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Article

Are You Sure About Your Career? Predictors of Vocational Confidence in Engineering Students

by
Marina Sousa
1,*,
Alexandra R. Costa
1,2,
Leandro S. Almeida
3 and
Eunice Fontão
1
1
ISEP, Polytechnic of Porto, R. Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
2
CIETI, Polytechnic of Porto, R. Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
3
School of Psychology, University of Minho, Campus de Gualtar, Edifício 14, 4710-057 Braga, Portugal
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(7), 787; https://doi.org/10.3390/educsci15070787
Submission received: 15 May 2025 / Revised: 14 June 2025 / Accepted: 17 June 2025 / Published: 20 June 2025
(This article belongs to the Section STEM Education)
Versions Notes

Abstract

:
The increasing flexibility and rapid, profound changes in the labor market require employability skills from graduates, dem1anding greater attention from higher education institutions to training opportunities that foster the development of these skills among their students. Using a sample of 373 first-year engineering students, this study analyzed, through regression analysis, the impact of sociodemographic (gender, age), academic (work, program choice, average grade), and psychological (life satisfaction, perseverance of effort, consistency of interests) variables on students’ confidence in achieving their professional career project after completing their degree. The results indicate that women and younger students show lower levels of confidence in achieving their future vocational projects, as do students with lower academic performance and those with less consistency in their interests. These findings suggest the need for specialized support services for students, starting from the first year, in career development provided by higher education institutions.

1. Introduction

The labor market has undergone profound changes in recent decades, characterized by globalization, the flexibilization of work arrangements, and an increasingly rapid pace of change. In this context, the transition from higher education (HE) to the labor market has become less linear and predictable, turning into a longer, more complex, and uncertain process (Sousa et al., 2021). In response, higher education institutions (HEIs) are striving to develop strategies and foster skills in their students to facilitate this transition and enhance their employability (Monteiro et al., 2025).
In Portugal, as in the rest of the world, HE has undergone a process of massification because of political and social transformations aimed at democratizing education and expanding access to new populations (Costa et al., 2016; Valadas & Fragoso, 2022). This transformation reflects the broader international trend described by Trow (1973), who conceptualized the expansion of higher education as a transition from an elite system to a mass system, and subsequently to a universal one. More recent contributions have built upon Trow’s framework to analyze the global implications of this shift, including the challenges of equity, quality, and institutional differentiation in massified systems (Scott, 2019; Trow, 2007). However, despite these efforts, studies show that this goal has not always been achieved, as the democratization of access has not necessarily led to the desired equalization within society—that is, increased access has not been matched by equal success in academic achievement and graduation outcomes (Valadas & Fragoso, 2022). This new reality presents challenges not only for HEIs but also for students themselves, who must face the task of choosing their future career paths at an early stage. Experiencing difficulties and doubts during this decision-making process is referred to as career indecision (Penn & Lent, 2018). Throughout their academic journey, students, particularly engineering students, face significant pressure to achieve strong academic performance, as they perceive that their results may directly influence their levels of employability upon graduation (Chai et al., 2024).
The choice of one career over another can be influenced by a variety of factors, ranging from personal interests or goals to the desire to meet societal expectations, as well as the evaluation of opportunities and/or threats in the labor market (Chung et al., 2009; Priyashantha et al., 2023; Yepes Zuluaga, 2024). It is also shaped by one’s belief in self-efficacy and outcome expectations (Lent et al., 2002).
According to the Social Cognitive Career Theory (Lent & Brown, 2019; Lent et al., 2002), individuals build their interests and self-perceptions through interaction with their social contexts, particularly within the family and school environment. These interactions ultimately impact the development of their vocational interests, career exploration, decision-making, and career choices, as well as their persistence and success in educational pathways, well-being and satisfaction in academic and professional situations, and even their self-determination throughout life (Lent & Brown, 2013; D. Wang et al., 2022).
According to several authors, a significant number of students experience high levels of vocational indecision (Atitsogbe et al., 2024). For engineering students, this challenge can be even greater due to the diversity of specialization areas, the perceived differences in academic demands, and the social prestige associated with each of these fields (Shivy & Sullivan, 2005). Other factors that may influence career indecision include a lack of information about available career options or fear regarding the demands of the profession (Lent et al., 2002). Conversely, the perception of strong employability and confidence in achieving one’s career goals are key factors in fostering a sense of security when choosing a career path (de las Cuevas et al., 2022). Therefore, understanding the factors that influence the choice of a future career can help improve students’ adaptation to HE, reduce dropout rates, which tend to be high in engineering programs (Costa et al., 2016), and facilitate the transition to the labor market (Kulcsár et al., 2020).
The aim of this study is to analyze the predictors of confidence in the future achievement of career goals among first-year engineering students, considering variables such as gender, choice of degree program, employment status (whether they only study or both work and study), life satisfaction, perseverance of effort, and consistency of interests.

