Next Article in Journal
Moral Panic over Fake Service Animals
Previous Article in Journal
Social Support and Self-Efficacy on Turnover Intentions: The Mediating Role of Conflict and Commitment
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Which Skills Are the Most Absent among University Graduates in the Labour Market? Evidence from Slovakia

1
Institute of Law, Slovak University of Agriculture in Nitra, 94976 Nitra, Slovakia
2
Institute of European Policies and Public Administration, Slovak University of Agriculture in Nitra, 94976 Nitra, Slovakia
3
Institute of Economic Policy and Finance, Slovak University of Agriculture in Nitra, 94976 Nitra, Slovakia
*
Author to whom correspondence should be addressed.
Soc. Sci. 2022, 11(10), 438; https://doi.org/10.3390/socsci11100438
Submission received: 25 August 2022 / Revised: 20 September 2022 / Accepted: 21 September 2022 / Published: 25 September 2022

Abstract

:
The most important purposes of Slovakian universities are research and education. The main goal of university education is to prepare highly skilled graduates to be employed in the labour market either at home or abroad. To achieve this goal, universities need to receive feedback from their graduates as to whether they are satisfied with their education and whether their employers are satisfied with their skills. The results obtained in this study show that, except for graduates from technical sciences, most graduates of Slovakian universities are not satisfied with the study programmes they chose. There are various factors affecting the satisfaction of graduates with their study programme; however, the most important ones were related to their employability and their employment in their field of study. Moreover, potential employers have greater expectations in relation to soft skills than graduates have acquired. The greatest differences between the required and acquired skills were seen in soft skills, such as the ability to take responsibility, to communicate with people, to negotiate, and to adapt to change, regardless of the field of study. Other than foreign language skills, the level of required hard skills was only slightly higher than the level acquired. According to these results, we make recommendations for universities, politicians, and potential employers; however, only reasonable cooperation among them can lead to graduates being satisfied with their chosen study programme.

1. Introduction

In Slovakia, one matter of discussion in public and political circles focuses on the concern that university graduates are not well prepared to achieve success in the labour market and that their skills do not match those required by employers (Kleštincová 2011; Kontrová et al. 2015; Lisá and Newman 2020). This issue is of great importance at a time of the ongoing accreditation of study programmes at Slovakian universities related to the adoption of measures to improve this situation. Moreover, skill mismatches appear to be key determinants of workers’ job satisfaction and may have negative impacts on wages (Badillo-Amador and Vila 2013). Abroad, many papers (presented below) discussing the gap between the skills that graduates acquire and those that employers require have been published. In Slovakia, this is a frequently discussed topic in political circles; however, scientific papers that try to attempt to reveal the causes of this phenomenon and look for tools to eliminate the gap between the skills of graduates and the requirements of the labour market in Slovakiaare missing. With our article, we attempt to engage in this discussion and support or refuse individual claims through the use ofanalytical tools. The goal of this paper is to determine which skills in the particular fields of study at Slovakian universities need to be imparted better or in greater quantity in order to align with the requirements of employers. The outcome should be graduates being satisfied with their study programmes at universities and well prepared for the labour market from the perspective of employers. First, we aimed to discover whether graduates who are employed are satisfied with their studies and which factors affect their satisfaction with their study programme. We were also interested in whether the level of satisfaction differed across graduates in particular fields. Second, based on these factors, we tried to quantify the differences in skills acquired during university studies and the requirements of the employers of these graduates. Lisá et al. (2019) argue that it is unnecessary to pay attention to skills in which graduates demonstrate a low level of proficiency but that are unimportant for success at work, and it is essential to pay attention to reducing the differences between graduates’ and employers’ perceptions of the level of skills acquired. Therefore, we compared 26 skills, which respondents rated on a scale from 1 (low level) to 10 (high level), first in terms of the skills acquired at the university and second in terms of their employer’s requirements for them. We hypothesised that statistically significant differences would exist between the skills that graduates acquire and those that employers require. Therefore, we were interested in the strength of the statistically significant differences, called the effect size. We determined which skills were the most absent—e.g., the skills with the biggest gap between the level acquired and the level required. At the same time, we compared the effect size among particular fields of study. Based on these results, we offer some recommendations for education policy as well as for Slovakian universities to eliminate the dissatisfaction of graduates and employers and to increase the quality of education and make receiving an education from Slovakian universities more attractive.

