Abstract
Keywords
Introduction
In the era of “mass entrepreneurship and innovation,” college students’ entrepreneurship has become a vital engine for promoting high-quality economic development (Zhang et al., 2020). However, previous research has found that the entrepreneurial intention of Chinese college students remains generally low, with a success rate of less than 3% (Zhang et al., 2020). Effectively stimulating college students’ entrepreneurial intention has thus become a focal point for both academia and governments (Liu et al., 2023; Zhou et al., 2021). In recent years, university entrepreneurship education, as a crucial means of cultivating entrepreneurial talent, has been the subject of considerable debate regarding its effectiveness (Chen, Wang, & Liu, 2023; Zhang & Li, 2023). While some studies have found that entrepreneurship education significantly enhances college students’ entrepreneurial intention (Nabi et al., 2017), others suggest its impact is minimal (Oosterbeek et al., 2010). This divergence may stem from the fact that existing research predominantly focuses on individual elements of entrepreneurship education, overlooking the synergistic effects among various components (Cai et al., 2019). In reality, entrepreneurship education is a complex and systematic endeavor, and its effectiveness depends on the organic integration of multiple factors, such as teaching content, teacher guidance, entrepreneurship competitions, and entrepreneurship practice (Wang et al., 2022). Nevertheless, current research on the combined effects of entrepreneurial education remains insufficient, lacking a systematic and holistic perspective (Li et al., 2021; Sun et al., 2024).
Additionally, recent advancements in entrepreneurship education research have begun to explore the multidimensional effects of entrepreneurial education portfolios (Liu et al., 2023). Significant complementary effects exist among the elements of entrepreneurship education, and the impact of a single element may be underestimated (Wang et al., 2022). The influence of entrepreneurial education portfolios on entrepreneurial intention exhibits nonlinear characteristics, with different combinations of elements potentially generating a “1 + 1 > 2” effect (Liu et al., 2023). Specifically, a well-designed entrepreneurial curriculum significantly enhances students’ entrepreneurial self-efficacy, thereby positively influencing their entrepreneurial intention (Brown & Mason, 2023). Teacher guidance, on the other hand, provides personalized feedback and mentorship, helping students overcome psychological barriers in the entrepreneurial process while bolstering their entrepreneurial confidence (Anderson & Jack, 2022). Entrepreneurship competitions simulate real entrepreneurial environments, stimulating students’ competitive spirit and innovative thinking while providing a platform to showcase and practice entrepreneurial ideas (Kuratko & Morris, 2023). Finally, entrepreneurship practice offers real-world entrepreneurial experiences, enabling students to translate theoretical knowledge into practical skills, thereby strengthening their entrepreneurial willingness (Obschonka & Stuetzer, 2023). These findings provide strong theoretical support for this study’s construction of a four-dimensional entrepreneurial education portfolio comprising “teaching content, teacher guidance, entrepreneurship competition, and entrepreneurship practice” (Liu et al., 2023; Wang et al., 2022).
Moreover, family background may also influence the effectiveness of entrepreneurship education (Anderson & Jack, 2022). Students with an entrepreneurial family background may be more likely to translate entrepreneurial education into actual entrepreneurial intention (Obschonka et al., 2015). However, existing studies often treat entrepreneurial family background as a control variable, neglecting its moderating role in the mechanism of entrepreneurship education (Cui & Sun, 2023; Sun et al., 2024). Entrepreneurial family background not only directly affects entrepreneurial intention but may also indirectly influence entrepreneurial behavior by moderating the pathways through which entrepreneurship education operates (Zhang et al., 2022). This finding provides a critical foundation for this study’s inclusion of entrepreneurial family background as a moderating variable.
Against this backdrop, this study constructs a four-dimensional entrepreneurial education portfolio comprising “teaching content, teacher guidance, entrepreneurship competition, and entrepreneurship practice” and introduces entrepreneurial family background as a moderating variable to explore the impact mechanism of entrepreneurial education portfolios on college students’ entrepreneurial intentions. This research not only helps clarify the root causes of the controversy surrounding the effectiveness of entrepreneurship education but also addresses the gap in existing studies regarding the combined effects of entrepreneurial education and individual differences (Fang & Zhang, 2023; Huang & Li, 2022). Furthermore, it provides new insights and evidence for optimizing university entrepreneurship education models and enhancing their practical effectiveness.
