Entrepreneurship education has emerged as a critical component in the development of human capital, particularly within TVET colleges (Kuratko & Morris 2018; Ndou 2021). These institutions play a vital role in equipping students with the skills and knowledge necessary to thrive in an increasingly competitive and dynamic economy (Winberg & Nomgauza 2023). The focus on entrepreneurship education within TVET colleges is driven by the recognition that fostering entrepreneurial competencies is essential not only for individual career success but also for broader economic development (Linton & Xu 2021; Martin, McNally & Kay 2013). This literature review explores the theoretical underpinnings of entrepreneurship education through the lens of the human capital theory (HCT) and examines its practical implications within the context of TVET institutions.

This study is significant as it examines the role of entrepreneurship education in fostering human capital by enhancing students’ capability to identify and capitalise on business opportunities. Literature highlights opportunity recognition and exploitation as essential components of entrepreneurial success. Although TVET colleges globally are integrating these concepts into their curricula, the effectiveness of such educational initiatives remains a subject of debate, particularly in resource-limited environments such as South Africa. Through a critical analysis of existing research, this review seeks to provide a comprehensive understanding of how entrepreneurship education influences the entrepreneurial mindset of TVET students and the challenges that impede its effective implementation.

One of the foundational theories that explains the role of entrepreneurship education is the HCT. This theory suggests that individuals accumulate valuable skills, knowledge and abilities through education and training, which, in turn, enhance their productivity and economic potential (Becker 2009; Linton & Xu 2021). Within the context of entrepreneurship education, the theory posits that the development of entrepreneurial skills – such as opportunity recognition, risk management and innovation – contributes to the formation of human capital, which is critical for successful business ventures. Entrepreneurship education provided by TVET colleges plays a crucial role in developing students’ human capital by equipping them with the essential knowledge and skills needed to recognise and capitalise on business opportunities within their respective industries. The link between entrepreneurship education and human capital development is particularly important in developing economies, where young people often lack the skills needed to enter the labour market or start their own businesses. Within the context of this study, the HCT highlights the role of education in building the skills and knowledge needed for business success.

Entrepreneurship education has become an essential part of the curriculum in TVET colleges worldwide, aiming to equip students with the skills necessary to thrive in a competitive and dynamic economy. Within these institutions, entrepreneurship education focusses on nurturing an entrepreneurial mindset, fostering innovation and building the capacity to recognise and exploit business opportunities (Kuratko & Morris 2018; Linton & Xu 2021). It plays a pivotal role in bridging the gap between vocational skills and business acumen, preparing students to either start their own businesses or apply entrepreneurial thinking in existing organisations (Kuratko 2020; Ndou 2021). The design of entrepreneurship education in TVET institutions typically integrates both theoretical and practical learning. Theoretical components cover fundamental business concepts such as finance, marketing and strategic planning. On the other hand, practical elements – such as simulations, internships and hands-on projects – allow students to engage with real-world business scenarios, enhancing their problem-solving and decision-making capabilities (Jones, Penaluna & Matlay 2019; Sibanda & Naidoo 2023). This blend of theory and practice is critical for developing the entrepreneurial competencies that students need to navigate the challenges of starting and managing a business.

Despite the efforts of integrating theory and practice, several challenges continue to hinder the effective implementation of entrepreneurship education within TVET institutions, particularly in South Africa. One of the primary challenges is resource constraints. Many TVET institutions operate under tight budgets, limiting their ability to offer comprehensive entrepreneurship programmes that include the necessary tools and resources for practical learning (Nkondo & Motsepe 2021; Sibanda & Naidoo 2023). This lack of resources often affects the quality of education, especially in terms of providing access to technology and real-world business experiences.

Opportunity recognition involves an individual’s capacity to determine, uncover or formulate patterns and ideas. Research indicates that this cognitive phenomenon plays a role in an individual’s decision-making process in entrepreneurship (Hassan et al. 2020). Manesh and Rialp-Criado (2019) found, in their study, that entrepreneurship education strengthens the impact of opportunity recognition on entrepreneurial intention. According to Shane and Venkataraman (2000), opportunity recognition is a core focus of entrepreneurship research, as the entrepreneurial journey begins with identifying a potential business idea that can be explored and transformed into a new product, service or process. Consequently, the idea of opportunity recognition has become a key concept in entrepreneurship studies (Filser et al. 2023; Hoang et al. 2022; Khanin et al. 2022).