2. Literature Overview

One of the most important roles of universities is education, which is supposed to prepare graduates for the labour market. However, employers are mostly not satisfied with the skill level of university graduates not only in Slovakia. There are many papers published in other countries discussing the gap between the skills that graduates acquire and those that employers require. In Romania, employers have noted a significant deficiency in the ability to take responsibility and make decisions, work under pressure, and pay attention to accuracy and attention to detail (Chiru et al. 2012). Moreover, the abilities desired by employers in Romania are communications, teamwork, problem solving, and assimilation of new knowledge (Nicolescu and Pacaronun 2009). Among British graduates, the lowest-rated competencies are written communication skills, information, communication, and technology (ICT) skills, field-specific technical expertise, foreign language proficiency, the ability to work independently, and being achievement oriented (Chiru et al. 2012). Polish university graduates lack generic competencies, such as communication and interpersonal skills, which are crucial in the recruitment process and finding a job (Gawrycka et al. 2020). In Hungary, Lithuania, Slovenia, Poland, and Turkey, the research data show that the graduates in higher education mainly lack three types of generic competence: the ability to work under pressure, time management, and higher mastery of their field (Pukelis and Pileičikiene 2012). In the US, some skills desired by employers, such as interpersonal skills, project management, and presentation skills, differ from the skills that job seekers acquire in graduate school (Dewey et al. 2008). In Egypt, the findings indicate a significantly negative relationship between deficiencies in specific skills-namely, decision making, information technology, critical thinking, legal knowledge, problem-solving skills, ethical behaviour, ambiguity tolerance, presentation skills, written communication, and cost and managerial accounting skills- and audit quality.
The above-mentioned range of skills confirms that soft skills are considered critical in job interviews and are becoming increasingly scarce (Schislyaeva and Saychenko 2022). Similarly, among the key competencies required by employers in Germany and Norway, Arthur (2006) mentioned analytical skills, social skills, management skills, communication skills, the ability to learn, and presentation skills. Archer and Davison (2008) confirmed that, regardless of the size of the company, ‘soft skills’ (e.g., communication skills and team-working) were perceived to have more weight than technical or ‘hard skills’ (e.g., a good degree qualification, IT skills). Pang et al. (2019) found that employers in Hong Kong ranked the ability and willingness to learn, teamwork and cooperation, being hardworking and willing to take on extra work, self-control, and analytical thinking as the top five competencies. In Malaysia, employers rated the ability to work in a team, the ability to handle stress, and the ability to solve problems as the most important generic skills that new accounting graduates need to have; in addition, employers expect employees to be responsible, reliable, and trustworthy (Lim et al. 2019). In Auckland, New Zealand, a graduate’s ability and willingness to learn was considered the most important competency in the workplace for recent graduates in business roles (Hodges and Burchell 2003). In Pakistan, employers give more importance to skills such as creativity, communication, interpersonal, decision making, and problem solving (Rizwan et al. 2018). In China, employers perceived positive attitudes and behaviours—for example, working cooperatively with others, being responsible and adaptable, the ability to resolve conflict, communicating effectively in oral and written English, and a strong commitment to learning continuously—as extremely important qualities in graduates (Velde 2009). In Chile, the most important nontechnical competencies are ethics, communications, teamwork, innovation, and budgeting (LeBoeuf et al. 2013). Lists of the most demanded skills in different countries principally coincide and soft skills, such as communication skills, self-motivation, and a willingness to learn are important not only for social sciences but also in the natural and technical sciences (Shmatko and Volkova 2020).
The research papers cited above declared that one of the most required skills is communication. Stevens et al. (2019) stated that employers and academics are dissatisfied with the communication skills of many science graduates. However, opportunities for students to communicate in a variety of contexts are lacking (Stevens et al. 2019). Mercer-Mapstone and Kuchel (2017) defined 12 core skills for effective science communication. The most important were the ability to ‘identify and understand a suitable target audience’, ‘use language that is appropriate for target audience’, ‘identify the purpose and intended outcome of the communication’, and ‘consider the levels of prior knowledge in target audience’. It is not clear what the best way or place is to teach communication skills in science degrees: by adding a dedicated course, or by integrating them into existing courses. Both approaches have advantages and disadvantages (Mercer-Mapstone and Kuchel 2017). However, Pelger and Nilsson (2018) found that integrating different ways of communication training into science courses entailed improved skills in sharing and discussing scientific information and increased understanding of the subject. Shivni et al. (2021) made some recommendations about how to help students determine the right audience for their communication project, providing opportunities for students to try multiple types of media, determining the type of language that is appropriate for the audience, and encouraging students to aim for a mixture of communication objectives.
The other skill most absent among graduates is creativity. Oliver and Jorre (2018) stated that, in order for creative outcomes to be effectively fostered, creative outcomes must be explicitly stated in curricula, assessed, and taught. In their analysis, Jorre et al. (2019) confirm this, highlighting the importance of explicitly designing curricula that help students understand the career opportunities available, the skills and abilities needed for diverse careers, and the experiences through which they might develop and demonstrate them (Jorre et al. 2019). Based on their analysis of the curriculum at Canadian universities, Marquis et al. (2017) confirmed that creativity is relatively circumscribed in many ways, particularly in science, technology, engineering, and mathematics but can nonetheless be fostered through relevant activities. Cachia and Ferrari (2010) argues that there is a discrepancy between how teachers perceive creativity and the way in which they claim to foster creativity during their teaching. In many countries, education policies and objectives mention the need for creative learning, but do not provide a comprehensive working definition of creativity or instructive guidelines on how it should be promoted at school (Cachia and Ferrari 2010). Creative learning can be seen as any learning which involves understanding and new awareness, which allows the learner to go beyond notional acquisition, and focuses on thinking skills. It is the ability to make connections between things which were not connected before and see relationships between unrelated items (Runco 2007). From the teacher’s perspective, student creativity is illustrated as a six-facet model, in which teachers ‘see’ student creativity expressed through (1) student self-reflections, (2) independent decisions, (3) through curiosity and motivation, (4) producing something, (5) multi-perspectives, and (6) when students develop original new ideas (Jahnke et al. 2017). Georgiou et al. (2022) argue that theorising the discipline and the nature of creativity together is important in order to understand how creativity might be discussed and fostered in higher education more fruitfully.
What about the other missing skills, not all of which are the responsibility of universities? For example, US employers believe that college and university graduates should possess general knowledge, but other required knowledge or skills can be acquired in the workplace (Kottmann and de Weert 2013). Assamoi (2015) added that the first sources of behavioural competencies, such as social skills, leadership, and values and attitudes are university clubs and other activities, friends, and parents and family members.

3. Materials and Methods

The data, collected as part of a national project, are available for the purpose of research activities for the project VEGA-1/0504/21. The database contains answers by 13,684 respondents, who are university graduates of various bachelor’s- and master’s-degree programmes and completed their studies between 2008 and 2014. Among these respondents, 236 were omitted from the research, as the vast majority of the key questions were not answered. Most of the 13,448 respondents (77%) were employed, with only 10% continuing their studies, 9% unemployed, and 4% staying home to take care of a family member. We divided the respondents into four groups by their field of study: 4622 respondents (34%) graduated from programmes in the technical sciences, including informatics (TS&I); 4166 (31%) were in economics or law (Eco&Law), 3504 (26%) in other social sciences (SocScie), and 1156 (9%) in the natural sciences (NatScie). Figure 1 illustrates the distributionof respondents according to their field of study and employment.
In further analysis, we look only at respondents who were employed (10,397) because only they could consider the quality of their study programmes with respect to the requirements on the labour market and could compare the quality of the skills acquired by them and required by their employers.
We used a logit model in Gretl and logistic regression in PSPP to identify the most important factors that affect the satisfaction of graduates with their study programmes.
The logit model is based on a generalised linear model in which logit is expressed using a linear transformation of explanatory variables as the logarithm of the chance of the ratio of two values:
l n π 1 π = α + β i x i + ε i
where α is the constant, βi is the vector of the regression coefficients of the model, xi is the vector of the independent variables, and εi is the random error of the residuals. Then, π is the conditional mean of the explained variable, expressed as:
π = e α + β i x i 1 + e α + β i x i
π expresses the probability that graduate i will be satisfied with his studies and thus chooses option 1 (McFadden 1974). The regression coefficients express the rate of change in the logit.
The logistic regression as an inverse function of logit is expressed as:
π = e x β 1 + e x β
We use several statistics to evaluate the quality of the model, such as McFadden’s R-squared, Nagelkerke’s statistics, likelihood ratio test-chi squared with the corresponding p-value, and a classification table (including sensitivity and specificity), used for determining the share of correctly classified objects (more detailed in Stankovičová and Vojtková 2007).
The significance of the individual independent variables included in the model was determined by the p-value (calculated in Gretl) and by Wald statistics (calculated in PSPP).
To compare the significant differences between the scores for acquired skills by the study and skills required by the employers, we used the Wilcoxon signed rank test. It is a nonparametric test. To evaluate the results, we used the standard z-value with a 95% confidence interval in a two-tailed test and p-value in PSPP. The effect size was calculated as follows:
r = z N
where z is the z-value, and N is number of pairs (more detailed in Corder and Foreman 2014).

