis revealed an average of 3.49 points for students coming from high-income families, 3.34 points for those from middle-income families, and 3.18 for those with low incomes, the differences being significant (F = 5.436, p = 0.004). These results suggest a moderate improvement in health for all three student categories, which might probably be associated with better nutrition and access to medical resources. To get a clear picture of the educational projects’ impact on the students’ socio-economic situation, the t-test for two independent samples was applied. The analysis aimed to compare the eight considered variables’ evolution for students coming from low-income families that were beneficiaries of the EU funding projects with those that did not benefit from these kinds of projects. The same type of analysis was put into practice for students coming from high- and medium-income families.

The results of the statistical tests applied for the two sub-samples of students from low-income families showed clear differences between those from schools that have benefited from EU-funded projects and those students coming from schools without EU funding for five of the eight analyzed variables (

Table 4. Results for Student t-test.

EU Funded Projects Have Been Implemented in the Represented School		n	Mean	Std. Deviation	F	p
V1—students’ families’ poverty level _P	No	100	2.8700	0.98119	0.642	0.327
	Yes	291	2.9794	0.9539
V2—social inequalities_P	No	100	2.8900	1.01399	0.662	0.164
	Yes	291	3.0481	0.96727
V3—juvenile delinquency rate_P	No	100	2.8000	1.07309	1.922	0.250
	Yes	291	2.9381	1.02198
V4—students’ nutrition_P	No	100	2.9600	1.07233	0.050	0.044
	Yes	291	3.2062	1.04655
V5—degree of discrimination_P	No	100	3.1700	0.91071	0.395	0.045
	Yes	291	3.3780	0.88360
V6—students’ ability to find a job_P	No	100	2.8900	0.99387	0.117	0.048
	Yes	291	3.1168	0.98616
V7—students’ quality of life_P	No	100	2.9800	1.06344	0.160	0.008
	Yes	291	3.2921	0.98291
V8—students’ health status_P	No	100	2.9200	0.99168	0.000	0.001
	Yes	291	3.2818	0.93383

p = most of the students come from families with poor economic situations. Source: the SPSS database.

).

The students’ health status had an average of 2.92 for the schools without EU projects and 3.28 for those with projects; the difference is significant (p = 0.001). For the students’ quality of life, the average of 2.98 in the schools without projects compared to 3.29 in the schools with projects indicates a significant difference (p = 0.008). The improvement in students’ nutrition has an average of 2.96 points for the students coming from schools where no projects have been implemented and 3.21 points for those with EU projects; the difference is statistically significant (p = 0.044). The students’ ability to find a job indicates an average of 2.89 for the schools without projects and 3.12 for those with projects; the difference is significant (p = 0.048). For the degree of discrimination, the average is 3.17 for the schools without projects and 3.38 for those with projects; the difference is statistically significant (p = 0.045). These results suggest that EU-funded projects have had a significant impact on students from low-income families in terms of these variables.

In contrast, the level of poverty (average of 2.87 for the schools without projects and 2.98 for those with projects, p = 0.327), social inequalities (average of 2.89 for the schools without projects compared to 3.05 for those with projects, p = 0.164), and the juvenile crime rate (average of 2.80 for the schools without projects and 2.94 for those with projects, p = 0.250) did not register significant perceived differences, stressing the need for more targeted interventions in these areas.

The results of the statistical tests applied for students from high- and middle-income families in the two sub-samples—students coming from schools that have benefited from projects funded by the European Union and those without projects—showed significant differences for several variables (

Table 5. Results for Student t-test.

EU Funded Projects Have Been Implemented in the Represented School		n	Mean	Std. Deviation	F	p
V1—students’ families’ poverty level _A_G	No	165	3.0121	0.91723	2.135	0.003
	Yes	534	3.2453	0.85635
V2—social inequalities_A_G	No	165	3.0424	0.95222	0.244	0.040
	Yes	534	3.2116	0.91587
V3—juvenile delinquency rate_A_G	No	165	3.0424	1.00214	0.128	0.701
	Yes	534	3.0768	1.00641
V4—students’ nutrition_A_G	No	165	3.2000	0.97655	0.455	0.233
	Yes	534	3.3052	0.99270
V5—degree of discrimination_A_G	No	165	3.3152	0.95513	0.941	0.022
	Yes	534	3.5019	0.89976
V6—students’ ability to find a job_A_G	No	165	3.0788	0.94345	1.566	0.000
	Yes	534	3.3839	0.94532
V7—students’ quality of life_A_G	No	165	3.2788	0.94086	0.064	0.008
	Yes	534	3.4981	0.92037
V8—students’ health status_A_G	No	165	3.1939	0.95571	0.183	0.007
	Yes	534	3.4195	0.93105