Once an opportunity is recognised, the next crucial step is opportunity exploitation, which involves taking action to realise the identified potential. The transition from recognition to action is a complex process that includes decision-making, resource allocation and risk management (Kuckertz et al. 2017; Linton & Xu 2021). Opportunity exploitation refers to the capacity to improve, extend and apply the existing organisational processes and routines, competencies and technology to create new or improved products or services, as needed by the market (Zobel 2017). Opportunity exploitation facilitates knowledge acquisition and enables acting upon the knowledge to produce tangible results. Ultimately, opportunity exploitation entails enabling implementation, applying assimilated capabilities and combining resources to unlock commercial potential (Mathafena & Msimango-Galawe 2023).

Based on insights from the literature review, the following hypotheses are proposed. The conceptual model for the study is illustrated in Figure 1.

Entrepreneurship education plays a fundamental role in enhancing individuals’ ability to recognise and capitalise on business opportunities (Othman et al. 2020b). By imparting essential knowledge and fostering critical skills, such programmes equip students with the tools necessary to identify viable market gaps and innovative solutions (Adejoke 2025; Sarkar & Jena 2022). Nabi et al. (2017) found that entrepreneurship education positively influences students’ entrepreneurial intentions and their capacity for opportunity identification. Similarly, Guo et al. (2017) indicates that opportunity recognition significantly mediates the relationship between entrepreneurial orientation and performance of small and medium-sized enterprises. These findings suggest that structured educational interventions in entrepreneurship can effectively cultivate an opportunity-oriented mindset, thereby facilitating the successful launch and sustainability of new ventures. Hence, the following hypothesis is formulated:

The contribution of entrepreneurship education has been identified to prepare individuals with the necessary skills and knowledge to identify and exploit business opportunities effectively (Boldureanu et al. 2020; Sánchez 2013). Through nurturing an entrepreneurial mindset, such education enhances one’s ability to recognise potential ventures and navigate the complexities of starting and managing a business (Kuckertz et al. 2017). Experiential learning approaches within entrepreneurship education have been shown to significantly improve opportunity identification and exploitation capabilities (Corbett 2005). Moreover, the development of self-regulation and decision-making heuristics through targeted education further facilitates the successful exploitation of identified opportunities (Bryant 2007). Based on the assertion, the following hypothesis is proposed:

The study population consisted of 240 students from the Vuselela TVET college, on the three campuses offering business studies programmes. The study was conducted using a sample of students studying Business Management and Marketing Management at the N5 and N6 levels of study. Students doing N4 were excluded because they do not have Business Management and Marketing Management background. The sample size included students registered for full-time and part-time studies.

A non-probability sampling method, that is the convenience sampling technique, was used to collect the cross-sectional data. The questionnaires were distributed to the students by the researchers during class time at the three campuses of Vuselela TVET college. Out of the total of 240 questionnaires distributed to students, 151 questionnaires were completed and used for data analysis.

The study used valid measurement items previously employed in entrepreneurship studies. The measurement items were adopted from the previous studies on entrepreneurship education, opportunity recognition and opportunity exploitation. Questionnaires were distributed to the students during class time at the three campuses offering Business Studies. The process of data collection was administered by the researchers involved in the study. All the completed questionnaires were captured in MS Excel and later imported to Statistical Package for the Social Sciences (SPSS) (IBM Corp., Armonk, NY, United States) and SmartPLS (SmartPLS GmbH, Bönningstedt, Germany) for processing. Confirmatory factor analysis (CFA) was used to ensure the reliability and validity of all the constructs and structural equation modelling (SEM) was used to test the proposed hypotheses.

Ethical approval to conduct this study was obtained from the University of Johannesburg School Research Ethics Committee (JBSREC) (No. JBSREC2024194). In addition, the Principal of Vuselela TVET college granted permission to the researchers to conduct the study at the college. Respondents were comprehensively briefed on the study’s purpose, the voluntary nature of their participation and their right to withdraw at any point without any repercussions. Prior to data collection, informed consent was obtained from each participant. The consent form clearly detailed the study’s objectives, methodology and potential benefits. Confidentiality and anonymity were rigorously upheld throughout the research process. Access to the data was restricted exclusively to the research team, with all data securely stored and utilised solely for the purposes of this study. To further safeguard participants’ privacy, all responses were aggregated and findings were reported in a manner that ensured individual participants could not be identified.

Table 1 presents the demographic breakdown of the data collected in the study. Demographic information was gathered from 151 participants using a structured questionnaire, which included details regarding campus location, age, gender, race, level of study and course of enrolment. Among the respondents, 58.3% were from the Klerksdorp Campus. In terms of age, most respondents (70.2%) fell within the 21–30 years age range. The gender distribution comprised 68.2% females (103 respondents). The racial proportion is 90.1% black people, 8.6% Coloured people, and 0.7% white people and Indian people. Regarding the level of study, 67.5% were enrolled in the N5 level. In addition, most participants (78.8%) were enrolled in Business Management courses.

The reliability and validity of the measurement tools were assessed using Cronbach’s alpha, composite reliability (CR) and average variance extracted (AVE) (Fornell & Larcker 1981; Hair et al. 2010). Reliability refers to the internal consistency of a group of questions intended to measure a particular variable. An acceptable level of reliability is indicated by alpha and CR values of 0.7 or higher and an AVE of at least 0.5 (Hair et al. 2010). The results of the reliability analysis for this study are presented in Table 2. Convergent validity evaluates how well a set of questions accurately measures the intended variable (Hair et al. 2010). Satisfactory convergent validity and internal consistency are demonstrated by factor loadings of 0.5 or above, CR values of 0.7 or higher and an AVE of at least 0.5 (Fornell & Larcker 1981).

Discriminant validity is established when the square root of AVE for a construct exceeds its correlation with all other constructs, as per the criteria established by Ab Hamid, Sami and Sidek (2017) and Fornell and Larcker (1981). The square root of AVE (in bold and italics) for one construct (EE) was found to be greater than its correlation with another construct in this investigation (Table 3), consequently providing substantial support for discriminant validity.

The SEM model fit’s acceptability was evaluated using SmartPLS statistics, which included the standardised root mean residual (SRMR) and the normed fit index (NFI), as well as the global fit index from this study. Using the formula provided by Henseler, Ringle and Sarstedt (2015), the global goodness-of-fit (GoF) statistic for the research model was computed:

The global GoF was determined to be 0.381, which surpasses the Khojasteh and Lo (2015) threshold of GoF > 0.36. This investigation concludes that the research model’s latent variable relationship is robust, suggesting a satisfactory overall fit.

The variation between the observed correlation and the model’s implied correlation matrix is the SRMR. In SmartPLS 4, standard bootstrapping was used. The average difference between observed and predicted correlation is a comprehensive model fit criterion. The NFI is 1 minus the null model Chi-squared. A closer NFI value near 1 indicates better alignment. Hair and Alamer (2022) recommend SRMR and NFI indices of more than 0.90 or less than 0.08. In this study, SRMR and NFI were 0.078 and 0.760, respectively (Table 4). The conceptual model for this study would have fit better with an NFI of 0.90, because the SRMR and global fit were good.

Q-squared (Q²) was implemented in this investigation to evaluate the predictive relevance of a model. When Q² exceeds 0, a model is considered predictively relevant. Therefore, Q² > 0 is thought to be favourable. In addition, the predictive relevance of endogenous constructs is established by Q². The presence of Q² values above zero suggests that the model has predictive relevance and that the values have been accurately reconstructed. The Q² for the latent and endogenous variables, OE and OR, in this study is 0.061 and 0.438, respectively, as indicated by the results in Table 5. This study model has significant predictive power and relevance, as these values are substantially above zero.

As the evaluation of the measurement model met the entire criterion, the structural model was then evaluated. In order to achieve this, a path analysis was implemented. Path coefficients were computed for each hypothesis that was proposed, and bootstrapping was employed to generate t-statistics and p-values for the purpose of evaluating the significance level. The theoretical foundations of the study and the significance of the relationship between model constructs were demonstrated and evaluated by this SEM procedure. The p-values and regression coefficients of the study were analysed to assess the structural model. The structural model’s outcome for the proposed hypothesis is illustrated in Figure 2.

Path analysis examined the causal relationship between latent variables after evaluating and finalising the measurement and structural models (Hancock, Stapleton & Mueller 2018). Clark and Watson (2019) contend that SEM asserts that specific latent variables have a direct or indirect impact on other variables in the model, as per Nusair and Hua (2010). This results in estimation results that demonstrate the relationship between these latent variables. The estimation results from hypothesis testing for this investigation are presented in Table 6. The table shows the path coefficients, t-statistics and proposed hypothesis, as well as whether the hypothesis is supported or rejected. According to the literature, a significant relationship is indicated by a t-value of greater than 1.96, and a robust relationship between latent variables is indicated by path coefficients greater than one (Zhang 2022).

Two hypotheses were formulated to resolve the research questions in accordance with the findings in Table 6. All hypotheses (H1 and H2) were statistically supported and found to be significant (p = 0.05, t > 196) based on the positive or negative effect of the relationship.

This section presents a discussion of the results extracted from hypothesis testing.

The selected TVET college was evaluated in terms of the relationship between entrepreneurship education and opportunity recognition. The findings suggest that entrepreneurship education has a beneficial impact on the recognition of opportunities. Furthermore, the findings indicate that the correlation between opportunity recognition and entrepreneurship education is robust and significant (β = 0.674, t = 12.545, p = 0.000). The hypothesis was corroborated by the results, which indicated a positive correlation. This suggests that the recognition of opportunities is significantly influenced by entrepreneurship education. Supporting the hypothesis, research conducted by Otache et al. (2024) also demonstrated that entrepreneurship education has a positive and significant impact on opportunity recognition. Their findings corroborate the results of the earlier correlation analysis:

Opportunity exploitation was evaluated concerning entrepreneurship education. The findings suggested that entrepreneurship education has a positive and significant impact on opportunity exploitation (β = 0.277; t = 3.938; p = 0.000). This suggests that there is a moderate correlation between entrepreneurship education and opportunity exploitation in the selected TVET college. This indicates that the hypothesis is significant and well-supported. In support of this finding, research by Othmanet et al. (2020a) demonstrated that entrepreneurship education positively influenced students’ actions in exploiting business opportunities. This highlights the fact that providing individuals with diverse experiences and knowledge can enhance their capacity to capitalise on entrepreneurial opportunities.

Most of the studies on entrepreneurship education have been conducted within the context of universities, with an emphasis on entrepreneurial intentions, entrepreneurial self-efficacy, entrepreneurial behaviour and other entrepreneurial outcomes. The significance of this study is examining the influence of entrepreneurship education on opportunity recognition and exploitation in the setting of a TVET college. A few studies on entrepreneurship education have been conducted within the TVET college environment.

The first limitation of this study is that it was conducted with a small sample size (n = 151) of students from a single TVET college. The second limitation is that the study focussed solely on students enrolled in business management and marketing management programmes, excluding those from other academic backgrounds. The last limitation is the reliance on quantitative methods for data collection, whereas the use of qualitative or mixed methods could provide an in-depth analysis of entrepreneurship education offered in the college.

This study presents several implications for both theory and practice. It has been demonstrated that entrepreneurship education improves the ability to recognise and exploit opportunities. Based on the findings, it is recommended that entrepreneurship education be made a compulsory subject across all programmes in the TVET college sector. This approach would ensure equal access for all students to gain the skills and exposure offered by entrepreneurship education. This provides a chance for future research to increase the sample size and involve a broader range of TVET colleges. Upcoming studies should also incorporate students from disciplines outside of business and management. In addition, future research could explore the impact of entrepreneurship education on various entrepreneurial outcomes within TVET colleges. Alternative research methods could be employed to gain a deeper understanding of entrepreneurship education. A comparative analysis between students from business and non-business backgrounds could be conducted as well. Furthermore, future studies might consider examining the moderating effects of age and gender.