Engineers’ self-perceived employability by gender and age: Implications for higher education

Abstract Due to the multiple barriers that prevent women from pursuing Science, Technology, Engineering, and Mathematics (STEM) careers, there is a persistent gender gap in these fields in many countries around the globe. Considering this, the purpose of this study was to compare the self-perceived employability among men and women, as well as to understand how it changes depending on age and employment status. For such purpose, an online questionnaire was administered to 505 senior students and recent graduates from five engineering programs offered by a higher education institution in Colombia. The relationships between the variables were examined using Pearson’s correlation test, data on women and men were compared using the t- Student test, and the interaction between gender and age was analyzed via factorial analysis of variance. According to the results, men had different and higher means than women, but these differences were not statistically significant. In terms of gender, the largest effect size was reported for the career resilience and optimism at work skills. Regarding employment status, employed respondents had different and higher means than unemployed respondents, and these differences were found to be statistically significant. These ground-breaking findings may help universities, organizations, and governments in the development of policies and strategies to draw and keep women in STEM careers. Importantly, it is imperative to focus on women’s career transition and advancement because their employability skills are just as strong as men’s, but they are less confident and less likely to achieve their career goals.


Introduction
The current global context demands professionals with skills in Industry 4.0 technologies, which are mainly taught in Science, Technology, Engineering and Mathematics (STEM) study programs (Christie et al., 2017).However, STEM fields have been mostly male-dominated.Despite recent progress in gender equality in the different spheres of life, gender inequality in higher education (HE) remains a worldwide issue, particularly in the engineering sector (UNESCO -IESALC, 2021).Although it seems to be decreasing, this is a persisting problem around the globe.For instance, in the US-where women represent 50% of the population-only 25% of the students in STEM higher education are women.According to UNESCO, 30% of the students who go to college around the world are women (Puccini Martinez, 2022).In Colombia-where women are 52% of the population -the number of female graduates from STEM higher education doubled between 2001 and 2021.Nevertheless, only 25% of the approximately 13,000 engineering graduates in Colombia are women.The engineering programs that present the greatest gender inequity by graduates are civil engineering with 46.65%, followed by computer engineering with 26.09%, electronic and telecommunications engineering with 17.44%, mechanical engineering with 13.20% and electrical engineering with 9.94% (El Espectador, 2022).Considering the rapid advances in science and technology, this gender disparity has a negative impact on the gap between the supply and demand for professionals to keep pace with the Information and Communications Technology (ICT) industry (Bennett & Ananthram, 2021).This is especially true in developing countries such as Colombia.
Various studies have been conducted to investigate the factors that influence individuals' choice of an engineering career when entering university.For instance, in their analysis, Álvarez-Aguilar et al. (2019) reported that family was the most influential factor, followed by the university's reputation and status.They, however, found that the graduate profile and the courses in the curriculum were the most motivating factors for women who chose engineering careers.
Likewise, there are several reasons why women do not pursue engineering careers, including social aspects (e.g., stereotypes, biases and social prejudices), the difficulty of the field of study and the courses (e.g., mathematics and physics), and personal issues (e.g., lack of self-confidence, fear, and low self-esteem).For example, engineering or the so-called "tough" careers are thought to be for men because the same gender stereotypes operate in the labor market.Also, it is believed that the service sector requires social skills, which are considered feminine, such as emotional labor or communication skills (UNESCO -IESALC, 2021).
Additionally, it is concerning that although, following graduation, women are expected to take graduate courses, engage in research, and occupy positions with competitive and similar pay to those of men, they often end up getting lower-status and less-paying jobs.Hence, for recent graduates-especially women-to find a job amid the current economic difficulties caused by the COVID-19 recession, it becomes imperative to complement their hard skills with a set of generic skills for employability.
Several studies have investigated students', graduates', and employers' perceptions of employability skills (Magdalene, 2015;McKinsey & Company, 2021).That research has provided key information about the kind of competencies that are necessary in the education of engineering students and graduates (Sandí et al., 2022).However, this topic has not received enough attention.Further research should examine students' and graduates' assessment of their own capacity to successfully complete their programs and have a successful transition into the labor market.Therefore, this study analyzed the self-perceived employability of 505 engineering students enrolled at Instituto Tecnológico Metropolitano (ITM), a public university institution of the Municipality of Medellín (Colombia).