1.1. Sociodemographic Variables and Career Indecision

The literature on engineering education highlights the influence of gender on perceived confidence in the future achievement of a professional career project. Although women’s academic performance is equivalent to that of men, and in many cases even superior (Stoet & Geary, 2018), some studies show that women report lower levels of confidence in their abilities and their perceived likelihood of success in engineering-related professions (Marra et al., 2009; Tandrayen-Ragoobur & Gokulsing, 2022).
Many explanations have been proposed for these gender differences. Women appear to show a stronger inclination toward careers in the humanities, in contrast to men, who tend to pursue careers more frequently in the sciences (Tandrayen-Ragoobur & Gokulsing, 2022; N. Wang et al., 2023). In addition to this, other factors such as gender stereotypes negatively impact women and their interest in careers. Women tend to underestimate their mathematical abilities and report a lower sense of belonging and identity in STEM programs compared to men (Luo et al., 2021; Tandrayen-Ragoobur & Gokulsing, 2022; N. Wang et al., 2023).
However, other studies point in the opposite direction. Olmos-Gómez et al. (2021) conclude that there are no gender differences, although they found that a middle-to-high socioeconomic background positively influences students’ confidence levels. According to Esters (2007), career indecision may be influenced by age in addition to gender, with the study concluding that younger male students, particularly those in their first year of study, tend to be the most undecided.
Another factor that may influence the career decision-making process is work experience, that is, whether students are employed while attending HE.
Although Mansor and Rashid (2013) concluded that students exhibit very high levels of career indecision, they did not identify work experience, gender, or academic performance as factors influencing students’ career indecision. In turn, Yaghi and Alabed (2021) identified age and gender as variables that influence decision-making. However, employment status, that is, whether students work while studying, was not found to have an influence.
The present study aims to examine whether confidence in the achievement of a professional career project varies according to sociodemographic variables such as gender, age, working-student status, and choice of degree program.

1.2. Life Satisfaction and Career Indecision

Life satisfaction refers to an individual’s overall subjective evaluation of their own life, based on factors such as personal fulfillment, interpersonal relationships, and sense of purpose, reflecting their perceived general well-being (Parola & Felaco, 2024; Reppold et al., 2019). High levels of life satisfaction are associated with greater resilience, better emotional balance, and success in areas such as career development (Diener et al., 1985). Research has shown that the way students make career-related decisions is consistently associated with their adaptation to HE studies and their overall life satisfaction (Samson et al., 2021). According to (Atitsogbe et al., 2024), difficulties in career decision-making have a negative impact on students’ life satisfaction, suggesting that higher levels of indecision are associated with lower levels of life satisfaction.
The present study aims to investigate whether life satisfaction is associated with confidence in the achievement of a professional career project.

1.3. Consistency of Interests, Perseverance of Effort, and Career Indecision

Pursuing a long-term goal requires determination and the ability to persist in overcoming obstacles (Datu et al., 2017). This personal attribute, which reflects passion and perseverance for achieving long-term goals, was termed grit by (Duckworth et al., 2011). The authors identified two dimensions that characterize the grit trait: perseverance of effort, which refers to the tendency to remain committed and exert effort in the face of difficulties encountered while pursuing goals, and consistency of interests, referring to the ability to maintain focus and passion for a specific interest or goal over long periods of time.
Thus, grit is a personality trait that impacts individuals’ performance across various areas of their lives. In students, for example, grit not only enables them to stay focused on their goals but also to persist in their studies, even when they encounter failure. In this sense, grit is one of the variables that helps explain why some students achieve greater success than others with similar intellectual abilities (Noronha et al., 2024).
Research has shown positive associations between the grit trait and life satisfaction, with this relationship potentially being direct, mediated, or moderated by other variables (Ain et al., 2021; Khan & Khan, 2017; Noronha et al., 2024). Khan and Khan (2017) argue that individuals who remain focused on achieving their long-term goals and overcome the difficulties and obstacles they face are generally more satisfied with their lives and with themselves.
Regarding the dimensions of grit, some authors suggest that while perseverance of effort is related to the determination to achieve a previously defined goal, consistency of interests depends on how well that goal has been clearly defined and understood (Fite et al., 2017). It is also worth noting that individuals with well-defined interests tend to have a clearer sense of self and of their goals, which suggests a potential relationship with their level of confidence in achieving their future professional career projects.
The present study aims to examine this relationship, which has received little attention from researchers, to determine whether perseverance of effort and consistency of interests are associated with confidence in achieving a professional career project.
Accordingly, the research question guiding this study is the following: What sociodemographic, academic, and personality factors predict students’ level of confidence in achieving their professional career project?