4. Results and Discussion

4.1. Satisfaction of University Graduates with Their Field of Study

We measured the satisfaction of employed graduates with the question about whether they would choose the same field of study at the same university again, or another field of study, or both (another field of study at another university), or would not study at the university. We consider only the first response (the same study at the same university) to mean satisfaction by the graduate; we treated all other answers as dissatisfaction with the university studies by the graduate. We expected most of the employed respondents to be satisfied with their field of study. Figure 2 illustrates the structure of responses by employed graduates.
Only 47% of the respondents (employed graduates) are satisfied with their university studies, and the remainder (53%) is dissatisfied for various reasons. However, this conclusions is not valid in general regardless the fields of study. We sorted the graduates into four groups based on their field of study, such as technical sciences, social sciences, natural sciences, and economics and law. In Figure 2, 54% of technical science graduates, 48% of graduates in economics or law, 43% of natural science graduates, and 37% of social science graduates are satisfied with their field of study. The most satisfied graduates are those in technical science and the least satisfied graduates are in social sciences. The technical science graduates have more job opportunities than the social science graduates; in addition, in Slovakia, graduates in the technical sciences usually receive higher salaries than those in the social sciences. However, there is one more reason that the highest share of satisfied graduates is in technical science. The most students studying technical sciences at universities had visited the technical high schools therefore they have already found their professional orientation while students studying the social or natural sciences are usually from grammar high school who have not usually correct visions their future career, so they could choose a study programme which they later (during their studies) found out of interest.
The results for the third response, indicating that the graduates would choose the same field of study at another university, are very interesting. We conclude that these graduates are firmly determined about their professional orientation, but they were disappointed in the university, which did not live up to their expectations, particularly in terms of the labour market. This is a clear signal to the university that the study programme needs to undergo certain changes, especially because the share of these responses is not negligible. Graduates in the natural sciences chose this response the most (11%), followed by 9% (by those in the social sciences) and 7% (by those in technical sciences).
Response options 2 and 4 indicate disappointment by the graduates with the field of study and their professional orientation. This combination raises a question as to whether it is necessary to adapt the study programmes more to the needs of the labour market or to increase awareness by high school students about study opportunities at universities. At the high schools, it would be necessary to improve students’ awareness of the possibilities of studying at universities and perfect information about ability. Varona Cervantes and Cooper (2022) found out in Germany that educational mismatch is also attributed to education choices based upon imperfect information about ability. This dissatisfaction by graduates ranges from 34% (technical sciences) to 49% (social sciences).
The lowest percentage of respondents (5% in each field of study) chose option 5, not to study at university at all. They are mostly graduates who are working outside their field of study or in positions that do not require a university education as well as those who are working in their field of study, but find that the professional orientation they chose is not fulfilling.
These results lead us to conclude that most graduates are not satisfied with their studies at Slovakian universities; however, with regard to the field of study, only the responses of technical science graduates confirm that most employed respondents are satisfied with their field of study.

4.2. Factors That Affect University Graduates’ Satisfaction with Their Studies

We assume that the most relevant factors affecting the satisfaction of graduates with their university studies are employability and employment in their field of study. In the models, y is the dependent variable, measured as follows: it takes a value of 1 if graduates are satisfied with their university studies and selected response option 1 = in the previous section; it takes a value of 0 when graduates are not satisfied with their studies. The 14 independent variables are listed in Table 1.
The significance of the above mentioned variables are expressed in Table 2.
The results of the model show that statistical significance is not confirmed for the variable gender (x1) and the level of study (bachelor’s or master’s degree) (x4). The rest of the independent variables can improve graduates’ satisfaction with their university studies, such as:
  • Age of graduates. Older respondents might indicate a more responsible approach to studies and that the respondent studies in a more targeted manner than younger graduates.
  • Number of years since leaving school. A longer period after graduation reduces the odds in favour of satisfaction with studies. It might indicate that universities improve their study programmes over time, thus increasing student satisfaction with their studies.
  • Form of study. The results show higher satisfaction among external (part-time) students. The chance in favour of satisfaction by full-time students decrease to 0.79. This is related to the fact that external students are usually older and choose their studies more deliberately.
  • Share of high-quality teachers. If the share of high-quality teachers increases by 1%, then the ratio of chances in favour of satisfaction with studies raise 1.01-fold. Given the result, we would expect a higher increase in satisfaction with studies. This variable probably will not be a decisive factor on the basis of which respondents would decide to attend the same school and study programme again.
  • Study as a good basis for entering the labour market. This is the most important factor affecting the satisfaction of graduates with their studies. If their studies have high benefits in terms of entering the labour market, satisfaction increases 2.11-fold; however, if studies yield only medium benefits, satisfaction increases only 1.20-fold.
  • Other important factors affecting the satisfaction of graduates with their study. These include studies as a good basis for further learning on the job (satisfaction increases 1.29-fold in the case of a high level); studies as a good basis for managing current work tasks (1.51-fold); studies as a good basis for a future career (1.77-fold); studies as a good basis for personal development (1.38-fold); studies as a good basis for a good basis for the development of entrepreneurial skills (1.57-fold).
  • The second-most-important factor is a job in the field of study. If graduates work outside the field of study, but can use at least some knowledge from their studies, it increases the chance in favour of dissatisfaction to 0.60. However, if they work outside their studies without any connection with their study programme, it increases the chance in favour of dissatisfaction to 0.39.
  • The last observed important factor affecting the satisfaction with the study is the field of study. Its statistically significant importance is assumed based on our previous analysis. If graduates studied technical sciences, the chance in favour of satisfaction with their studies increase 1.31-fold in comparison with the natural sciences; if they studied economics or law, the chance in favour of satisfaction with their studies increase 1.21-fold; however, if they studied the social sciences, the chance in favour of satisfaction with their studies decreases to 0.88.
We conclude that the most important factors that affect graduates’ satisfaction with their studies are related to their employability and employment in their field of study. The share of satisfaction with their studies is also affected by their field of study. On the other hand, the share of high-quality teachers is statistically significant indicators; however the satisfaction with the study programme affects to a negligible extent. In comparison to the results from Sri Lanka, the quality of the academic staff, university facilities, degree program, administrative staff, university location and university image have been correlated significantly with student satisfaction (Weerasinghe and Fernando 2017). There are many similar papers on student satisfaction with their study program focus on examining the conditions of education at universities, such as friendly classmates, expert teacher, well-known institute, good facilities, good technology, good management, good curriculum, practical program, good teaching, the satisfaction on the expert teacher, well known institute, and friendly (e.g., Leesoh et al. 2007; Khosravi et al. 2013; Luo et al. 2015; Kieng et al. 2021). However, there are only few paper oriented on the relation between satisfaction of study and labour market. In US, the study indicates that satisfaction with preparation for career and academic advising are the two factors that have the highest impact on satisfaction with university study (Tessema et al. 2021). Moreover, Varona Cervantes and Cooper (2022) found evidence that education mismatch does indeed have labour market effects through wages, job assignment and training.

4.3. Does a Gap Exist between the Skills Acquired by Graduates through Their Studies and Those Required by Their Employers?