Employability in higher education
In the context of higher education, the concept of employability first appeared in the 1997 Dearing Report to justify the need to include other skills besides cognitive knowledge in all curricula to ensure greater job performance (Orellana, 2018).Quality assurance and results in universities, however, have been associated with pragmatic measures.For instance, employability is measured based on the employment rates of recent graduates and regarded as an institutional achievement rather than an individual result of a student who got a job.Clearly, few definitions describe employability as being equipped for a job, and many others prioritize the fact of getting a job because it is easier to measure.Yet, in doing so, they are only measuring institutional efficiency and leaving graduate employability aside (Harvey, 2001).Table 1 shows the definitions of employability.
Since employability is influenced by an individual's experiences, context, and labor market, it is open to subjective interpretation.In this regard, Hillage and Pollard (1998) presented an employability framework that emphasizes the various elements that interact within the concept of employability: assets, presentation, deployment, and external factors.Assets include personal attributes and basic traits (e.g., reliability and honesty); specific, generic, and key skills (e.g., communication and problem solving); and high-level skills (e.g., teamwork and business awareness).Presentation is defined as individuals' ability to arrange an appointment for an appropriate position by demonstrating their employability assets.Deployment refers to a variety of skills, including career management skills (e.g., awareness of one's own strengths and limitations and opportunities in the labor market, as well as decision-making and transition skills) and job search skills.Finally, external factors are the elements associated with the context, such as local labor market demand or work-related personal situations.
In this study, dispositional employability was used as a guideline.According to (Fugate & Kinicki, 2008), dispositional employability is "a constellation of individual differences that predispose employees to (pro)actively adapt to their work and career environments" (p.20).In other words, it captures the individual characteristics that foster adaptive behaviors and positive work outcomes, making it easier for employees to seek and take advantage of career opportunities within and outside an organization.The disposition of employability encompasses proactive individual characteristics, such as adaptation and willingness to change, which help individuals to prepare ahead of time for these changes rather than waiting for them to occur abruptly.There are, however, prerequisites for workplace adaptation, including those individual differences that promote active adaptability (e.g., optimism), adaptive schemes or a cognitive component, and the ability to learn and change to meet demands (Ashford & Taylor, 1990).Table 2 shows the operationalization of employability.

Gender, age and employability
In their study, McQuaid and Lindsay (2005) identified several factors (individual, personal, and external) as being related to employability.Although gender is a demographic variable, it should be considered one of the most influential factors in the development of employability skills and certain transferable abilities.Despite its importance and consequences on higher education programs, this factor is absent in most curricular discussions.As a result, these simplistic discussions ignore the influence of multiple sociocultural factors (e.g., gender, ethnicity, and social class) on the development and efficacy of employability (Gracia, 2009).
Although there are universal factors that condition the gender gap in STEM higher education, specific cultural patterns marked by social stereotypes, biases, and gender roles depend, to a great

Author(s) Definition
Harvey ( 2001) "The propensity of the graduate to exhibit attributes that employers anticipate will be necessary for the future effective functioning of their organization" (p.100) Thijssen (1997) An individual's skills to effectively perform in the world of work.Knight and Yorke (2002) Set of accomplishments (skills, knowledge, and personal traits) that provide graduates with the best conditions to find a job and succeed in the various vocations they may choose, with benefits for themselves, as well as for the labor market, the community, and the economy.
Enríquez and Rentería (2007) Alternative explanation for everything that enables individuals to enter or remain in the workforce.
extent, on each local culture.Then, the gap gender is not the same across all geographic regions worldwide (Verdugo-Castro et al., 2022).In the US, women typically have restricted access to quality education, especially in STEM areas, among other disciplines (Sharma, 2023).The number of women in STEM careers is still extremely low, despite the great potential of these fields.As a matter of fact, from the moment STEM subjects are chosen, the number of women studying these subjects declines progressively, with a high dropout rate.
The same holds true in the subsequent transition from education into employment (Herman, 2015).In terms of job characteristics, there exist gender differences in employment opportunities across all sectors (ILO, 2016), with issues such as salary, mobility, self-employment, and access to leadership roles having unfavorable outcomes for women (Monteiro et al., 2022).
In STEM industries, gender also plays a key role in employability because most organizations seek employees capable of adjusting to constant changes, traveling abroad, and working long hours, which is challenging for women who are mothers and wives.This is even truer when they stop working to care for their children in their first years, as their résumé and skills get out of date, and when they decide to return to work, they are offered less-skilled occupations (Jenkins, 2006).
In employability analyses, age is also employed as a covariate.According to studies in the field, age discrimination in the workplace is a contentious issue, especially at older ages (Froehlich et al., 2015;Rothwell & Arnold, 2007;Van der Heijde & Van der Heijden, 2005), and with particular concern in older women, who face a higher risk of age discrimination than men (Barrington, 2015).Older women are more likely to lower their career expectations (Magnarelli et al., 2020) and are the most disadvantaged in doctoral training structures (Beasy et al., 2022).