Literature Review and Hypothesis
Social Cognitive Theory
Social Cognitive Theory (SCT) posits that human behavior is shaped by the dynamic interplay between personal factors, environmental factors, and behavioral patterns (Bandura, 1986). In the context of entrepreneurship research, SCT provides a robust framework for understanding how individual develops entrepreneurial intentions through observational learning, self-efficacy, and environmental interactions (Fang & Zhang, 2023). Specifically, entrepreneurship education, as an environmental factor, enhances students’ entrepreneurial self-efficacy by providing knowledge, skills, and practical opportunities, thereby strengthening their entrepreneurial intentions (Huang & Li, 2022). Additionally, SCT emphasizes the importance of individual differences in shaping behavior. Personal factors, such as family background, may moderate the impact of environmental factors on behavioral outcomes (Obschonka & Stuetzer, 2023). Thus, SCT offers a solid theoretical foundation for this study to explore the impact of entrepreneurship education portfolios on entrepreneurial intentions and the moderating role of entrepreneurial family background.
Entrepreneurship Education
Entrepreneurship education is a critical tool for fostering entrepreneurial intentions, as it equips students with the knowledge, skills, and mindset necessary to pursue entrepreneurial opportunities (Brown & Mason, 2023). However, the effectiveness of entrepreneurship education depends not on a single element but on the synergistic effects of multiple components. Entrepreneurship education portfolios, including comprising teaching content, teacher guidance, entrepreneurship competition, and entrepreneurship practice, can significantly enhance students’ entrepreneurial intentions through complementary effects (Kuratko & Morris, 2023). Specifically, teaching content helps students build a cognitive framework for entrepreneurship by imparting systematic knowledge (Anderson & Jack, 2022); teacher guidance boosts students’ entrepreneurial confidence through personalized feedback and support (Sun et al., 2024); entrepreneurship competition simulates real entrepreneurial environments, stimulating students’ competitive spirit, and innovative thinking (Chen, Zhang, & Liu, 2023); and entrepreneurship practice provides hands-on experience, enabling students to translate theoretical knowledge into practical skills (Obschonka & Stuetzer, 2023). Despite these advancements, existing research often focuses on individual elements, leaving a gap in the systematic exploration of the combined effects of entrepreneurship education portfolios. This gap provides a significant research opportunity for this study.
Entrepreneurial Family Background
Entrepreneurial family background is a significant contextual factor influencing individuals’ entrepreneurial intentions. Students from entrepreneurial families are often exposed to entrepreneurial activities from a young age, providing them with relevant knowledge, skills, and resources that facilitate the translation of entrepreneurship education into tangible entrepreneurial intentions (Chen, Zhang, & Liu, 2023). Such a background fosters greater receptiveness to and application of entrepreneurship education by offering role models and creating a supportive environment (Kim & Park, 2022). Additionally, an entrepreneurial family background not only directly influences entrepreneurial intentions but may also indirectly affect entrepreneurial behavior by moderating the pathways through which entrepreneurship education impacts students (Müller & Hensellek, 2023). These findings underscore the critical role of entrepreneurial family background in the mechanism through which entrepreneurship education influences entrepreneurial intentions, offering a solid theoretical foundation for incorporating entrepreneurial family background as a moderating variable in this study.
Theoretical Framework and Hypothesis
Building on social cognitive theory and the literature reviewed above, this study proposes a theoretical framework to examine the impact of entrepreneurship education portfolios on undergraduate entrepreneurial intentions and the moderating role of entrepreneurial family background. The framework posits that entrepreneurship education portfolios positively influence entrepreneurial intentions by enhancing students’ knowledge, skills, and self-efficacy (Brown & Mason, 2023; Kuratko & Morris, 2023).
Teaching content forms the foundation of entrepreneurship education by providing students with the theoretical knowledge and conceptual frameworks necessary to understand entrepreneurship. Studies have consistently shown that well-designed curricula can significantly enhance students’ entrepreneurial self-efficacy and intentions. Entrepreneurship courses positively influence students’ attitudes toward entrepreneurship, which in turn increases their entrepreneurial intentions (Fayolle et al., 2006). Entrepreneurship education literature concluded that teaching content is one of the most effective components in fostering entrepreneurial intentions (Smith & Johnson, 2024). By equipping students with knowledge about opportunity recognition, business planning, and risk management, teaching content helps them develop a cognitive framework that supports entrepreneurial behavior (Brown & Taylor, 2024).