The analysis above shows that the satisfaction of graduates is influenced mainly by their employment, ideally in their field of study. To achieve this satisfaction, university graduates must have the skills required by potential employers. The question is: which skills that would increase their chances of finding a job do university graduates lack? In other words, which skills should receive more focus and emphasis in the curriculum at Slovakian universities? We asked employed graduates to rate 26 hard and soft skills, using a scale from 1 (low) to 10 (high), first, in terms of the skills acquired through their studies and, second, in terms of employer requirements. The skills were divided into two groups as follows:
  • Hard skills consist of general knowledge, professional theoretical and methodological knowledge, language skill in the mother language, skill at a foreign language, mathematical skill, computer skill, economic skill, and legal skill.
  • Soft skills include the ability to use knowledge in practice, knowledge of the conditions in which professional methods and theories can be used in practice, the ability to work with information, the ability to identify and solve problems, creative thinking and acting, presentation skills, skill at written expression, the ability to make independent decisions, the ability to work in a team, having an active approach, entrepreneurship ability, the ability to handle stressful situations and obstacles, the ability to take responsibility, organisation, management and leadership, the ability to communicate with people and to negotiate, the ability to adapt to changes, the ability to work in an intercultural environment, and the ability to learn and organise their learning.
We assume that there are statistically significant differences between the acquired and required skills; however, we were interested not only in the existence of these differences but also in the size of the effect. The effect size enables us to determine which skills required for employments are the most absent for university graduates in their particular fields of study (Table 3).
In most cases, statistically significant differences arise between the skills obtained by graduates through their studies at Slovakian universities and those required by their employers. Statistically significant differences are absent for only few skills and only in particular fields of study, such as general knowledge (hard skills) in the social sciences, mathematical skills (hard skill) in the natural sciences or economics & law, the ability to learn and organise their learning (soft skills) in the social and natural sciences. We conclude that for most skills, a statistically significant difference exists between acquired and required skills. Moreover, the z-values are all negative, which indicates that the employer skill requirements exceed the level of graduates’ skills.
The levels of statistical significance do not indicate whether those differences between acquired and required skills are negligible or serious. Therefore, we look at the effect size (r). The value of r leads us to conclude that:
  • Graduates in the technical sciences have the highest differences in skill at a foreign language (hard skills) and soft skills, such as the ability to identify and solve problems, creative thinking and acting, the ability to make independent decisions, having an active approach, the ability to take responsibility, organisation, management, and leadership, the ability to communicate with people and to negotiate, the ability to adapt to changes, and the ability to work in an intercultural environment.
  • Graduates in economics and law have the highest differences in computer skills (hard skills) and soft skills such as the ability to identify and solve problems, creative thinking and acting, the ability to make independent decisions, having an active approach, the ability to handle stressful situations and obstacles, the ability to take responsibility, the ability to communicate with people and to negotiate, and the ability to adapt to change.
  • Graduates in the social sciences have the highest differences in economics and computer skills (hard skills) and soft skills such as the ability to identify and solve problems, the ability to handle stressful situations and obstacles, the ability to take responsibility, the ability to communicate with people and to negotiate, and the ability to adapt to change.
  • Graduates in the natural sciences have the highest differences in economics skills (hard skills) and soft skills such as the ability to take responsibility, the ability to communicate with people and to negotiate, and the ability to adapt to change.
We list here only the most serious differences between the required and acquired skills in particular fields of study. However, that does not mean that the other skills are at a satisfactory level. Most of them have an effect size higher than 0.30 in absolute value, it is an indication of medium-high differences between the required and acquired skills. Regardless of the field of study, the effect size of hard skills is, on average, −0.30 and that of soft skills is, on average, −0.41. This means that soft skills are usually neglected more than hard skills by universities in their study programmes. However, the small effect size (under 0.20 in absolute value) does not mean that the skills are not required by the employers, only that the skills of graduates are at a satisfactory level. Therefore, they should be also taken into account when the curriculum is prepared. On average, a smaller effect size was found in the natural and social sciences. This means that graduates in these fields reflect better the requirements of employers than graduates in the technical sciences and economics and law. At the same time, the effect size on average is higher than 0.30 in absolute values, thus neither the graduates in the natural sciences nor those in the social sciences should be satisfied with their level of hard or soft skills.
It is very surprising that the highest differences between the required and acquired skills were seen in soft skills, such as the ability to take responsibility, to communicate with people and to negotiate, and to adapt to change, regardless of the field of study. Similar results were found as well in other European countries, such as Romania (Chiru et al. 2012; Nicolescu and Pacaronun 2009), Poland (Gawrycka et al. 2020), Germany and Norway (Arthur 2006), and Hungary, Lithuania, Slovenia, and Turkey (Pukelis and Pileičikiene 2012). However, we agree with Leoni (2014), who believes that in general, because of the way in which they are trained and selected, university instructors cannot meet the educational challenges of modern employment conditions because of their heavy focus on research and little, if any, on teaching. One solution might be to distinguish between academics that are focused on research and have a smaller teaching burden and academics who are focused on teaching hard and soft skills to students and do less research. Few people are capable of being good teachers and good researchers at the same time, if for no other reason than time pressure.
Moreover, the soft skills that are lacking are not the responsibility of universities. Behavioural skills such as the ability to take responsibility (one of the most insufficient skills) should mainly be developed beginning in childhood, at nursery school, primary, and high school, as well within the family. It is difficult to teach these skills to adult students at universities if their previous training in these skills at school and by their families was neglected. Assamoi (2015) writes that the first sources of training in behavioural competencies at a university are clubs and other activities, in addition to friends, parents, and other family members. However, other soft skills (e.g., communication, creativity, problem solving) could be developed through education and training at universities. Finch et al. (2013) suggest that, in order to increase new graduates’ employability, university programmes and courses should focus on the learning outcomes linked to the development of soft skills. Gunn et al. (2010) agree that universities should take into account students’ employment needs ‘including the generic skills and abilities needed in the workplace’ and reflect this in the design of the curriculum and courses. However, academics fear that focusing on employability will lead to a diminution in academic standards and objectives. However, Knight and Yorke (2002) assume that curricula designed to enhance employability can also be beneficial in academic terms, e.g., in addition to subject knowledge, course content can address specific and generic skills, self-efficacy and effective critical thinking.
Based on our results, regardless of the field of study, universities should include more courses or lectures related to professional communication, psychology, and personal development in their curriculum. Moreover, university curricula should include problem-based learning methods to develop creativity and independence in graduates and enhance their ability to define a problem and seek solutions based on their theoretical background not only from their original disciplines but also from others. The integration of knowledge in their field of study from different disciplines when seeking solutions to problems enables them to take a multidisciplinary approach, which is one of the most important goals of sustainable development, including the sustainability of universities and their study programmes.
In addition, one of the best ways to eliminate the differences between the acquired and required skills is the opportunity to gain professional experience while a student, based on cooperation between potential employers and universities. Jackling and Natoli (2015) also recommend exposing students to real work environments. If this is not possible for a variety of reasons, simulation games could be used, as seen in business education. The use of business simulations facilitates sustainable knowledge transfer between education and industry (Beranič and Heričko 2022; Lovin et al. 2021; Boyle et al. 2016). However, the development of entrepreneurial skills is also useful in other fields of study.
Another way to develop the soft skills in students is by involving universities in cooperative projects with employers, which gives students better professional training before graduation (Letovancová and Lisá 2008). Aliu and Aigbavboa (2021) present a model for effective university-industry linkage that offers students mentoring opportunities and exposure to relevant training. Universities need to foster collaboration with industry in order to continuously enhance the employability of students before graduation (Aliu and Aigbavboa 2021), and employers need to take an active part in that collaboration, for example, by hiring students and giving them relevant and meaningful responsibilities. It is insufficient for employers merely to state that the graduates are unskilled and unprepared for the labour market. Moreover, policy makers should support these steps with financial programmes (e.g., decreasing taxes for participating employers, subsidies for student wages). At a minimum, universities could organise (together with potential employers of graduates) a short-term training programme for professional development to help students enhance their soft skills before they enter the labour market, and potential employers should work with the universities to design relevant study programmes. Nowadays, the new accreditation procedure asked from the universities the cooperation with the experts from the practice however, some fear that it will be limited to formal cooperation.
Intercultural skills are important not only for the graduates but also in the development of other soft skills. According to Mezirow (2018), exposing graduates to different cultural experiences can expand their worldview as well as help them to develop empathy, compassion, and an appreciation for diversity. De Sisto and Dickinson (2019) prefer to develop intercultural skills outside the classroom, which, they argue, enable students to come together in a relaxed environment and understand other cultures through sharing personal narratives. Furthermore, socialisation and cultural exposure during extracurricular events are positive experiences that foster an increased feeling of belonging (De Sisto and Dickinson 2019). One way to support intercultural skills is through student internships. Teichler and Janson (2007) agree that internships and short-term study abroad are the most appropriate methods for obtaining employability skills. Pinto (2020) states that studying abroad has a positive effect on the probability of becoming an entrepreneur, working in a foreign country, and gaining ICT skills (Pinto 2020).
Moreover, the technical infrastructure of universities is important as well. If classes take place in modern buildings with equipment that enables learning through specific IT programmes, teachers use information resources in the teaching process and this enables the integration of a number of specific practical activities, and if students have access to modern libraries and databases that enable them to conduct research, then students can attain specific skills, which implicitly influences their chances of employment (Gora et al. 2019). Lisá et al. (2019) added that institutions of higher education can provide and facilitate services, such as active contacts with employers, and promote self-management skills through career guidance centre services and psychological services, e.g., for the purpose of improving self-awareness that can help graduates identify the right profession for themselves (Lisá et al. 2019).
We mention here a few ways to improve the soft skills of university graduates, whose use depends on the field of study. However, regardless the field of study, cooperation among industry, universities, and national and EU governments is needed because universities should be one of the main engines of sustainable development with respect to human resources.