Stages
Alternative 1 Alternative 2 Alternative 3 Stage 1: Theoretical definition Employability is the ability to gain and retain fulfilling work (Hillage & Pollard, 1998).
Employability is the propensity of the graduate to exhibit attributes that employers anticipate will be necessary for the future effective functioning of their organization (Harvey, 2001).
Employability is the ability of the graduate to get a satisfying job.Given the importance of gender and age differences for employability, this study proposes the following hypothesis: there are statistically significant differences in the self-perceived level of development of employability skills that depend on gender (men/women), age (15 to 35/over 36 years), employment situation (employed/unemployed), and various interactions between these three factors.

Methodology
This study adopted an inductive approach to investigate the relationship between age and gender and the self-perceived level of development of employability skills.A rigorous process was followed to collect a representative sample of the student population of ITM's College of Engineering (n = 505 answered questionnaires).This should enable a deeper understanding of said relationship and offer arguments for a discussion.
An online questionnaire with closed-ended questions was administered in 2022 to collect quantitative data from participants.To recruit them, a variety of strategies were employed, including the involvement of scholarship recipients, who contacted them by phone or by email, asking them to complete the questionnaire.

Sample
The study population consisted of senior students from five engineering programs offered by the ITM in 2021 and graduates from the same programs from the two previous academic years (i.e., 2020 and 2021).To ensure representativity, this study used a stratified sampling technique that considered the number of students and graduates-classified by gender-of said study programs from the same years.According to ITM's academic information system, in 2021, there were 6,112 students enrolled in these engineering programs.Among them, 12.2% were women.In turn, there were 495 graduates, out of which 16.6% were female.
After the field work, 505 participants gave their informed consent.Among them, 70 participants (13.9%) were women.Table 3 shows that half of the participants were between 26 and 35 years of age; and more than a quarter of them, between 36 and 45.Moreover, 85.2% of the participants belonged to socioeconomic strata 1, 2, and 3, which is a close representation of the student population at ITM and in Colombia.

Measurements
In accordance with the proposed objective and methodology, an instrument was designed to assess a series of individual factors related to the abilities and skills (competences) necessary for a person to perform well in the world of work and evolve as an individual capable of adapting to the changes and needs of the environment.
Employability skills were evaluated using the six dimensions proposed by Fugate and Kinicki (2010): openness to changes at work (3 items), work and career proactivity (2 items), career motivation (2 items), work and career resilience (3 items), optimism at work (2 items), and work identity (1 item).An additional dimension-proposed by Bennett and Ananthram (2021)-was also included: professional knowledge (3 items).On a 5-point Likert scale, respondents indicated the extent to which they displayed each behavior in the workplace (e.g., "I apply the knowledge and skills acquired during my undergraduate studies in the workplace").According to the results, the Cronbach's alpha was between 0.70 and 0.86, and the reliability of this scale (α = 0.70) indicated acceptable internal consistency.Reliability, however, was recalculated using SPSS, yielding a Cronbach's alpha of 0.879 and a Cronbach's alpha based on standardized items of 0.886.
Table 4 shows the matrix of correlations between the seven dimensions.As observed in this table, the strongest positive significant correlations were between openness to changes at work (EP1) and work and career proactivity (EP2) and between career motivation (EP3) and work and career resilience (EP4).

Procedure
A descriptive statistical analysis was performed using frequency distributions and cross tabulation, and the mean and standard deviation of each quantitative variable were computed.A differential analysis was also conducted using the t-Student test, with gender, age, and employment status as the independent variables.Finally, Analysis of Variance (ANOVA) was employed to explore the interaction between the self-perceived level of development of employability skills and factors such as gender, age, and current employment status.
The value of the t-Student test, the F in ANOVA, the probability associated with these values (p), the degrees of freedom (df), and the effect size were estimated.The latter was calculated following Cohen's (1992), according to which a value of 0.20 represents a small difference; a value of 0.50, a moderate difference; and a value of 0.80 or greater, a large difference.Furthermore, the proposed hypotheses on the relationship between employability skills and age, gender, and employment status were tested using Pearson's correlation coefficient (r) and its error probability (p).The data were statistically processed using IBM SPSS (version 20.0) for Windows.

Results
This section describes the results obtained from the statistical analysis performed on respondents' perceived level of development of the seven employability skills, which they rated using a 5-point Likert scale, with 1 being "strongly disagree" and 5 being "strongly agree."Such results are presented as a function of gender, age, and employment status in Table 5.As can be seen in this table, respondents perceived a higher level of development of work and career resilience ( � X ¼ 4:22 and σ ¼ 0:679) and openness to changes at work � X ¼ 4:20 and σ ¼ 0:646 À � .Concerning gender, men perceived a higher level of development of most employability skills, with the exception of openness to changes at work-skill in which women obtained a mean higher than the overall mean � X ¼ 4:22 and σ ¼ 0:610 À � .In terms of age, respondents aged between 15 and 35 years perceived a higher level of development of employability skills than those in the other age groups, except for those aged over 36, who reported a higher level of applying the knowledge and skills acquired during their undergraduate studies in the workplace ð � X ¼ 4:25 and σ ¼ 0:715Þ.When it comes to employment status, employed respondents perceived a higher level of development of the seven employability skills, resulting in a significant difference when compared to those unemployed.
The significance of the differences in the self-perceived level of development of employability skills depending on gender, age, and employment status was estimated using the t-Student test.Following Martín et al. (2022), the assumption of homogeneity of variances was tested with Levene's test and the nonparametric Mann-Whitney U test, and their results corroborated those of the t-Student test.
According to the information presented in Table 5, men had different and higher means than women, but these differences were not found to be statistically significant ðp>0:05Þ.To assess the magnitude of the difference between the means of the two groups, the effect size was calculated for each skill.According to the results, the effect sizes for work and career proactivity d and professional knowledge d ¼ 0:152 ð Þ were between low and moderate, and the smallest effect size was reported for openness to changes at work d ¼ À 0:027 ð Þ.
In the case of age, the results presented in Table 6 followed this same trend.For employment status, employed respondents had different and higher means than unemployed respondents, and these differences were found to be statistically significant ðp<0:01Þ in the openness to changes at work, work and career proactivity, work and career resilience, optimism at work, and work identity skills.In the career motivation and professional knowledge skills, however, there were no statistically significant differences ðp>0:01Þ although the trend was the same.Additionally, the largest effect size was reported for work and career resilience d The second proposed hypothesis states that there exist significant differences in the self-perceived level of development of employability skills depending on gender (men/women), age (between the ages of 15 and 35 years/over 36 years old), employment status (employed/unemployed), and the possible interactions between these three factors.A factorial ANOVA was used to test this hypothesis, with the dependent variables being the seven employability skills and the independent variables being gender, age, and employment status.According to the results of Levene's test, the assumption of homogeneity of variances was met in all cases (Martín et al., 2022).In the cases in which the assumption of normality was not met, it was assumed, as indicated by Blanca et al. (2017), that this had no substantial effect on the ANOVA result, and the analysis was continued.
As can be seen in Table 7, men differ from women in the self-perceived level of development of two of the seven employability skills-openness to changes at work (EP1) and work and career proactivity (EP2) (p < 0.05), as also evidenced in Table 5.In the rest of the skills, the differences were not found to be statistically significant (p > 0.05), despite they followed the same trend.In terms of age (between the ages of 15 and 35 years or aged over 36 years), there were statistically significant differences (p < 0.05) in the work and career proactivity (EP2) and work identity (EP6) skills, with individuals under the age of 35 obtaining higher scores when compared to those over this age, as indicated in Table 5 and  6.This difference, however, is considered low (η 2 = 0.005) according to Cohen's (1992).
The interactions between two factors did not yield statistically significant differences because the error probability of F was less than 0.05, as shown in Table 7, with the effect sizes (η 2 <0.010) being very small.An exception to this was observed in the openness to changes at work (EP1) skill, in which the interaction between gender and employment status produced statistically significant differences (p < 0.05), with η 2 = 0.022-an effect size considered small according to Cohen's (1992).The same occurred in the work and career proactivity (EP2) skill, where the interaction between those two factors did not yield statistically significant differences (p > 0.05 and η 2 = 0.021).In the interactions between the three factors, the error probability of F was also not less than 0.05.Finally, as observed in Figure 1, unemployed women aged over 36 obtained lower scores than men in the career motivation (EP3), optimism at work (EP5), and work identity (EP6) skills, but there were no statistically significant differences (p > 0.05).

Discussion
This study investigated whether there are statistically significant differences in the self-perceived level of development of employability skills depending on gender, age, and employment status.For that purpose, the following seven key dimensions of employability were considered: openness to changes at work, work and career proactivity, career motivation, work and career resilience, optimism at work, work identity, and professional knowledge (Bennett & Ananthram, 2021;Fugate & Kinicki, 2010).
Participants' responses clearly illustrate the gender gap present in engineering programs at ITM: 86.1% men and 13.9% women.This is consistent with official estimates according to which, in Colombia, there were fewer female than male engineering graduates from 2001 to 2020.
In Colombia, the gender gap in STEM graduates has remained relatively steady over time, at roughly 39.4%.In particular, STEM programs at different educational levels present a certain gender gap: college (37.5%), graduate diploma (34.4%), master's degree (47.8%), and Ph.D. (51.9%) (CCCE, 2020).This means that, on average, 42.9% less women than men graduate from STEM programs.Although this gap increases noticeably as the educational level is higher, this is not far removed from the situation in other countries.For example, in Australia, women are reported to make up only 30% of individuals with STEM degrees (Dockery & Bawa, 2018).
To mitigate the impact of this gap, in 2022, the Colombian government adopted its "Public Policy on Gender Equality for Women: Towards Sustainable Development" through the National Council for Economic and Social Policy (CONPES in Spanish), which highlighted the digital gender gap.According to the International Telecommunication Union (ITU; 2021), the digital gender gap covers four aspects: (i) internet use and access; (ii) access to digital tools and skills; (iii) participation in the digital environment and STEM fields; and (iv) leadership and entrepreneurial spirit in the technology sector (DNP, 2022).This gap is also addressed in the United Nations Sustainable Development Goal 5, which promotes gender equality.To achieve it, the existing gap between men and women in STEM education should be reduced.
Consequently, in order to promote social change and fight stereotypes and gender discrimination, this public policy should pay more attention to gender equity and concentrate on issues relating to female leadership and entrepreneurship in the technology industry and STEM education.
Even though this study was limited to a single university and its results cannot be generalized to the entire country, its findings refute the popular misconception that women in STEM disciplines lack employability skills.According to the results, men presented different and higher arithmetic means than women, but these differences were not statistically significant.This is in line with the findings of Ehrlinger and Dunning (2003), who reported that, despite performing similarly to men in STEM areas, women are more likely to underestimate their skills.Also, Nabi and Bagley (1998) found significant gender differences in graduates' perceptions of their ability to develop specific transferable skills, with women demonstrating lower levels of confidence in their communication and problem-solving skills.Finally, Hill et al. (2010) reported that female students have less confidence in their skills in technical areas like math and physics.
Another gender gap has been found in employability-related support perceived by graduates.This gap affects female graduates more than their male counterparts and is especially visible in disciplinary areas that, historically, have been predominantly male (O'Leary, 2021).As a result, male graduates are more likely to obtain a full-time job with clear, well-defined functions in accordance with their education level.This is in contrast with the perceptions of women, who have lower expectations of employability and successful job transitions-even when they have adequate professional preparation (Monteiro et al., 2022).
Women, for instance, show less confidence in their communication and problem-solving skills (Nabi & Bagley, 1998), despite common sense that women are more emotionally intelligent, and men are more adept in critical thinking (O'Leary, 2017).Nevertheless, women in STEM careerscompared to those in other fields-show more confidence in tasks that involve problem-solving and decision-making, goal-oriented behavior, and improving occupational mobility (Bennett et al., 2021).In R&D jobs, women are less likely than men to engage in collaborations in fields related to science, technology, and innovation.In addition, they believe they are less equipped for technology-related jobs than men (Beasy et al., 2022).
In Colombia, educational gender gaps are created since childhood and get wider with age, especially in early adolescence (around 12 years old), when the percentage of female students is 12.5%.In 2020, 39.1% of women and 16.7% of men 15 years and older who were not studying did not have their own income-that is a 22.4% gap against women (Puccini Martinez, 2022).Considering age and employment situation, men-whether employed or unemployed-exhibit a similar trend to that observed in their answers regarding the development of employability skills.This is contrary to the answers given by unemployed women between 15 and 35, who feel that they can be proactive at work and are open to changes at work but show low levels of motivation and optimism regarding their STEM careers.Unemployed women aged over 36 were found not to feel proactive at work and professionally, which causes them to be less optimistic about achieving their career goals.
One of the responsibilities of the private sector is to keep their employees up-to-date regardless of their gender to avoid human capital depreciation, especially in professions that undergo rapid changes, such as those in STEM.Especialmente dentro de la industria de TI, la necesidad de actualización continua es totalmente necesaria, tanto para mujeres empleadas como desempleadas, debido a que el conocimiento en estas áreas pierde valor rápidamente.Las certificaciones formales en ciencia, tecnología e ingeniería pueden percibirse como de mayor importancia y de más valor agregado para las mujeres que para los hombres, como una forma de establecer puntos diferenciales y ganar legitimidad dentro de estos entornos dominados por hombres (Herman, 2015).

Conclusions
Despite efforts to have more graduates from STEM programs, there is still a shortage of this kind of talent in Latin America with respect to the growth of the IT industry.Beyond this region, the gender gap and employability rates are topics of global interest-they are even among the challenges proposed in the United Nations Sustainable Development Goals.However, in order to close this gap, governments and educational and labor systems should focus their efforts on helping individuals to develop employability skills alongside the STEM knowledge and skills required to succeed in the labor market.
Considering the above, this study analyzed employability from the perspective of employees, i.e., what people believe they are seeking for in a job (such as their possibilities of success and job satisfaction), as well as the factors that influence their perceptions, including gender, age, and employment situation.This is what distinguishes this study from most publications into employability, which focus on the effects of government policy, organizations' human resource strategies, society in general, and educators.Additionally, this research paves the way to bridge the gap between theory and reality in terms of the relational knowledge between the "internal" factors of employability (e.g., individuals' set of skills and their application to their studies) and other sociodemographic factors that affect it.
The results of this study confirmed that perceived employability is highly complex due to the multiple factors that influence how individuals perceive it, which, in turn, conditions both its outcomes and most significant effects.Importantly, such complexity derives from its subjective nature, that is, from the way professionals-based on their experiences, personal traits, and the characteristics of the labor market-perceive a greater or lesser degree of development of the skills they need to obtain a job, maintain it, and be promoted.
Although one of the strengths of this research is that the study participants included graduates and students from various engineering programs, it was not possible to obtain a representative sample of the population studying these careers at the national level.Nevertheless, the stratified sampling used in this study provided results that can be generalized to ITM's College of Engineering.A possible limitation of this study is that it did not include participants from other colleges, which could have been used to explore the potential effect of gender in different disciplines.
Future studies should use longitudinal designs to evaluate individuals' development of employability skills during professional training, prior to graduation, and several years after graduation.This would allow researchers to identify other factors influencing the degree of development of these skills and not only consider variables such as gender, age, and employment status.

Figure
Figure 1.Differences in the self-perceived level of development of employability skills depending on gender, age, and employment status.Note: Own work.

Table 3 . Age and gender distribution of the study population
Note: Own work using SPSS V26 software.

Table 6 . Student's t-test results Gender Age Employment status
Note: Own work using SPSS V26 software.