2. Materials and Methods

This study employed a quantitative research design, using a questionnaire administered to students from various engineering programs at [blinded for peer-reviewed]. The sample was selected based on convenience criteria, prioritizing ease of access, availability, and willingness to participate among eligible respondents. Efforts were made to increase the heterogeneity of the sample by including students from a broad range of engineering programs, such as civil, electrical, computer, chemical, energy systems, mechanical, and industrial management engineering. The inclusion criteria for the study were being an undergraduate engineering student, attending the daytime program, and completing all the survey questions.
The questionnaire was completed by students online, after being invited to participate in the study during class. Participants were assured of informed consent, given the freedom to choose whether to participate, and guaranteed the anonymity of their responses. Data collection took place between March and May 2024.
The questionnaire was divided into four sections. The first section included sociodemographic questions, while the second and third sections incorporated assessment instruments previously validated with Portuguese university students: the Satisfaction with Life Scale and the Grit Scale. The fourth section consists of the item designed to assess the level of confidence in the future achievement of the professional career project.
A total of 384 responses were collected, of which 11 were excluded for not meeting the inclusion criteria. The data collected through the online platform were entered into an Excel database and subsequently transferred to IBM SPSS Statistics, version 29.0, where the statistical analysis was conducted.

2.1. Sociodemographic Questions

The sociodemographic questions included gender, age, degree program, and whether or not the student was employed while studying.

2.2. Satisfaction with Life Scale (SWLS)

This study used the Portuguese validated version of the Satisfaction with Life Scale (Diener et al., 1985). This instrument consists of five items, rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale is formed by 5 items: “In most ways my life is close to my ideal”, “The conditions of my life are excellent”, “I am satisfied with my life”, “So far, I have gotten the important things I want in life”, and “If I could live my life over, I would change almost nothing”.
The Portuguese version has been the subject of several validation studies (Laranjeira, 2009; Sancho et al., 2014; Silva et al., 2015), showing good indicators of validity (with the emergence of a single factor) and reliability of the results. In the present study, the analysis of the internal consistency of the items yielded a Cronbach’s alpha coefficient of 0.869 and a McDonald’s omega coefficient of 0.871.

2.3. Grit Scale

The Grit Assessment Scale (EAGrIt-LP) (Noronha & Almeida, 2022) consists of eight items, rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
The items on the scale are as follows: “I have my life goals defined for the coming years”, “My interests are stable”, “I have defined what I want to do with my life”, “Even if an important activity is difficult, I persist until I accomplish it”, “I maintain a consistent set of goals over time”, “I follow my plans, even when I face obstacles in carrying them out”, “When I start a task, I focus on completing it”, and “I persist in order to achieve my goals”. These eight items are evenly distributed across two positively correlated factors: persistence (or perseverance of effort) and consistency (or stability of interests). The scale’s development and validation studies demonstrated adequate validity and reliability coefficients (Noronha & Almeida, 2022). In the present study, for the four items of the interest consistency dimension, a Cronbach’s alpha coefficient of 0.873 and a McDonald’s omega coefficient of 0.877 were obtained. For the four items of the effort persistence dimension, a Cronbach’s alpha coefficient of 0.857 and a McDonald’s omega coefficient of 0.858 were obtained.

2.4. Level of Confidence in the Future Achievement of the Professional Career Project

Students’ level of confidence in their professional career projects is an indicator of vocational orientation, and its analysis provides insight into how students perceive their professional future. To assess the level of confidence in the future achievement of their professional career project (ProjCarr), students responded to the item “Regarding your professional career project” with answers rated on a 4-point Likert-type scale: 1—I am certain about what I will do after graduation, 2—I have some ideas about what I intend to do after graduation, 3—I am somewhat undecided about what to do after graduation, and 4—I am completely undecided about what I will do after graduation.