5. Conclusions

Higher education should reflect, on the one hand, the demand of students for education in particular fields of study and, on the other, the needs of the labour market and the requirements of potential employers of those students after they graduate.
From the student perspective, the results show that most students are not satisfied with their university studies. The most important factors that affect their satisfaction are related to their employability after graduation and finding a job related to their field of study.
From the employer perspective, the results show that the soft skills required most—such as communication skills, willingness and ability to take responsibility, flexibility, teamwork, creativity and problem solving—are not the ones obtained by students while at Slovakian universities, regardless of their field of study. Some of these, such as behavioural skills (e.g., being responsible), should be developed beginning in primary and high school as well as at home. Others—including communication skills, teamwork, creativity, and problem solving—could be improved through game simulations, working on real projects in a real work environment at a potential employer, internships abroad, summer school projects, etc.
Depending on the field of study, many possibilities are available. Moreover, the integration of skills and knowledge from different disciplines in a search for solutions to problems can lead to the creation of a multidisciplinary approach, which is one of the most important aims of sustainable development, including that of universities and their courses of study. However, cooperation among industry, universities, and national and EU governments is needed in order to achieve improvement in this area. Policy makers at the national and EU level should support the cooperation with financial programmes (e.g., decreasing taxes for participating employers, subsidies for student wages, grants projects to support soft skills trainings). The new university accreditation process in Slovakia should take into account the need for soft skills in individual professional courses or as separate courses, especially in natural and technical sciences, where the possibility of training them within professional courses is not assumed.
There are also some limitations of this study. The first limitation is related to the question of the satisfaction of graduates with their study programmes. If the respondents answered that they would choose another study program at the same school (option 2) or a different study program at another university (option 4), they may be dissatisfied either because they are not interested in what they do professionally or were disappointed by their chosen study program. It would be appropriate to find out whether their choice may have led them to a related study program, where the school did not seem to offer the graduates what they needed to enter the labour market, or to a completely different field of study, which would confirm the presumption of the incorrect professional orientation of graduates. The second limitation is related to the respondents having graduated from 2008 to 2014. It would be appropriate to repeat this research after a new accreditation process has been implemented in Slovakia. The third limitation concerns the study programs, which were divided into only four groups for the sake of clarity. The analysis of individual study program subgroups could lead to more detailed results being obtained. However, given that in each group of study programs insufficient soft skills have been demonstrated, this analysis is already applicable to the adoption of political measures as well as measures at the level of universities.