A = most students come from families with an average economic situation. G = most students come from families with good or very good economic situations. Source: the SPSS database.

)

Significant differences between schools with and without EU projects were observed for six of the eight variables analyzed. The biggest difference was recorded for the students’ ability to find a job. The average in the schools without projects was 3.08 points, and in the schools with projects, it was 3.38 points (p = 0.000). This suggests a considerable impact of the projects on the education of high- and middle-income students for integration into the labor market.

Another significant impact was recorded for the poverty level of the students’ families. The average in the schools without projects was 3.01 points, and in the schools with projects, it was 3.25 points (p = 0.003). It suggests that the projects have contributed to reducing poverty among students. Though it is hard to appreciate that educational projects are able to influence the students’ families’ poverty levels, the research results revealed that the benefits, rewards, and prizes received by the students in these types of projects influence the way that teachers appreciate the material status of students’ families.

Regarding the students’ health status, the average in the schools without EU projects was 3.19 points, and in the schools with projects, it was 3.42 points. The significant difference (p = 0.007) suggests a positive impact on the health status of early childhood students from middle- or high-income families, possibly due to better access to health services and health education.

A significant difference was observed in terms of the students’ quality of life. The average in the schools without EU projects was 3.28 points, and in the schools with projects, it was 3.50 points, (p = 0.008). These values suggest that the projects have improved students’ living conditions, including the educational and social environment.

A significant impact of EU projects (p = 0.022) was also observed for the degree of discrimination. The average in the schools without EU projects was 3.32 points, and in the schools with projects, it was 3.50 points. The projects contributed to a more inclusive and equitable educational environment, reducing the perception of discrimination among students.

A significant difference (p = 0.040) was also observed in terms of social inequalities. In the schools without EU projects, the average was 3.04 points, and in the schools with implemented projects, the average was 3.21 points. These results suggest that the projects had a positive effect on reducing social inequalities and creating a fairer environment.

In contrast, no significant differences were observed for certain variables, indicating possible areas where additional interventions or more targeted strategies might be needed. These are the juvenile delinquency rates for which no significant differences were recorded. The average in the schools without EU projects was 3.04 points, and in the schools with projects, it was 3.08 points (p = 0.701). It suggests that EU projects have not had a significant impact on the reduction in juvenile delinquency. Also, there have been no significant differences in the nutrition of students coming from high-income families. The average in the schools without EU projects was 3.20 points, and in the schools with projects, it was 3.31 points (p = 0.233). This suggests that the projects did not have a significant impact on improving the nutrition of these students.

3.4. O4. Identifying the Factors with a Positive Influence on the Evolution of Students’ Socio-Economic Indicators

A k-means cluster analysis has been computed to classify students according to their evolution regarding the analyzed socio-economic indicators. Two clusters have been obtained from a number of 1090 valid cases (

Table 6. Final cluster centers.

	Cluster
	1	2
V1—students families’ poverty level	2.39	3.60
V2—social inequalities	2.33	3.66
V3—juvenile delinquency rate	2.25	3.54
V4—students’ nutrition	2.35	3.84
V5—degree of discrimination	2.71	3.90
V6—students’ ability to find a job	2.52	3.70
V7—students’ quality of life	2.52	3.95
V8—students’ health status	2.52	3.85

Source: the SPSS database.

): Cluster 1 (n1 = 446 cases), characterized by lower evolution, and Cluster 2 (n1 = 644 cases), characterized by higher evolution.

The results of the analysis of the relationship between the EU-funded projects implementation and membership in the resulting clusters revealed that the percentage of schools that implemented such projects is higher in the case of Cluster 2 than in the case of Cluster 1 (

Table 7. Final cluster centers.