3. Results

3.1. Sample

This study is based on a sample of 373 engineering students from [blinded for peer-reviewed]. Most of the students are male, with ages primarily ranging between 18 and 21 years old. Students come from various engineering programs, with most enrolled in computer engineering (see Table 1).

3.2. Professional Career Project

As this study focuses on the relationship between a set of sociodemographic and psychological variables and students’ level of confidence in achieving their current professional career project, Table 2 presents the results by cross-tabulating this level of confidence with gender, degree program choice, and whether students work and study or only study. All these variables were dichotomized. Regarding gender, only 9 students did not identify with the binary system (male, female). Additionally, most students reported being enrolled in their first-choice program, which led us to group the remaining students into the “other” category. For the question of whether students had a paid job, including part-time work, the response was already dichotomized (yes, no). As for the level of confidence in achieving their professional career project (ProjCarr), students’ responses were distributed across the four provided levels, ranging from certainty to complete indecision.
As the results show, a higher proportion of male students fall into confidence levels 1 and 2 regarding their professional career, while the situation is reversed for levels 3 and 4, where a higher proportion of female students is observed. At the extreme ends of the scale, 13.9% of male students are in level 1 compared to 7.1% of female students, whereas 7.1% of males and 13.1% of females fall into level 4. This inversion in the gender distribution across the confidence levels is statistically significant (chi-square = 18.346, df = 3, p < 0.001), suggesting that the two variables are associated, with male students showing higher confidence in achieving their career project after graduation than female students.
A similar trend is observed with respect to whether students are enrolled in their first-choice degree program. Students attending a first-choice program tend to be proportionally more represented in confidence levels 1 and 2, while those not enrolled in a first-choice program are more represented in levels 3 and 4. However, statistical analysis of this discrepancy in proportions revealed that the difference is not statistically significant (chi-square = 4.271, df = 3, p = 0.234).
Finally, when comparing students who work and study with those who only study, a higher proportion of working students is found in confidence level 1, while a greater proportion of non-working students falls into levels 3 and 4. The two groups are proportionally similar at confidence level 2. These differences are particularly pronounced at the extreme ends of the confidence scale (total confidence and total uncertainty). Statistical analysis of this discrepancy across the four confidence levels revealed a significant difference (chi-square = 21.485, df = 3, p < 0.001). Based on this, we can infer that students who work tend to show greater confidence in achieving their career projects, whereas those who only study express greater uncertainty.

3.3. Satisfaction with Life and Grit

In Table 3, we present the results of cross-tabulating age, average grades in completed courses, life satisfaction, perseverance of effort, and consistency of interests with students’ level of confidence or uncertainty in achieving their professional career project after completing their academic studies. Given the quantitative nature of the variables, we present the mean values and standard deviation (the latter in parentheses).
Analyzing the results, we observe a decrease in the mean values of the five variables considered as we move from higher confidence levels to those with greater uncertainty regarding students’ achievement of their professional career projects after completing their degree.
It is also observed that there is generally greater variability in the results across the five variables, which is reflected in the standard deviation values when considering students in degree level 1 or those with higher certainty in achieving their career project.
By analyzing mean differences through one-way analysis of variance (F-Oneway), we find a statistically significant difference across the four groups of students based on their level of confidence or uncertainty in achieving their professional career project for the following variables: age (F(3, 369) = 11.368, p < 0.001, η2 = 0.085), average grades in completed courses (F(3, 337) = 3.490, p < 0.05, η2 = 0.030), life satisfaction (F(3, 369) = 4.812, p < 0.01, η2 = 0.038), perseverance of effort (F(3, 369) = 11.391, p < 0.001, η2 = 0.085), and consistency of interests (F(3, 369) = 42.185, p < 0.001, η2 = 0.255).
As we can observe, the differentiation among the four groups of students is minimal for the average grades and life satisfaction, but it is more pronounced in the other three variables, particularly in the consistency of interests.
Finally, when comparing the four groups of students in terms of the means for the analyzed variables (using the Bonferroni method in contrast analysis), we find that for age, the mean is higher and significantly different when comparing group 1 with groups 2, 3, and 4, which do not differ from each other.
For the average grades, the differences between the four groups of students are not statistically significant at any point. For life satisfaction, the mean of groups 1 and 2 is significantly higher than that of group 4. In perseverance of effort, groups 1 and 2 have significantly higher means when compared to groups 3 and 4. Finally, for consistency of interests, there is a statistically significant difference when comparing the four groups, with a progressive decrease in the mean as we move from group 1 to group 4 (1 > 2 > 3 > 4).
To conclude the statistical analyses, a linear regression analysis (enter method) was performed to assess the impact of personal (gender, age, working-student status), academic (degree program choice, average grades in courses), and psychological (life satisfaction, perseverance of effort, consistency of interests) variables on students’ level of certainty or uncertainty when evaluating the achievement of their professional career project after completing their degree. The model was statistically significant (F(8, 324) = 19.607, p < 0.001), explaining about 30% of the variance in students’ confidence in their future careers (R square = 0.328, adjusted R square = 0.310).
Table 4 summarizes the coefficients obtained in the regression analysis.
In line with the results obtained in Table 1 and Table 2, when analyzing potential differences between the four groups of students based on the personal, academic, and psychological variables considered in this study, a statistically significant impact of some variables on the differentiation of the four groups of students is observed.
These include gender, age, average grades, and consistency of interests (in the case of perseverance of effort, the t value is at the threshold of statistical significance, suggesting greater certainty about students’ future career projects when they exhibit higher perseverance of effort). Regarding gender, women tend to show more uncertainty about their future careers, as do younger students. At the same time, students with lower academic performance (lower average grades) also show greater uncertainty about their professional future.
Finally, considering the grit dimension identified as consistency of interests, a clear differentiation between the four groups of students is observed, suggesting that greater consistency of interests is associated with greater certainty about students’ career projects after completing their degree.

4. Discussion

Higher education no longer represents a prestigious status for a minority of the population. The increased demand for higher professional qualifications by the labor market and the democratization of society have generalized access to and enrollment in HE for a student population that is both larger and more socially heterogeneous. At this point, it is crucial that HEIs not only ensure access but also create conditions for the effective success of incoming students, meaning the completion of their programs and the development of employability skills and strategies that facilitate their entry into the labor market. This represents a significant challenge for institutions given the diversity of students in terms of skills, motivations, career projects, and levels of autonomy and self-regulation. It is therefore important for institutions to understand the key variables determining the academic success of their students in a broad sense and to implement measures in line with these insights.
In line with other research in the field, and specifically focusing on engineering programs, this study aimed to identify sociodemographic, academic, and psychological variables that may be associated with students’ vocational indecision, more specifically their level of certainty or uncertainty regarding their future professional career among first-year engineering students. The sample’s focus on first-year students aligns with research from various countries, which points to higher levels of academic failure and dropout rates among first-year students (Araújo, 2017).
The results of the regression analysis showed a statistically significant impact of some of the variables considered in the study on students’ vocational certainty/uncertainty levels, explaining just over 30% of the observed variance in the criterion variable (students’ vocational certainty/uncertainty regarding their future professional career). This convergence of variables aligns with Social Cognitive Career Theory (Lent & Brown, 2019; Lent et al., 2002), which emphasizes individuals’ interactions with their social contexts in the construction of their career projects through the development of interests, self-efficacy beliefs, and vocational choices. In terms of sociodemographic variables, differences were found in relation to gender and age. Specifically, women and younger students show greater uncertainty about their professional future. While it can be accepted that, as students gain experience and maturity, they clarify and commit to vocational projects in terms of their education and future professional practice (Esters, 2008); the greater vocational uncertainty among women justifies a more comprehensive analysis of contributing factors.
Women remain underrepresented in STEM programs, with their percentage increasing in courses related to biology and health, and decreasing in programs related to computer science, mathematics, and physics (Almeida et al., 2024; Vaarmets, 2018). On the other hand, even when performing academically at the same level as men (Stoet & Geary, 2018), women tend to report lower perceptions of competence and self-efficacy when enrolled in STEM courses (Marra et al., 2009; Tandrayen-Ragoobur & Gokulsing, 2022). These lower perceptions of competence and self-efficacy, given their relevance in vocational decision-making and the construction of academic and professional career paths (Lent & Brown, 2019; N. Wang et al., 2023), may help explain higher levels of uncertainty among women in pursuing vocational careers in the STEM field. Complementary to this perspective, Tandrayen-Ragoobur and Gokulsing (2022) and N. Wang et al. (2023), for example, note that women tend to show less interest in pursuing careers in science-related fields, are more likely to underestimate their abilities in mathematics, and are disproportionately affected by gender stereotypes that create unfavorable biases against them. In addition, Luo et al. (2021) highlight that women often report a lower sense of belonging and identity when enrolled in STEM programs.
Their education within the family and society may have directed them more towards professions in social relations and helping fields, and less towards working with data, objects, and equipment, which generates greater uncertainty among women enrolled in engineering programs regarding their professional futures. Women seem to be more influenced by family, teachers, and peers than men in their career choices, allowing the perpetuation of certain gender stereotypes in the selection of courses and professions (Speer, 2017; Zafar, 2012).
In terms of academic variables, it was found that students with better academic performance, here referring to their grades in courses, tend to have greater certainty regarding their future professional careers. This result, suggesting an early clarification of the career project among students with better academic performance, does not find support in the literature. However, it may be consistent with Social Cognitive Career Theory (Lent & Brown, 2013, 2019), which posits that academic and professional vocational trajectories are developed over time as individuals engage in vocational experiences and decision-making, gradually consolidating their interests and self-efficacy beliefs. As a result, they achieve higher levels of satisfaction and success in their performance, which in turn reinforces their ongoing career choices and projects (D. Wang et al., 2022). It is important to note, however, that some studies do not support this perspective. Mansor and Rashid (2013), for example, report not finding any influence of academic performance on career indecision.
Regarding the psychological variables, both dimensions of grit are associated with levels of certainty/uncertainty regarding future professional careers. In the case of perseverance of effort, the results were at the threshold of statistical significance; however, for consistency of interests, the association found was statistically significant. In this case, consistency of interests seems to be related to the degree of clarity and depth with which students have their goals defined and clarified, leading to greater certainty in achieving their future vocational projects (Fite et al., 2017). Students with well-defined interests are likely to have a clearer sense of self and their goals, showing greater confidence in achieving their future professional career projects.
Finally, these results can also be interpreted considering the model proposed by Trow (1973), in which higher education evolved from an elite system to a mass, and later, a universal system. This transformation did indeed broaden access, but it also introduced new challenges, such as promoting equity and the difficulty institutions face in addressing the diverse profiles of students. Scott (2019) argues that increased access does not necessarily translate into greater equality in academic outcomes or professional opportunities. In this sense, the differences observed in students’ confidence in achieving their career projects—particularly among those with lower academic performance or who work while studying—may reflect persistent inequalities, even within more inclusive systems.

4.1. Practical Implications

This study aimed to contribute to the literature on career development by analyzing how personal, academic, and psychological variables influence students’ perceptions of their future professional careers. Using a sample of engineering students, the results pointed to higher levels of confidence in the achievement of future vocational projects among male students, working students, those with better academic performance, and students with greater consistency in their interests. Since it is the objective of HEIs to create opportunities for career development and future employability for all their students, it is important that institutions have monitoring plans and support and/or counseling services in place, focused on promoting the clarification of career goals. In accordance with Social Cognitive Career Theory, institutions should foster environments and provide opportunities that enable students to engage in exploration, make and experience decisions, confront barriers, solidify vocational interests and self-efficacy beliefs, and ultimately promote academic success and satisfaction. These career development and/or personal development actions should accompany students throughout their entire academic journey, including the first year of study.

4.2. Limitations and Suggestions for Future Research

This study has some limitations that should be acknowledged to guide future research. The sample was obtained through convenience sampling, with students from a single institution, all enrolled in engineering programs, which may limit the comparability and generalizability of the results, even though the sample size is reasonably large. Additionally, the assessment of confidence in achieving the future career project relied on a single item, and it would be beneficial in the future to use a scale to ensure a more consistent evaluation of this construct. Finally, it would be worth considering the inclusion of other psychological variables related to the professional career project, such as self-efficacy, intrinsic motivation, or self-determination.

Author Contributions

Conceptualization, M.S., A.R.C. and L.S.A.; methodology, M.S., A.R.C. and L.S.A.; software, M.S. and L.S.A.; validation, M.S., A.R.C. and L.S.A.; formal analysis, M.S.; investigation, M.S., E.F. and A.R.C.; resources, M.S.; data curation, M.S.; writing—original draft preparation, M.S., A.R.C. and L.S.A.; writing—review and editing, E.F.; visualization, E.F.; supervision, M.S.; project administration, L.S.A.; funding acquisition, M.S., A.R.C. and L.S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The data for this study were gathered through a questionnaire designed to respect the privacy of all participants. Responses were fully anonymized, and no information that could directly or indirectly identify individuals was collected. Consequently, it was not possible to link any data back to specific participants. Throughout the research process, we took great care to uphold ethical standards and to ensure that participants’ privacy, confidentiality, and autonomy were fully respected.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is available upon request from the first author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
HEIHigher Education Institution
HEHigher Education

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Table 1. The characterization of the sample (N = 373), in percentages.
Table 1. The characterization of the sample (N = 373), in percentages.
GenderMale75.1
Female22.5
Not specified2.4
Age18–1951.5
20–2130.0
over 2218.5
Bachelor’s degree programsSystems Engineering5.6
Computer Engineering70.0
Civil Engineering15.5
Other Engineering8.9
Working studentYes22.3
No77.7
Table 2. Cross-tabulation of dichotomized personal variables and confidence in achieving the professional career project.
Table 2. Cross-tabulation of dichotomized personal variables and confidence in achieving the professional career project.
Variables ProjCarr1ProjCarr2ProjCarr3ProjCarr4
GenderMale39 (13.9%)182 (65.0%)39 (13.9%)20 (7.1%)
Female6 (7.1%)41 (48.8%)26 (31.0%)11 (13.1%)
Program Choice1st choice43 (13.3%)201 (62.0%)56 (17.3%)24 (7.4%)
Other4 (8.2%)27 (55.1%)11 (22.4%)7 (14.3%)
WorkYes21 (25,3%)50 (60.2%)11 (13.3%)1 (1.2%)
No26 (9.0%)176 (61.4%)56 (19.3%)30 (10.3%)
Table 3. Cross-tabulation of quantitative personal variables and confidence in achieving the professional career project.
Table 3. Cross-tabulation of quantitative personal variables and confidence in achieving the professional career project.
VariablesProjCarr1ProjCarr2ProjCarr3ProjCarr4
Age (years)24.45 (8.87)20.50 (3.72)20.03 (3.73)19.65 (2.32)
Average grade14.45 (1.88)14.11 (1.60)13.65 (1.31)13.47 (1.27)
Satisfaction with life18.53 (5.60)18.40 (4.27)17.25 (4.51)15.39 (4.81)
Perseverance of effort16.72 (2.99)16.54 (2.46)14.87 (3.22)14.32 (3.49)
Consistency of interests16.81 (3.16)15.56 (2.74)12.75 (3.36)10.81 (3.11)
Table 4. Regression analysis coefficients.
Table 4. Regression analysis coefficients.
VariablesBErrorBetatSignif
(Constant)5.1490.563 9.146<0.001
Gender−0.2200.081−0.126−2.7230.007
Age−0.0240.009−0.148−2.7170.007
Work0.0980.1020.0530.9660.335
Program choice−0.0170.105−0.008−0.1610.872
Average grade−0.0630.022−0.131−2.8210.005
Satisfaction with life−0.0090.009−0.055−1.0380.300
Perseverance of effort0.0330.0170.1211.9570.051
Consistency of interests−0.1130.014−0.513−8.107<0.001
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Sousa, M.; Costa, A.R.; Almeida, L.S.; Fontão, E. Are You Sure About Your Career? Predictors of Vocational Confidence in Engineering Students. Educ. Sci. 2025, 15, 787. https://doi.org/10.3390/educsci15070787

AMA Style

Sousa M, Costa AR, Almeida LS, Fontão E. Are You Sure About Your Career? Predictors of Vocational Confidence in Engineering Students. Education Sciences. 2025; 15(7):787. https://doi.org/10.3390/educsci15070787

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Sousa, Marina, Alexandra R. Costa, Leandro S. Almeida, and Eunice Fontão. 2025. "Are You Sure About Your Career? Predictors of Vocational Confidence in Engineering Students" Education Sciences 15, no. 7: 787. https://doi.org/10.3390/educsci15070787

APA Style

Sousa, M., Costa, A. R., Almeida, L. S., & Fontão, E. (2025). Are You Sure About Your Career? Predictors of Vocational Confidence in Engineering Students. Education Sciences, 15(7), 787. https://doi.org/10.3390/educsci15070787

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