Author Contributions

Conceptualisation, J.L. and Ľ.R.; methodology, J.L.; validation, J.L., Ľ.R. and I.T.; formal analysis, J.L. and Ľ.R.; investigation, J.L. and Ľ.R.; resources, I.T.; data curation, M.P., Ľ.R. and I.T.; writing—original draft preparation, J.L.; writing—review and editing, Ľ.R., I.T., T.M. and M.P.; visualisation, T.M.; project administration, I.T.; funding acquisition, I.T. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences within the following projects: Employability of graduates as a determinant of sustainable development of universities No. VEGA-1/0504/21 and Coworking spaces as a phenomenon of shared economy and a new trend for business and the workplace No. VEGA-1/0437/22.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Aliu, John, and Clinton Ohis Aigbavboa. 2021. Structural determinants of graduate employability: Impact of university and industry collaborations. Journal of Engineering, Design and Technology 19: 1080–100. [Google Scholar] [CrossRef]
  2. Archer, Will, and Jess Davison. 2008. Graduate Employability: What Do Employers Think and Want? London: The Council for Industry and Higher Education (CIHE). [Google Scholar]
  3. Arthur, Lore. 2006. Higher education and the area of work: Issues, challenges and responses in Norway and Germany. Research in Comparative and International Education 3: 241–52. [Google Scholar] [CrossRef]
  4. Assamoi, Christophe A. O. 2015. Core competencies development among science and technology (S&T) college students and new graduates. American Journal of Educational Research 3: 1077–84. [Google Scholar]
  5. Badillo-Amador, Lourdes, and Luis E. Vila. 2013. Education and skill mismatches: Wage and job satisfaction consequences. International Journal of Manpower 34: 416–28. [Google Scholar] [CrossRef]
  6. Beranič, Tina, and Marjan Heričko. 2022. The impact of serious games in economic and business education: A case of ERP business simulation. Sustainability 14: 683. [Google Scholar] [CrossRef]
  7. Boyle, Elizabeth A., Thomas Hainey, Thomas M. Connolly, Grant Gray, Jeffrey Earp, Michela Ott, Theodore Lim, Manuel Ninaus, Claudia Ribeiro, and João Pereira. 2016. An update to the systematic literature review of empirical evidence of the impacts and outcomes of computer games and serious games. Computers & Education 94: 178–92. [Google Scholar]
  8. Cachia, Romina, and Anusca Ferrari. 2010. Creativity in Schools: A Survey of Teachers in Europe. European Commission Joint Research Centre Institute for Prospective Technological Studies. Luxembourg: Publications Office of the European Union. [Google Scholar]
  9. Chiru, Codrin, Stela Georgiana Ciuchete, Gina Gilet Lefter (Sztruten), and Elena Paduretu (Sandor). 2012. A cross country study on university graduates key competencies. An employer’s perspective. Procedia—Social and Behavioral Sciences 46: 4258–62. [Google Scholar] [CrossRef]
  10. Corder, Gregory W., and Dale I. Foreman. 2014. Nonparametric Statistics. A Step-by-Step Approach, 2nd ed. Hoboken: John Wiley & Sons, Inc. 288p. [Google Scholar]
  11. De Sisto, Marco, and Genevieve Dickinson. 2019. Investigating strategies for developing cultural intelligence: A creative learning experience to enhance student transition to a global workforce. In Transformations in Tertiary Education. Edited by Belinda Tynan, Tricia McLaughlin, Andrea Chester, Catherine Hall-van den Elsen and Belinda Kennedy. Singapore: Springer Nature, pp. 145–61. [Google Scholar] [CrossRef]
  12. Dewey, Jennifer D., Bianca E. Montrosse, Daniela C. Schröter, Carolyn D. Sullins, and John R. Mattox. 2008. Evaluator competencies: What’s taught versus what’s sought. American Journal of Evaluation 29: 268–87. [Google Scholar] [CrossRef]
  13. Finch, David J., Leah K. Hamilton, Riley Baldwin, and Mark Zehner. 2013. An exploratory study of factors affecting undergraduate employability. Education + Training 55: 681–704. [Google Scholar] [CrossRef]
  14. Gawrycka, Małgorzata, Justyna Kujawska, and Michał T. Tomczak. 2020. Competencies of graduates as future labour market participants—Preliminary study. Economic Research-Ekonomska Istraživanja 33: 1095–107. [Google Scholar] [CrossRef]
  15. Georgiou, Helen, Annette Turney, Erika Matruglio, Pauline Jones, Paul Gardiner, and Christine Edwards-Groves. 2022. Creativity in higher education: A qualitative analysis of experts’ views in three disciplines. Education Sciences 12: 154. [Google Scholar] [CrossRef]
  16. Gora, Ana Alexandra, Simona Cătălina Ștefan, Ștefan Cătălin Popa, and Cătălina Florentina Albu. 2019. Students’ perspective on quality assurance in higher education in the context of sustainability: A PLS-SEM approach. Sustainability 11: 4793. [Google Scholar] [CrossRef]
  17. Gunn, Vicky, Sheena Bell, and Klaus Kafmann. 2010. Thinking Strategically about Employability and Graduate Attributes: Universities and Enhancing Learning for beyond University. Enhancement Themes. QAA. Available online: http://www.enhancementthemes.ac.uk/documents/G21C/Employability_230210.pdf (accessed on 15 June 2020).
  18. Hodges, Dave, and Noel Burchell. 2003. Business graduate competencies: Employers’ views on importance and performance. Asia-Pacific Journal of Cooperative Education 4: 16–22. [Google Scholar]
  19. Jackling, Beverley, and Riccardo Natoli. 2015. Employability skills of international accounting graduates: Internship providers’ perspectives. Education & Training 57: 757–73. [Google Scholar]
  20. Jahnke, Isa, Tobias Haertel, and Johannes Wildt. 2017. Teachers’ conceptions of student creativity in higher education. Innovations in Education and Teaching International 54: 87–95. [Google Scholar] [CrossRef]
  21. Jorre, Trina Jorre de St, Joanne Elliott, Elizabeth D. Johnson, and Stewart Bisset. 2019. Science students’ conceptions of factors that will differentiate them in the graduate employment market. Journal of Teaching and Learning for Graduate Employability 10: 27–41. [Google Scholar] [CrossRef]
  22. Khosravi, Ali Akbar, Kambiz Poushaneh, Amitida Roozegar, and Nasrin Sohrabifard. 2013. Determination of Factors Affecting Student Satisfaction of Islamic Azad University. Procedia—Social and Behavioral Sciences 84: 579–83. [Google Scholar] [CrossRef]
  23. Kieng, Rotana, Kitti Phothikitti, and Rawin Vongurai. 2021. Critical Factors Affecting Student Satisfaction and Loyalty: An Empirical Study in Cambodia. The Journal of Asian Finance, Economics and Business 8: 225–34. [Google Scholar] [CrossRef]
  24. Kleštincová, Lucia. 2011. Spájame vysoké školy s trhom práce./We Join the Universities with the Labour Market. Bratislava: Inštitút Hospodárskej Politiky. 41p. [Google Scholar]
  25. Knight, Peter T., and Mantz Yorke. 2002. Employability through the curriculum. Tertiary Education and Management 8: 261–76. [Google Scholar] [CrossRef]
  26. Kontrolvá, Mária, Jan Koucký, Peter Obdržálek, and Daniela Olejárová. 2015. Vysoké školy, pracovný trh a uplatnenie absolventov./ Uniersities, Labour Market and Employability of Graduates. Bratislava: CVTI. 41p. [Google Scholar]
  27. Kottmann, Andrea, and Egbert de Weert. 2013. Higher Education and the Labour Market, International Policy Frameworks for Regulating Graduate Employability. Enschede: Centre for Higher Education Policy Studies. 53p, Available online: http://doc.utwente.nl/88807/1/higher-education-and-the-labour-market.pdf (accessed on 1 July 2021).
  28. LeBoeuf, Richard, Matías Pizarro, and Ricardo Espinoza. 2013. Identification of non-technical competency gaps of engineering graduates in Chile. International Journal of Engineering Education 29: 426–38. [Google Scholar]
  29. Leesoh, Niramon, Nittaya McNeil, Paktra Kooburat, and Achara Thummarpon. 2007. Factors Affecting Graduates Satisfaction about the Learning Process at Prince of Songkla University. Kasetsart Journal of Social Sciences 28: 117–26. [Google Scholar]
  30. Leoni, Riccardo. 2014. Graduate employability and the development of competencies. The incomplete reform of the ‘Bologna process’. International Journal of Manpower 35: 448–69. [Google Scholar] [CrossRef]
  31. Letovancová, Eva, and Elena Lisá. 2008. Professional orientation of university students and comparing them with requirements of vocational positions in labour market in Bratislava. In Kairos. Edited by Bernd Glazinski and Josef Kramer. Cologne: Verlag für Angewandte Managementforschung, pp. 66–91. [Google Scholar]