The School You Represent Has Implemented EU-Funded Projects—Cluster Number of Case Crosstabulation			Cluster Number of Case		Total
			1	2
The school you represent has implemented EU-funded projects	No	Count	132	133	265
		% within Cluster Number of Case	29.6%	20.7%	24.3%
	Yes	Count	314	511	825
		% within Cluster Number of Case	70.4%	79.3%	75.7%
Total		Count	446	644	1090
		% within Cluster Number of Case	100.0%	100.0%	100.0%

Pearson Chi-square = 11.456, Sig. = 0.001. Source: the SPSS database.

). This difference is statistically significant according to the Chi-square test, revealing that the evolution of the students’ socio-economic indicators has been higher in the schools that implemented European projects.

To identify the main factors that influence the membership of the cluster with higher evolution (EVOL), a binary logistic regression was used with the following independent variables: implementation of EU-funded projects (FIN), primary education (ISCED1), lower secondary education (ISCED2), and vocational education (ISCED3.1). High-school education (ISCED 3.2) was excluded due to its strong negative influence on the dependent variable as was explained in the methodological section.

According to the results, the probability of being part of Cluster 2 (EVOL) is influenced by the following independent variables: implementation of EU-funded projects (FIN), primary education (ISCED1), and lower secondary education (ISCED2). The following logistic regression equation was obtained:

$$P \left(EVOL=1\right)={\displaystyle \frac{e^{-0.386+0.525FIN+0.581 ISCED1+0.513 ISCED2}}{1+e^{-0.386+0.525FIN+0.581 ISCED1+0.513 ISCED2}}}$$

where

• FIN—an independent variable representing funding, a factor influencing the evolution (EVOL).
• ISCED1—an independent variable indicating the level of primary education according to the ISCED (International Standard Classification of Education).
• ISCED2—an independent variable indicating the level of lower secondary education according to ISCED.
• e—constant.

The results presented in

Table 8. Results of binary logistic regression.

Variables in the Equation		B	S.E.	Wald	df	Sig.	Exp(B)
Step 1 a	FIN	0.479	0.142	11.358	1	0.001	1.615
	Constant	0.008	0.123	0.004	1	0.951	1.008
Step 2 b	FIN	0.502	0.143	12.320	1	0.000	1.652
	ISCED1	0.310	0.138	5.023	1	0.025	1.364
	Constant	−0.099	0.132	0.561	1	0.454	0.906
Step 3 c	FIN	0.525	0.144	13.285	1	0.000	1.690
	ISCED1	0.581	0.159	13.391	1	0.000	1.787
	ISCED2	0.513	0.148	12.052	1	0.001	1.669
	Constant	−0.386	0.156	6.094	1	0.014	0.680

Source: the SPSS database. ^a Variable(s) entered on step 1: FIN. ^b Variable(s) entered on step 2: ISCED1. ^c Variable(s) entered on step 3: ISCED2.

(Exp(B)) reveal that the probability of obtaining a higher evolution in terms of the students’ socio-economic indicators is increasing with 69% for the schools that implemented EU-funded projects (FIN), with 78.7% for primary education (ISCED1) and 66.9% for lower secondary education (ISCED2).

4. Discussion

The analysis of student’s socio-economic situation—considering both those who have benefited from EU fundings and students that have not benefited from EU-funded educational projects—indicates a slight general improvement. The greatest improvement was reported in reducing the degree of discrimination. The fact that the interviewed teachers perceived a decrease in discrimination in schools reflects progress in promoting inclusion and social equity. The existing literature supports these findings. Several studies [47,48] highlight that diversity in the school environment contributes to reducing prejudice and to strengthening social cohesion. Progress in this area is a positive indicator that Romanian schools have begun to adopt practices that promote inclusion, although significant challenges remain for highly vulnerable groups, such as students from low-income families or ethnic minorities, as highlighted by Kisfalusi in his studies [79]. In addition to the progress in approaching discrimination, teachers observed significant improvements in the students’ quality of life. These developments confirm the conclusions of Hofmarcher [50], who emphasizes the role of education in reducing economic disparities by developing human capital.

Modest progress has been noted regarding students’ health and nutrition. These positive developments can be explained by the introduction of activities related to health education or school meals in many Romanian schools within isolated projects such as those funded by various NGOs or the EU, or national programs like “School Otherwise” (a national program aimed at developing students’ learning competencies and socio-emotional skills through various engaging activities organized over two weeks) or “Healthy Meal” (a program providing free daily nutritional support in the form of a food package or a hot meal). These results are also supported by other authors such as Dauenhauer and Kulinna [120] and Panchacola [75], who have shown that programs promoting physical activity, students’ emotional well-being, and nutrition have a significant impact on students’ health. Rakesh et al. [97] emphasize the importance of health programs integrated into the curriculum in reducing depressive symptoms and the risk of poor mental health among students.

The improvement in the school climate, evident in many Romanian schools, can play an important role in students’ mental health by reducing depressive symptoms and improving emotional resilience. These results are supported by other studies that emphasize that a safe and inclusive school environment supports emotional health and reduces the risk of deviant behaviors, such as the studies by Gase et al. [98] and László et al. [99]. These trends have also been observed by Cueto and Chinen [74] and Chunkai Zhao and Boou Chen [73] in similar contexts such as Peru and China, where school meal programs demonstrated a significant impact on health and academic performance.

More than that, the findings from this study bring a new perspective on this phenomenon—the EU funding process represents a chance for some categories of students, namely those coming from low-income families. As the results have shown, the situation regarding health and nutrition is different in their case and, in addition to the conclusions from other studies, we can affirm that for these students, the EU membership represents a particular premise in the government trying to increase the level of education for the Romanian children.

The juvenile crime rate has remained almost constant, being the least influenced aspect of the socio-economic situation. This result underscores the need for more specific interventions in this area, including mentoring and extracurricular programs, as per the studies by Carr and Marie [62] and Fredricks and Eccles [63].

The impact of EU-funded educational programs on the socio-economic situation of students in Romania clearly indicates that EU-funded educational projects positively influenced most of the analyzed aspects. The schools that implemented such projects recorded greater improvements than those that did not receive funding, particularly in terms of improving students’ health and quality of life, employability, and nutrition, and reducing social inequalities and poverty. These findings are supported by the studies by Ferrer-Estévez and Chalmeta [6], which demonstrated the effectiveness of integrated educational interventions in reducing socio-economic disparities.

However, the progress in almost all the aspects has been modest, indicating the limitations of isolated educational interventions, confirming the studies by Borbely et al. [18] and Robertson [45], which point out that poverty is a structural issue requiring systemic approaches, such as investments in infrastructure and complementary social policies.

The analysis, which aimed to find possible disparities connected with the students’ families’ incomes, showed that the students from high- and middle-income families benefited from progress in several components of the analyzed socio-economic situation compared to those from low-income families. The better results of students from more prosperous families reflect not only the effects of the implemented projects, but also the socio-economic context that amplifies these benefits. The better results achieved by students from families with good financial situations can be explained by a combination of economic, social, and educational factors, which influence the way in which these pupils benefit from educational interventions. They can have access to technology and study materials, tutoring, access to educational clubs, have a better emotional state and motivation, do not feel financial stress, and are not affected by prejudice or discrimination, factors that amplify the benefits of educational interventions, as it results from the studies by Abbott and Gallipoli [56], Christine Farquharson [41], and others [10,26,34,47,54]. For the students from low-income families, EU-funded programs had a significant impact on a smaller number of components (five components). However, the impact of EU-funded educational projects on these students was stronger than in the case of students from affluent families. The variable related to nutrition, which was not significantly influenced by EU funding in the case of middle- and high-income students, was strongly impacted by EU-funded educational projects for students from low-income families. Moreover, EU-funded educational projects had a significant impact on the quality of life and health of low-income students but did not significantly impact poverty and social inequalities. These findings are similar to those reported by Mostert [71], who highlighted that direct interventions, such as meal programs, can have an immediate impact, but reducing poverty requires more comprehensive policies.

Our findings also confirm the observations of Gorard and Siddiqui [32] regarding the importance of targeted policies to support disadvantaged students and underscore the need for targeted educational strategies to more effectively reduce gaps and support students from disadvantaged backgrounds, as also supported by Robertson [45]. The Romanian context gives a particular approach to this idea, as in the mentioned studies, the term “disadvantaged children” does not refer especially to financial aspects as it did in this research by connecting the variables’ influence considering different types of families with different levels of income.

Our analysis demonstrated that the implementation of EU-funded projects was identified as the main factor influencing students’ socio-economic progress. Furthermore, primary and lower secondary educational levels (ISCED1 and ISCED2) were associated with the greatest improvements, confirming the importance of early education interventions, as demonstrated by Gibbons and McNally [30] and Shava et al. [11]. These interventions lay the necessary foundation for reducing socio-economic disparities and promoting long-term development. Väänänen et al. [10] also emphasize that early education provides the necessary foundation for reducing social and economic gaps. In contrast, interventions at the high school level had a more limited impact, suggesting the need for vocational training programs aligned with labor market demands, as proposed by Müller and Wicht [89]. Although EU-funded programs positively influenced several dimensions of socio-economic development, the overall progress was modest. Structural barriers, such as economic disparities or the timing of interventions, limit the potential for transformative changes. This observation aligns with Borbely et al. [18] and Robertson [45], who argue that isolated educational interventions must be complemented with systemic socio-economic policies. The paper proposes a more comprehensive analytical framework to assess the impact of educational programs financed by the European Union. This framework goes beyond the classical economic perspectives usually targeted by the funders to verify the programs’ objectives’ fulfillment by measuring a set of indicators aimed at fundamental human rights values. By introducing an “external” evaluation criterion that gives the measurement a perspective of sustainable development, the paper brings elements of novelty that were not enough approached by the literature.

Limitations and Directions for Future Research

Although this study provided a detailed picture of the impact of EU programs, the analysis relied exclusively on teachers’ perceptions, limiting a comprehensive understanding of the impact of educational programs. The study was based on quantitative methods, which limit the ability to explore causality and participants’ individual experiences in depth. Additionally, the analysis did not include contextual factors such as school infrastructure, available resources, or community involvement, which could influence the impact of EU-funded programs.

Future research could integrate the students’ and parents’ perspectives and qualitative analyses to better understand the mechanisms through which education contributes to socio-economic development. Additionally, it should explore the long-term effects of EU-funded educational programs on the socio-economic integration of students, tracking indicators such as employability, income, and graduates’ social contribution. Moreover, a comparative approach among EU member states would be useful to identify the best practices and replicable models.

5. Conclusions

The results of our study lead to the identification of the premises and factors that influenced the extent of the funding programs’ contribution to education and the way that it can influence it in future funding programs. A positive evolution in the socio-economic development of Romanian students is confirmed; also, a significant, though modest, contribution of these programs to socio-economic development, particularly through improving quality of life, nutrition, and health and reducing social inequalities, was highlighted. However, although the programs generally succeeded in improving socio-economic indicators, disparities based on the socio-economic status of families still persist. This highlights the necessity for more targeted policies that prioritize vulnerable groups—such as students from low-income families. Through cluster analysis and logistic regression, it was found that the projects have the most significant impact on students from primary and lower-secondary education cycles, suggesting that early interventions have more profound and lasting effects. It demonstrated that it is necessary to prioritize the equitable allocation of resources, focusing on disadvantaged areas and reducing educational segregation, for more effective educational policies. Interventions through funded educational programs in primary and lower-secondary cycles, as well as the implementation of programs that combine formal education with socio-economic support, are recommended. Additionally, constant monitoring of the programs’ impact is essential to adjust interventions and ensure equal access to quality education.

The management of future funded programs will benefit from more comprehensive data, enabling the removal of constraints and factors that slow an easy project implementation. This will enhance the control over the efficiency of financial investments in education and increase the likelihood of significantly contributing to achieving the strategic objectives in the field of education concerning students’ socio-economic situations. Thus, the educational projects implemented in Romania will better contribute to achieving the Sustainable Development Goals of the 2030 Agenda, particularly SDG4, dedicated to inclusive and equitable education, and will lead to reduced inequalities and the building of a more prosperous and sustainable society.