Teacher guidance plays a pivotal role in translating theoretical knowledge into practical insights (Anderson & Lee, 2023; Martinez & Carter, 2024). Effective mentorship and personalized feedback from instructors play a crucial role in boosting students’ confidence and motivation to pursue entrepreneurial ventures. Teacher guidance positively impacts students’ entrepreneurial intentions by offering role models and mitigating perceived barriers to entrepreneurship (Nguyen & Lee, 2023). Correspondingly, students who receive mentorship from experienced entrepreneurs are more likely to develop strong entrepreneurial intentions (Zhang & Chen, 2024). These findings highlight the significant role that teacher guidance and mentorship play in entrepreneurship education, making them essential components of a comprehensive educational approach.
Entrepreneurship competitions offer students a valuable platform to apply theoretical knowledge in a practical, simulated business environment, helping to cultivate creativity, teamwork, and problem-solving abilities. Research has shown that participating in such competitions positively impacts students’ entrepreneurial intentions. Specifically, students who take part in entrepreneurship competitions demonstrate increased levels of entrepreneurial self-efficacy and intentions compared to those who do not participate (Batz Liñeiro et al., 2024). These competitions expose students to real-world entrepreneurial challenges, enhancing their readiness to pursue entrepreneurial ventures (Zhang & Yang, 2024). This evidence highlights the importance of entrepreneurship competitions as an essential component of entrepreneurship education programs (Pilar & Tejedor Miralles, 2023).
Entrepreneurship practice, which includes internships, start-up projects, and other hands-on experiences, bridges the gap between theory and practice. By engaging in real-world entrepreneurial activities, students gain practical skills and a deeper understanding of the entrepreneurial process. Students who participate in entrepreneurship practice report higher levels of entrepreneurial intentions and are more likely to start their own businesses (Wang & Liu, 2022). Experiential learning activities, such as business simulations and start-up projects, significantly enhance students’ entrepreneurial intentions by providing them with a sense of accomplishment and confidence (Sofiullah et al., 2023). Therefore, the following hypotheses are proposed:
Simultaneously, entrepreneurial family background may amplify this effect by providing additional resources, role models, and a supportive environment (Fang & Zhang, 2023; Obschonka & Stuetzer, 2023). Entrepreneurial family background can influence a student’s entrepreneurial intentions by providing them with early exposure to entrepreneurship. Individuals from entrepreneurial families tend to have higher entrepreneurial intentions and are more likely to start their own businesses (Martins et al., 2023). These students often have role models and mentors within their family who provide both practical knowledge and emotional support, increasing their readiness to pursue entrepreneurial careers (Cheng & Li, 2022). They might feel more confident and motivated to pursue entrepreneurship due to the supportive family environment, which could enhance the effectiveness of entrepreneurship education (Zhang et al., 2022). Conversely, students without an entrepreneurial family background might not benefit from the same level of external support or encouragement, making them less likely to act on the education they receive (Chen & Liu, 2021). Therefore, the following hypotheses are proposed:
Figure 1 is the depiction of the construct relationships in our conceptual model.

The conceptual model.
Methodology
Data Collection and Demographic Profile
Accurate and sufficient empirical data are required to test these two research hypotheses. A questionnaire survey was conducted to collect the necessary data for this study, using a five-point Likert scale ranging from “1:
Descriptive Analysis.
Measurement Instruments and Questionnaire Development
Questionnaire utilized in this investigation was produced and verified in the English language. De-translation was employed by Brislin (1980) in order to convert metrics to Chinese from English. In order to ascertain measurement precision, multiple authors conducted exhaustive comparisons and translations of the scales from Chinese to English. The entrepreneurship education portfolio’s measurement items were created using Huang and Huang’s (2019) research. The items for measuring students’ entrepreneurial intent were based on the research of Li et al. (2020) and Lee and Herrmann (2021; Table A1, See Appendix 1).
Data Analysis
Following the work of Li et al. (2020) and Wang et al. (2023), we consider the approach of partial least square based structure equation model (PLS-SEM) due to the advantage of processing multiple independent variables at the same time, allowing us to overcome the constraints of multicollinearity between independent variables in the analysis of retrieved empirical data. The PLS method effectively tests the exploratory theory (Henseler et al., 2009), which does not require a normal data distribution and is suitable for small sample sizes compared to SEM based on variance-covariance (Fornell & Bookstein, 1982).
Empirical informed were analyzed utilizing confirmatory factor analysis (CFA) and structural equation models (SEM), with partial least squares (PLS) path models being the predominant approach. Mean variation extraction (AVE), composite reliability (CR), and Cronbach’s alpha were utilized to assess significance, factor loading values, and convergence validity. The validity of discrimination is evaluated using two criteria: the Heterotrait–Monotrait (HTMT) ratio and the AVE of each idea being greater than its squared correlation with other ideas (Fornell & Larcker, 1981). The bootstrapping technique was employed to validate the proposed research model and assess the interrelationships among all variables. Ultimately, the regulatory impact of culture is scrutinized through the implementation of multi-group analysis (MGA), with an initial examination of measurement invariance (MICOM).
Results
The Measurement Model: Reliability and Validity Assessments
When adopting the methodologies of other studies, it is imperative to take into account prevalent methodological fallacies (Alegre & Chiva, 2013; Ifinedo, 2011). Version 26 of SPSS was initially utilized to conduct the Harman experiments. The explanatory variance of the initial factor is calculated when the sum of all variables is less than 50% and there is no measurement error in the analysis. The eigenvalues of the first factor explain 41.569% of the variance in this research, which is below the threshold of 50% (Table 2). This suggests that the study is free from standard method bias.
Common Method Bias Test.
Regarding the content validity of the scales suggested in this article, each scale was constructed in consultation with pertinent scholarly works in order to ascertain the content validity of the measuring instrument (Cronbach, 1971). In addition, Boateng et al. (2018) suggest that the expert-advised scale constitutes a methodology. To further ensure the content validity of the measurement instrument, the scale utilized in this article was further discussed with professional experts regarding the core content of entrepreneurship education. We consider several options for students after graduation in light of their entrepreneurial intentions. Regarding family entrepreneurship, we consider whether the family members have prior entrepreneurial experience.
As stated previously, the convergence validity of the study model was evaluated according to the following criteria: (a) the factor load must exceed .5; (b) the CR value must exceed .6; and (c) the AVE value must exceed .5 (Chan et al., 2018; Chin, 1998; Yang & Su, 2017). Moreover, when employing Cronbach’s alpha to assess the internal consistency reliability of a scale, a threshold of .6 is deemed minimally acceptable (Cronbach, 1951; Nunnally & Bernstein, 1994; Yang & Su, 2017). The fact that the burden for each factor is greater than .5 and the AVE value is also greater than .5, as shown in Table 3, indicates that the convergence effect of the research model is favorable. Both Cronbach’s alpha and CR values exceeded .6 and .8, respectively, signifying that the internal consistency of the study model was attainable.
Factor Loading, Cronbach’s alpha, CR, AVE of Constructs.
Discriminant validity testing requires that each factor correspond to an individual dimension (Gómez-Ramirez et al., 2019). The correlation coefficient between the square root value of AVE and the latent configuration is used for comparison, and the square root value of AVE must be greater than the value of all potential configurations, according to Fornell and Larcker (1981). The correlation coefficient is calculated rather than the square root of AVE. According to Table 4, the square root values for all AVEs are greater than those for all potential ideas. Furthermore, all single-trait-to-monotrait ratios are less than one. Because all of the ideas in this study have been tested for validity and reliability, these two results show that the discriminant validity of the measurements is good, and the scale of this study is valid and reliable.
Fornell–Larcker Criterion.
The Structural Model
To evaluate the predictive capability of the structural model, the

The structural model.
Table 5 displays the validation results for the variables and puts the research hypotheses to the test. The findings were widely accepted. Entrepreneurship education practice accounted for 83% of students’ entrepreneurial intentions based on the
The
Multi-Group Analysis for Entrepreneurial Family Background
To investigate the moderating effect of family entrepreneurship background in the model, we divided the survey participants into entrepreneurial and non-entrepreneurial experiences based on whether relatives had entrepreneurial experience. The impact of family entrepreneurship background variables on students’ entrepreneurial intentions was discussed using relatives’ entrepreneurial experience as a binary variable, and the entrepreneurial intentions of students from various entrepreneurial family backgrounds were comprehended. Prior to examining the relationship between configurations, it is necessary to validate the hypothesis of measuring invariance for these two samples, which are drawn from different populations and have different characteristics (Sinkovics et al., 2016; Tarhini et al., 2015). This eliminates the possibility that the observed differences are the result of measurement model errors (Rialp-Criado, 2018). Consequently, in order to validate the measurement invariance suggested by Carranza et al. (2020), the composite model’s measurement invariance (MICOM) is established. MICOM is also capable of analyzing scalar invariance, composition invariance, and configuration invariance (equivalence of composite mean and variance; Sinkovics et al., 2016). Table 6 displays the results of configurational and compositional invariance, which demonstrate the measuring instrument’s partial invariance because the equality of the combinatorial means is not verified. The moderating effect of entrepreneurial family background on students’ entrepreneurial education and entrepreneurial intention, on the other hand, can be assessed (Lee et al., 2021). MGA is necessary for evaluating the conditioning effect in light of this information (Sinkovics et al., 2016).
Configural Invariance and Compositional Invariance.
The verification of the relationship between the hypothetical results of the further development of the background adjustment effect of household entrepreneurship is shown in Table 7. MGA findings generally support H2 (moderating effect of entrepreneurial family background). The group path coefficient demonstrated the difference between those with and without a family entrepreneurship background for the groups adjusted by family entrepreneurship background. In terms of EEP to SEI, Group 1’s pathway coefficient is .039 (βGroup1− βGroup2 = .039,
Causal Hypotheses Testing and Multi-Group Comparison Test Results for Culture.
Discussion
This study explores the relationship between entrepreneurship education and the entrepreneurial intentions of Chinese undergraduates through empirical analysis, with a particular focus on the moderating role of entrepreneurial family background. The findings indicate that entrepreneurship education has a significant positive impact on students’ entrepreneurial intentions, while entrepreneurial family background plays a crucial moderating role in this relationship.
Drawing on social cognitive theory, this study confirms the critical role of entrepreneurship education in shaping students’ entrepreneurial intentions. The results show that the four core components of entrepreneurship education have a significant positive impact on students’ entrepreneurial intentions. This finding aligns with the research of Santos et al. (2019) and Sarooghi et al. (2019), who also found that entrepreneurship education significantly enhances entrepreneurial intentions by improving students’ self-efficacy and perceived feasibility. Specifically, teaching content has the most significant influence, with a path coefficient of .767, followed by entrepreneurship practice (β = .832), teacher guidance (β = .897), and entrepreneurship competition (β = .900). This study further validates the importance of entrepreneurship education in fostering students’ entrepreneurial mindset and stimulating their entrepreneurial willingness (I. Anwar & Saleem, 2019; D. Boldureanu et al., 2020; Zhang & Chen, 2024).
However, not all studies agree on the positive relationship between entrepreneurship education and entrepreneurial intentions. For example, Oosterbeek et al. (2010) found that entrepreneurship education had little to no effect on students’ entrepreneurial intentions in their study of Dutch students. They argued that the lack of practical application and real-world relevance in the curriculum might explain this discrepancy. Similarly, Von Graevenitz et al. (2010) suggested that the impact of entrepreneurship education depends heavily on the quality of the program and the students’ prior exposure to entrepreneurial activities. These studies highlight the importance of contextual factors, such as curriculum design and students’ backgrounds, in determining the effectiveness of entrepreneurship education.
Additionally, the study finds that entrepreneurial family background significantly moderates the relationship between entrepreneurship education and entrepreneurial intentions. Students from entrepreneurial families show a greater increase in entrepreneurial intentions (β = .859) after receiving entrepreneurship education compared to their peers from non-entrepreneurial families (β = .820), with the difference being statistically significant (
Conclusion
This study provides a comprehensive analysis of the relationship between entrepreneurship education and entrepreneurial intentions among Chinese undergraduates, with a particular focus on the moderating role of family entrepreneurial background. By controlling for this variable, the research offers theoretical insights into how external factors influence the effectiveness of entrepreneurship education and provides practical guidance for designing targeted educational policies and curriculum strategies. Through a detailed examination of entrepreneurship education’s core components, including the teaching content, teacher guidance, entrepreneurship competition, and entrepreneurship practice, the study moves beyond treating entrepreneurship education as a broad, undifferentiated concept. This granular perspective, framed by social cognitive theory, emphasizes the importance of a well-structured and multi-faceted educational approach that mirrors real-world entrepreneurial dynamics. This contribution is particularly relevant in the Chinese socio-economic context, where entrepreneurship is increasingly promoted as a driver of innovation and economic growth.
Another significant contribution lies in the exploration of the interaction between family entrepreneurial background and educational programs. The study highlights that students with entrepreneurial family histories are more likely to develop entrepreneurial intentions due to their prior exposure to entrepreneurial resources and experiences (Kristova & Malach, 2017). This finding underscores the critical role of both educational and familial contexts in shaping entrepreneurial aspirations and suggests that entrepreneurship education is not experienced uniformly across student populations. Students from entrepreneurial families benefit from an existing knowledge base and support system, which strengthens their ability to translate educational experiences into entrepreneurial motivations. In contrast, those without such backgrounds may require additional resources and targeted interventions to foster similar outcomes. This insight calls for a more personalized and inclusive approach to entrepreneurship education that acknowledges and accommodates the diverse socio-cultural contexts of learners. By integrating these dimensions, educators can design more effective programs that support the development of entrepreneurial intentions across a broader and more diverse student body.
The study also offers important practical implications for multiple stakeholders, including higher education institutions, policymakers, educators, and industry partners. For higher education institutions, the findings highlight the need to design comprehensive and differentiated entrepreneurship curricula that combine theoretical knowledge with practical experience. Universities should develop personalized learning pathways that address the varying needs of students with and without entrepreneurial family backgrounds. For instance, students with prior exposure could benefit from advanced, practice-oriented modules, while others may require foundational courses and additional mentorship to bridge the experiential gap. Furthermore, interdisciplinary collaboration across academic departments can foster a broader set of entrepreneurial competencies, preparing students to navigate complex and dynamic entrepreneurial ecosystems. For policymakers, the study suggests the importance of supporting educational innovation through policies that encourage flexible, experiential, and context-specific entrepreneurship programs. Providing financial incentives for underrepresented groups and establishing public-private partnerships can ensure equitable access to high-quality entrepreneurship education. Policymakers should also implement mechanisms to evaluate the long-term effectiveness of these programs, ensuring that educational strategies evolve in response to socio-economic changes.
Educators, as direct facilitators of entrepreneurship education, can apply these insights by adopting holistic teaching approaches that integrate theoretical instruction with experiential learning. This includes incorporating practical experiences such as business simulations, entrepreneurship competitions, and industry-led projects that provide students with hands-on exposure to entrepreneurial processes. Differentiated teaching strategies, such as personalized case studies and modular learning formats, can further accommodate the diverse backgrounds and learning needs of students. Additionally, assessment methods should extend beyond traditional examinations to include project-based evaluations, business pitch competitions, and reflective practices that measure entrepreneurial competencies more comprehensively. Industry partners play a crucial role in bridging the gap between academic knowledge and real-world practice. Collaborating with universities to co-design curricula, offer mentorship, and provide early-stage funding for student ventures can enhance the practical relevance and impact of entrepreneurship education. Industry professionals can also contribute to knowledge transfer by participating in academic programs as guest speakers and mentors, sharing their insights into emerging entrepreneurial challenges and market demands.
Limitations and Future Research Directions
This study has several limitations that should be considered. First, it primarily focuses on Chinese undergraduates, which may limit the generalizability of the findings to students in other cultural or economic contexts. The impact of entrepreneurship education is likely to vary across countries with different entrepreneurial climates, educational structures, and economic conditions. Future studies could examine these variables in diverse regions to better understand how contextual factors shape entrepreneurial outcomes.
Second, the study concentrates on family entrepreneurial background as a moderating factor, primarily focusing on immediate family members. However, other influential factors, such as mentorship from non-family members, peer influence, or broader social networks, may also play a significant role in shaping students’ entrepreneurial intentions. Future research could broaden the scope of social influences to provide a more comprehensive understanding of the factors that impact entrepreneurial aspirations.
Finally, while this study dissects entrepreneurship education into core components like teaching content, guidance, competitions, and entrepreneurship practice, it may not fully capture the complexity of entrepreneurship education. Important factors such as mentorship, entrepreneurial mindset development, and networking opportunities were not considered in this analysis. Future studies could refine the model by incorporating these additional dimensions to offer a more holistic view of how entrepreneurship education influences entrepreneurial intentions.