  32. Lim, Yet Mee, Tat Huei Cham, and Teck Heang Lee. 2019. Employer-employee perceptual differences in job competency: A study of generic skills, knowledge required, and personal qualities for accounting-related entry-level job positions. International Journal of Academic Research in Accounting, Finance and Management Sciences 9: 73–83. [Google Scholar] [CrossRef]
  33. Lisá, Elena, and Denisa Newman. 2020. Zamestnateľnosť a kariérové zručnosti študentov a absolventovvysokých škôl v kontexte zamestnávateľských očakávaní. /Employability and career skills of students and university graduates in the context of employer expectations. Kariérové poradenstvo v teórii a praxi/Career Counseling in Theory and Practice/ 17: 47–58. [Google Scholar]
  34. Lisá, Elena, Katarína Hennelová, and Denisa Newman. 2019. Comparison between employers’ and students’ expectations in respect of employability skills of university graduates. International Journal of Work-Integrated Learning 20: 71–82. [Google Scholar]
  35. Lovin, Daniel, Monica Raducan, Alexandru Capatina, and Nicoleta Cristache. 2021. Sustainable Knowledge Transfer from Business Simulations to Working Environments: Correlational vs. Configurational Approach. Sustainability 13: 2154. [Google Scholar] [CrossRef]
  36. Luo, Siming, Niamatullah, Jianying Gao, Dan Xu, and Khurrum Shaf. 2015. Factors Leading to Students’ Satisfaction in the Higher Learning Institutions. Journal of Education and Practice 6: 114–18. [Google Scholar]
  37. Marquis, Elizabeth, Kaila Radan, and Alexandra Liu. 2017. A present absence: Undergraduate course outlines and the development of student creativity across disciplines. Teaching in Higher Education 22: 222–38. [Google Scholar] [CrossRef]
  38. McFadden, Daniel. 1974. Conditional logit analysis of qualitative choice behaviour. In Frontiers in Econometrics. New York: Academic Press, pp. 105–42. [Google Scholar]
  39. Mercer-Mapstone, Lucy, and Louise Kuchel. 2017. Core skills for effective science communication: A teaching resource for undergraduate science education. International Journal of Science Education, Part B 7: 181–201. [Google Scholar] [CrossRef]
  40. Mezirow, Jack. 2018. Transformative learning theory. In Contemporary Theories of Learning. Oxfordshire: Routledge, pp. 114–28. [Google Scholar]
  41. Nicolescu, Luminița, and Cristian Pacaronun. 2009. Relating higher education with the labour market: Graduates’ expectations and employers’ requirements. Tertiary Education and Management 15: 17–33. [Google Scholar] [CrossRef]
  42. Oliver, Beverley, and Trina Jorre de St Jorre. 2018. Graduate attributes for 2020 and beyond: Recommendations for Australian higher education providers. Higher Education Research & Development 37: 821–36. [Google Scholar]
  43. Pang, Elvy, Michael Wong, Chi Hong Leung, and John Coombes. 2019. Competencies for fresh graduates’ success at work: Perspectives of employers. Industry and Higher Education 33: 55–65. [Google Scholar] [CrossRef]
  44. Pelger, Susanne, and Pernilla Nilsson. 2018. Observed learning outcomes of integrated communication training in science education: Skills and subject matter understanding. International Journal of Science Education, Part B 8: 135–49. [Google Scholar] [CrossRef]
  45. Pinto, Fernando. 2020. The effect of university graduates’ international mobility on labour outcomes in Spain. Studies in Higher Education 47: 26–37. [Google Scholar] [CrossRef]
  46. Pukelis, Kestutis, and Nora Pileičikiene. 2012. Matching of developed generic competencies of graduates in higher education with labour market needs. Quality of Higher Education 9: 140–67. [Google Scholar] [CrossRef]
  47. Rizwan, Ali, Ayhan Demirbas, Nader Al Sayed Hafiz, and Umair Manzoor. 2018. Analysis of perception gap between employers and fresh engineering graduates about employability skills: A case study of Pakistan. International Journal of Engineering Education 34: 248–55. [Google Scholar]
  48. Runco, Mark A. 2007. Creativity: Theories and Themes: Research, Development, and Practice. Amsterdam: Elsevier Academic Press. [Google Scholar]
  49. Schislyaeva, Elena Rostislavovna, and Olga Anatolievna Saychenko. 2022. Labour market soft skills in the context of digitalization of the economy. Social Sciences 11: 91. [Google Scholar] [CrossRef]
  50. Shivni, Rashmi, Christina Cline, Morgan Newport, Shupei Yuan, and Heather E. Bergan-Roller. 2021. Establishing a baseline of science communication skills in an undergraduate environmental science course. International Journal of STEM Education 8: 47. [Google Scholar] [CrossRef]
  51. Shmatko, Natalia, and Galina Volkova. 2020. Bridging the Skill Gap in Robotics: Global and National Environment. SAGE Open 10: 1–13. [Google Scholar] [CrossRef]
  52. Stankovičová, Iveta, and Mária Vojtková. 2007. Viacrozmerné štatistické metódy s aplikáciami./Multivariate Statistical Methods with Applications. Bratislava: IURA Edition, Member of Wolters Kluwer. 261p. [Google Scholar]
  53. Stevens, Sarah, Rebecca Mills, and Louise Kuchel. 2019. Teaching communication in general science degrees: Highly valued but missing the mark. Assessment & Evaluation in Higher Education 44: 1163–76. [Google Scholar] [CrossRef]
  54. Teichler, Ulrich, and Kerstin Janson. 2007. The professional value of temporary study in another European country: Employment and work of former ERASMUS students. Journal of Studies in International Education 11: 486–495. [Google Scholar] [CrossRef]
  55. Tessema, Mussie T., Kathryn Ready, and Wei-Choun Yu. 2021. Factors Affecting College Students’ Satisfaction with Major Curriculum: Evidence from Nine Years of Data. International Journal of Humanities and Social Science 2: 34–44. [Google Scholar]
  56. Varona Cervantes, Carla, and Russell Cooper. 2022. Labor market implications of education mismatch. European Economic Review 148: 104179. [Google Scholar] [CrossRef]
  57. Velde, Christine. 2009. Employers’ perceptions of graduate competencies and future trends in higher vocational education in China. Journal of Vocational Education and Training 61: 35–51. [Google Scholar] [CrossRef]
  58. Weerasinghe, Salinda IM, and Ranhaluge Lalitha Srimath i Fernando. 2017. Critical factors affecting students’ satisfaction with higher education in Sri Lanka. Quality Assurance in Education 26: 115–30. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Structure of respondents.
Figure 1. Structure of respondents.
Socsci 11 00438 g001
Figure 2. Structure of employed respondents based on their satisfaction or dissatisfaction with their studies.Note: 1 = graduates would choose the same field of study at the same university (satisfaction with the study at the university); 2 = graduates would choose another field of study at the same university (dissatisfaction with the field of study); 3 = graduates would choose the same field of study at another university (dissatisfaction with the university); 4 = graduates would choose another field of study at another university(dissatisfaction with both, field of study and the university as well); 5 = graduates would not study at the university (dissatisfaction with the university study in general).
Figure 2. Structure of employed respondents based on their satisfaction or dissatisfaction with their studies.Note: 1 = graduates would choose the same field of study at the same university (satisfaction with the study at the university); 2 = graduates would choose another field of study at the same university (dissatisfaction with the field of study); 3 = graduates would choose the same field of study at another university (dissatisfaction with the university); 4 = graduates would choose another field of study at another university(dissatisfaction with both, field of study and the university as well); 5 = graduates would not study at the university (dissatisfaction with the university study in general).
Socsci 11 00438 g002
Table 1. Independent variables.
Table 1. Independent variables.
VariableName of VariableShort Description
x1gender0 = female; 1 = male
x2ageranges from 27 to 69; mean is 36 years
x3Number of years since leaving schoolranges from 8 to 14; mean is 10 years
x4type of study0 = master’s degree studies; 1 = bachelor’s degree studies
x5form of study0 = full-time students; 1 = external (part-time) students
x6share of high-quality teachersRanges from 0% to 100%; mean is 55.6%
x7study as a good basis for entering the labour marketHigh benefit
Medium benefit
Small benefit—benchmark
x8study as a good basis for further learning within the workHigh benefit
Medium benefit
Small benefit—benchmark
x9study as a good basis for managing current work tasksHigh benefit
Medium benefit
Small benefit—benchmark
x10study as a good basis for a future careerHigh benefit
Medium benefit
Small benefit—benchmark
x11study as a good basis for personal developmentHigh benefit
Medium benefit
Small benefit—benchmark
x12study as a good basis for the development of entrepreneurial skillsHigh benefit
Medium benefit
Small benefit—benchmark
x13work in the field of studyWork out of the field of study
Work out of the field of study but using knowledge from the field of study
Work in the field of study—benchmark
x14field of studyTechnical sciences
Economics/law
Social sciences
Natural sciences—benchmark
Notes: The significance of the model is expressed with statistics such as McFaden’s R-squared, which is 0.194; this means that, at 19.4%, we are approaching the actual value, which is always very low (usually up to 20%), so, it is difficult to draw a conclusion about the suitability of the model. Therefore, we supplement the model evaluation with Nagelkerke’s statistics, whose value rangesfrom 0 to 1. In our case, Nagelkerke’s R-squared reaches a value of 0.31, which means that the logistic regression model explains 31% of the variability. The likelihood ratio test (chi squared = 2791.03, with a p-value = 0.000) confirms the significance of the model as a whole. However, the most important indicator for evaluating the quality of both models is the number of correct predictions. The models report 71.30% of correct predictions, which is a relatively robust result (sensitivity is 0.76 and specificity 0.65).
Table 2. Results of the logit model and logistic regression.
Table 2. Results of the logit model and logistic regression.
Independent Variable xiSlopep-Value Exp (β)Wald Statistics
Constant−5.0070.0000.2225.07
x10.0070.5641.030.33
x20.0060.0001.0313.72
x3−0.0240.0000.9138.77
x4−0.0300.1190.892.43
x5−0.0570.0030.799.10
x60.0030.0001.01179.66
x7
High benefit 0.1840.0002.1173.87
Medium benefit 0.0450.0181.205.56
Small benefit benchmark 117.96
x8
High benefit 0.0640.0041.298.15
Medium benefit −0.0110.6150.960.25
Small benefitbenchmark 30.00
x9
High benefit 0.1020.0001.5120.94
Medium benefit 0.0530.0091.246.80
Small benefitBenchmark 23.94
x10
High benefit 0.1420.0001.7748.72
Medium benefit 0.0120.5041.050.45
Small benefitbenchmark 89.95
x11
High benefit 0.0800.0011.3810.18
Medium benefit−0.0430.0870.842.94
Small benefitbenchmark 90.25
x12
High benefit 0.1120.0001.5710.05
Medium benefit 0.0430.0011.1910.60
Small benefitbenchmark 40.26
x13
work out of the field of study−0.2230.0000.39205.85
work out of the field of study with using knowledge from the field of study−0.1260.0000.6086.40
work in the fields of studybenchmark 223.95
x14
Technical sciences0.0660.0041.318.37
Economics/law 0.0480.0351.214.45
Social sciences −0.0320.1640.881.93
Natural sciencesbenchmark 42.59
Notes: The significance of the variables in the model can be assessed in GRETL via the p-value test at 5% significance level and in the PSPP program via Wald statistics. If the Wald’s statistics approach zero, the significance of the variables in the model is decreasing.
Table 3. Differences between acquired and required skills in particular fields of study.
Table 3. Differences between acquired and required skills in particular fields of study.
Skill/Field of StudyWilcoxon Test Statistics and Size EffectTS&IEco&LawSocScieNatScie
General knowledge Z-score
r
−15.21
−0.28
−7.48
−0.15
−0.26 *
−0.01
−3.85
−0.15
Professional theoretical and methodological knowledgeZ-score
r
−10.39
−0.19
−4.23
−0.08
−3.17
−0.07
−2.00
−0.08
Economics skillsZ-score
r
−25.75
−0.48
−17.22
−0.34
−24.77
−0.55
−13.29
−0.52
Legal skillsZ-score
r
−20.02
−0.37
−11.99
−0.24
−14.38
−0.32
−10.38
−0.41
Language skills in the mother languageZ-score
r
−10.06
−0.19
−11.53
−0.23
−4.71
−0.10
−4.84
−0.19
Skill at a foreign languageZ-score
r
−33.25
−0.62
−23.27
−0.46
−17.50
−0.39
−10.51
−0.42
Mathematical skillsZ-score
r
−26.38
−0.49
−0.79 *
−0.02
−17.35
−0.38
−0.73 *
−0.03
Computer skillsZ-score
r
−16.56
−0.31
−26.25
−0.52
−24.20
−0.54
−9.12
−0.36
Skill to work with informationZ-score
r
−18.29
−0.34
−22.67
−0.45
−11.11
−0.25
−5.90
−0.23
Ability to identify and solve problemsZ-score
r
−33.39
−0.62
−31.88
−0.64
−24.45
−0.54
−12.13
−0.48
Creative thinking and actingZ-score
r
−28.58
−0.53
−28.44
−0.57
−18.62
−0.41
−10.56
−0.42
Presentation skillsZ-score
r
−6.29
−0.12
−11.51
−0.23
−4.31
−0.10
−3.34
−0.13
Skill of written expressionZ-score
r
−12.95
−0.24
−18.08
−0.36
−2.43
−0.05
−3.64
−0.14
Ability to make independent decisionsZ-score
r
−30.91
−0.58
−28.82
−0.57
−20.28
−0.45
−12.38
−0.49
Ability to work in a teamZ-score
r
−21.32
−0.40
−18.49
−0.37
−14.11
−0.31
−9.66
−0.38
Having an active approachZ-score
r
−29.85
−0.56
−29.81
−0.59
−21.69
−0.48
−12.13
−0.48
Entrepreneurship abilityZ-score
r
−23,70
−0.44
−22.41
−0.45
−19.61
−0.43
−9.95
−0.39
Ability to handle with stressful situations and obstaclesZ-score
r
−24.22
−0.45
−27.72
−0.55
−23.56
−0.52
−11.96
−0.47
Ability to take responsibilityZ-score
r
−32.76
−0.61
−31.47
−0.63
−25.38
−0.56
−14.15
−0.56
Organisation, management, and leadershipZ-score
r
−26.99
−0.50
−22.69
−0.45
−19.80
−0.44
−11.90
−0.47
Ability to use knowledge in practiceZ-score
r
−25.90
−0.48
−22.86
−0.46
−11.18
−0.25
−7.05
−0.28
Ability to communicate with people and to negotiateZ-score
r
−34.97
−0.65
−32.62
−0.65
−26.73
−0.59
−15.92
−0.63
Ability to adapt to changesZ-score
r
−29.67
−0.55
−30.18
−0.60
−24.87
−0.55
−13.67
−0.54
Ability to work in an intercultural environmentZ-score
r
−31.08
−0.58
−21.26
−0.42
−14.12
−0.31
−8.78
−0.35
Ability to learn and organise their learningZ-score
r
−3.08
−0.06
−4.50
−0.09
−0.17 *
−0.00
−0.68 *
−0.03
Knowledge of the conditions under which it is possible to use professional methods and theories in practiceZ-score
r
−18.93
−0.35
−14.96
−0.30
−7.12
−0.16
−4.12
−0.16
* means that the statistically significant differences are not given. Notes: We used a Wilcoxon signed rank test at 5% significance level and then drew conclusions based on the z-value and p-value to clarify the statistically significant differences between the skills acquired and required; p-value was usually smaller than 0.05; only in some cases the statistically significant differences were not proved. In Table 3 it is remarked by *. The effect size (r) enables us to compare the differences in its size between pairs. The effect size is measured from −1 to 1; if the size is negative, then employer requirements of graduates’ skills exceed the level obtained by the graduates through their studies. If r is close to zero, the effect size is negligible, and the differences can be narrowed through graduates’ engagement in independent study or short training. However, if r is close to one in absolute value, the effect size is very high, indicating a serious problem related to a particular skill obtained in a field of study.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Lazíková, J.; Takáč, I.; Rumanovská, Ľ.; Michalička, T.; Palko, M. Which Skills Are the Most Absent among University Graduates in the Labour Market? Evidence from Slovakia. Soc. Sci. 2022, 11, 438. https://doi.org/10.3390/socsci11100438

AMA Style

Lazíková J, Takáč I, Rumanovská Ľ, Michalička T, Palko M. Which Skills Are the Most Absent among University Graduates in the Labour Market? Evidence from Slovakia. Social Sciences. 2022; 11(10):438. https://doi.org/10.3390/socsci11100438

Chicago/Turabian Style

Lazíková, Jarmila, Ivan Takáč, Ľubica Rumanovská, Tomáš Michalička, and Michal Palko. 2022. "Which Skills Are the Most Absent among University Graduates in the Labour Market? Evidence from Slovakia" Social Sciences 11, no. 10: 438. https://doi.org/10.3390/socsci11100438

APA Style

Lazíková, J., Takáč, I., Rumanovská, Ľ., Michalička, T., & Palko, M. (2022). Which Skills Are the Most Absent among University Graduates in the Labour Market? Evidence from Slovakia. Social Sciences, 11(10), 438. https://doi.org/10.3390/socsci11100438

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop