essay on vocational training

Essay on Vocational Education for Students and Children

500 words essay on vocational education.

It refers to a skill-based program that enables students to obtain knowledge, training, and practical skills of a specific trade. It is often referred to as technical or career education as it helps students develop skills in a particular discipline. In addition, they focus more on application-based training rather than theoretical knowledge.

Besides, diverse job functions from various sectors such as food and beverages, computer network cosmetology, banking and finance, tourism, skilled trades, and healthcare, etc. include vocational training.

Source: NIOS

Benefits of Vocational Training

The vocational training has many benefits not only for an individual but also for the nation. Furthermore, some benefits of vocational training are:

Job-ready – This training makes a person job-ready and students can directly get a job after completing their studies. In addition, it provides students the required set of skills and training for various jobs such as fashion designers, computer networking, interior designing and many more. Also, it makes the person skilled and ready for the job of their respective fields.

Low Education Cost – The fees of these courses are quite economic and anyone can easily afford to pay for them. Moreover, they are an easy alternative for those students who do not want to opt for a 3-year degree course. Many of these vocational courses are as good as degree courses and offer employment quickly. Besides, they are best for those students who cannot afford the cost of the degree course.

Career advancement – They are also the best alternative for those people who have a job and want to acquire new skills. Also, the duration of these courses is quite less compared to the degree courses but the set of skills taught is quite useful and important.

Besides, it is quite effective for a professional to improve the prospect of their career. In addition, dropouts and students who are less interested in academic studies can choose from a range of diverse courses in their field of interest.

Economic Development – The demand for skilled professionals in the various sector is growing day by day in the world. In addition, the existence of skilled manpower is beneficial to society as well as the economy of developing nations. With this, the need for importing manpower from other nation is also reduced.

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Growing Need for Vocational Education

The development of nations requires skilled manpower and vocational education prepares them for the job. Also, the demand for skilled labor has increased manifold in both the business and government sectors. Furthermore, over the year the vocational education has diversified immensely.

Moreover, vocational courses come as a surprise package as students get the opportunity to enhance and get trained to improve their natural talents and skills. Besides, they become highly successful in their field and fetch good packages.

In conclusion, the students who complete these courses are better at a job than those who only receive an academic education. Also, it is an asset of the country that helps the economy to develop and grow. In addition, there is a high demand for these skilled people in both the government and the business sector. Above all, it benefits students, society, nation, and employers.

FAQs about Essay on Vocational Education

Q.1 How vocational education is different from traditional education? A.1 In traditional education the main emphasis is on teaching and learning of theoretical materials. But vocational education emphasizes on learning and teaching of practical knowledge. Also, vocational education makes the person job-ready.

Q.2 Who is the father of vocational education? A.2 Charles Allen Prosser is known as the father of vocational education. His aim was to improve the education system of the country which later reforms the world.

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Why Skills Training Can’t Replace Higher Education

• George D. Kuh

It’s a disservice to students and civil society.

One of the dominant narratives in the media is that we need to produce more workers now who can do whatever is needed now, using short-term post-secondary certification programs. The focus is typically on “vocational” skills, contrasted with what too often are characterized as relatively useless liberal education outcomes. Of course, short-term vocational skills-based programs are critically important and well suited for many people. But this is not an acceptable policy choice for addressing the demands of the 21 st century workplace and fixing the shortcomings of American higher education. Abbreviating post-secondary preparation programs may well reduce short-term costs for students, institutions, and many employers. However, privileging short-term job training over demanding educational experiences associated with high-levels of intellectual, personal, and social development — a foundation for continuous life-long learning — is a bad idea for individuals, for the long-term vitality of the American economy, and for our democracy.

Much of the current media-reported posturing by policy makers and pundits about the failure of U.S. colleges and universities to adequately prepare people for the 21 st workplace is either ill informed or misguided, in my opinion.

• GK George D. Kuh is the Chancellor’s Professor Emeritus of Higher Education at Indiana University, and a co-author of Using Evidence of Student Learning to Improve Higher Education .

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• Trends in Education

The importance of vocational training for career development

May 16, 2024 •

9 min reading

When it comes to finding a job and encouraging emerging professionals to excel in their new career path, making sure that graduates have the skills they need for the position plays an essential role. Students who do not have the necessary skills will quickly find themselves struggling in their new position. They may start to lose confidence and feel unsure about what to do. The businesses that hire them will also feel frustrated as they lose money and time. They find themselves training new employees who do not have the insight and practical knowledge they need to do what they were hired to do.

What is Vocational Education?

Let's delve into the essence of vocational education . The term refers to specialized programs that are crafted to equip individuals with the necessary skills and training for a specific profession or career path. By undertaking these courses, students not only acquire vital vocational skills essential for future employment but also gain foundational knowledge akin to what is typically learned during high school.

"Vocational education and training, allows students to gain practical experience in their chosen career path before they even graduate."

Students who finish those rigorous programs have the credentials and training they need to get started right away in their chosen career path.

Not only do the students feel confident in their abilities, but the employers themselves know that they have made a solid choice in their new hire and can count on them to begin excelling in the position quickly.

In today's competitive job market, there is a noticeable disparity between the number of job openings and the skills possessed by potential candidates. The growing demand for specialized skills has prompted experts to acknowledge that many individuals may struggle to meet the criteria required for these positions. Undoubtedly, vocational education plays a crucial role in bridging this gap and preparing individuals for successful careers.

For those interested in the benefits of vocational education for job training and career preparation, here are some of the key positives for both students and employers with this type of career preparation path.

Skill development and employability

Vocational learning opportunities play a critical role in skill development and employability. The importance of vocational development can largely be summed up as the difference between theoretical knowledge vs. practical skills. In non-vocational studies, students often spend hours of their time exploring a variety of different subjects. Their class time tends to be only a few hours per week, as they will spend many hours in the library and on computers conducting research and writing papers that help them continue to build their theoretical knowledge in a variety of fields.

Even within their chosen discipline, they often spend a significant amount of time exploring theories, ideas, and procedures used by other professionals in the industry. They have significantly fewer opportunities to put these ideas to work compared to students going through a vocational education situation. The skills for work and vocational pathways are significantly limited for these students, as their theoretical knowledge does not have the work experience that helps them transition from a classroom study topic into their actual profession. This can sometimes cause challenges when the students graduate and transition into the working world.

However, for students in a vocational education and training setting, this situation gets corrected. Students spend hours in the practical workshops each week learning hands-on practical skills related to their chosen field. Class time tends to increase in these schools, compared to their outside research time, because students spend more time exploring actual work opportunities that prepare them for their future jobs. They do not focus as much time on researching the theoretical as learning the practical.

Students also have courses that will walk them through chances to use the highly specialized equipment and spaces that they need to do their jobs well. Rather than simply learning about this type of equipment or how it might be useful in the job, they have the chance to try out their skills while still in school. When the time comes for them to transition to an actual job, they have the experience they need to begin the job right away. They will not have to spend time learning how to physically operate the equipment on the job, allowing them to become a valuable employee and build a careers faster.

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The value of graduating with work skills.

When employers look for new employees to join their institution, they know that they want to find someone who has the skills to do the job well and can adapt quickly to the work environment. Businesses spend a significant amount of money trying to onboard new employees, as they must go through a training process and anticipate that there will be a learning curve for the employee on a new job.

Vocational schools help with bridging the skills gap between work and education.

Students do not enter the work field with little practical experience regarding the tools and environments in which they will work. Instead, they have specifically worked in these situations throughout their education under the supervision of their trainers. This creates a more favorable employability skills assessment. Potential employers can look at the academic record of these students and know the type of skills they will already have when they first enter the building. This effect can be leveraged even more when a training institution is applying a competency-based training approach that is mapped with the industry's needs.

For those interested in learning how to enhance employability skills, therefore, the first solution should lie in vocational learning opportunities. These skills can help students learn the techniques and strategies that they specifically need for this area of work and ensure that they are prepared to succeed. Employers can feel confident that the candidates they receive from a quality school already have the experience and training they need to begin work right away.

Finding a job following graduation

Many graduates struggle to find employment immediately following graduation. It can be a stressful time for many students, trying to balance their last few months of studies as they begin to submit applications and search for positions in their chosen field of work. For students who have graduated from a vocational training school, however, this situation can go a bit differently. They have the experience to list on their resume and employers know they have a significant portion of the training they need. Often they even have started building a professional network through their job placements and internships they could potentially leverage. This helps to open doors to new possibilities.

Graduates often want to know how they can enhance their employability opportunities. The answer lies in gaining the work experience that employers want to see. Bringing this experience can make it significantly easier to find a job. Experience gives employers more insight into how a candidate will perform on the job and how many resources will need to be dedicated to training a new hire for the job. For vocational students, these work experiences become part of the curriculum.

Throughout the studies, students gain hands-on opportunities through internships and practical learning opportunities. Completing real work projects, as they do in a variety of classes, helps students build employable resumes before they even graduate.

Building strong networks for students before graduating

In nearly any industry, the importance of a strong network can play a direct role in finding a job and building a successful career. Connections and relationships can help people find new jobs, learn about new opportunities, and have chances to continue their education and build more career-based skills.

Through a vocation-based education, students have an excellent opportunity to build a strong network that will enhance their learning experience and the rest of their professional careers. With a vocation-based training program, students work more closely with their fellow students and their trainers on their coursework. Since less time is spent independently researching and writing papers and more time is spent in class working on projects and learning practical skills, students naturally develop better and closer relationships with their classmates. Their fellow students transition from being people they simply sit next to in the lecture hall into partners with whom they work during projects and internships.

Similarly, students have more opportunities to get to know their professors. With skills-based training, students work more directly with their trainers. The hands-on opportunities they have to work during their coursework let them complete projects, engage with work tasks, and learn specialized techniques under the direct supervision of the trainer. Trainers are there to provide support and students have opportunities to speak with them and engage with more one-to-one time. This builds relationships and can help students find professional mentors for the transition to the business world. Through internship opportunities, students expand this relationship horizon into the work world, even before graduation.

Altogether, this type of practical classroom experience helps those learning in a vocational training program develop a strong professional network that will benefit them throughout their entire professional career. They will have people who can provide them with insight and guidance as they build a career and find the jobs they want.

Students experience economic benefits

Students who go through vocation-based schooling also have the chance to receive a variety of different economic benefits from their education.

Most importantly, they often do not have to spend as much on their schooling while still receiving an education that prepares them exceptionally well for their field. Vocational schools often have fewer years required to earn the degree of certification and often cost less in tuition each year as well.

Additionally, students who graduate from specialized programs like this can enter their career path faster. Employers know that they already have work experience and training related to their field, which makes it easier to transition into the desired role and takes less of a toll on the business working to onboard them. Students can accept more specialized jobs and earn the applicable salary as well. This combines to create a strong economic opportunity for graduates from vocational programs. Vocational graduates also tend to have a good toolset to rise through the ranks rapidly as they know the trade inside out. Another financial aspect is the "earn as you learn" that many vocational training paths offer. Here students can earn some money and hence reduce the financial impact of their studies through paid internships as part of some curricula.

When it comes to educating students, the importance of building skills-based education cannot be underestimated. Students who attend schools that specialize in teaching them skills that they need to excel in a particular field will find that they finish school well-prepared to enter their chosen field. They gain on-site work experience throughout their education so the transition to the working world is minimal, helping them professionally and financially. The businesses that hire them know that they can count on their new employees to get started immediately in the field and work with a high level of independence and competency, creating a favorable experience for everyone involved.

Those interested in pursuing a vocational pathway for their education and a career in one of the many exciting trade areas these types of schools serve should carefully consider if the benefits described here will help them in their chosen field.

Head of Vocational Education & Training by EHL & Consultant - EHL Education Consulting

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• Open access
• Published: 16 November 2020

Does tertiary vocational education beat academic education? A matching analysis of young men’s earnings developments

• Veronika Lukesch 1 &
• Thomas Zwick   ORCID: orcid.org/0000-0003-4032-1995 1 , 2 , 3  

Empirical Research in Vocational Education and Training volume  12 , Article number:  16 ( 2020 ) Cite this article

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This paper shows that young men who completed an apprenticeship education plus a tertiary vocational education have considerably higher earnings during the first half of their career than those who obtained an academic education in addition to their apprenticeship education. We match employees with a tertiary vocational and an academic education based on their labour market experience and their individual and employer characteristics during their formative apprenticeship training years in which they presumably decided on their further education track. Then we compare the earnings developments in both groups of the matched sample during their tertiary education phase and after its completion for maximally 16 years after apprenticeship completion. We use linked employer-employee data of the IAB (LIAB9310).

Introduction

There is a lively debate on differences between the returns of vocational in comparison to academic or general education (Eichhorst et al. 2015 ; Hanushek et al. 2017 ). It is however frequently overlooked in this debate that apprenticeship training does not equate to streaming into vocational education at the secondary level because a considerable share of former apprentices moves on to academic education in many countries (Ryan 2001 ). Besides academic education, many apprentices obtain vocational tertiary education. Vocational tertiary education however is comparable to academic education with respect to duration and is sorted into the same level in most professional classifications (OECD 2015 ).

This paper compares accumulated earnings of employees with a vocational tertiary education to academics when both groups have a completed vocational training on the upper secondary level. The comparison allows the assessment of the market value of vocational and academic education for relatively homogeneous groups of employees. Besides having a comparable education history, employees in both comparison groups have the ambition to add a higher education after having obtained an occupation that gives access to the skilled labour market (Rzepka 2018 ). Homogeneity of academics and employees with vocational tertiary education with respect to career orientation and schooling efforts allow us to effectively control for the endogeneity of educational path choice. The earnings differences we calculate therefore can be interpreted as causal effects of differences in the choice of the education path. So far, most comparisons of the returns to education of vocational and academic education are on secondary education or they do not take into account differences in the prestige and selectivity of vocational and academic education (Verhaest and Baert 2018 ).

Besides calculating the earnings differences in vocational vs. academic education, the question whether tertiary vocational education is an attractive alternative to academic education also is important in its own right, however. The group of those with completed apprenticeship training who are interested in a tertiary education and have the choice between vocational and academic education track is large and growing in Germany (Rzepka 2018 ).

Our contributions to the literature on the returns to academic versus vocational training are: first, we address the selection bias into academic vs. vocational tertiary education by identifying and using comparable homogeneous employee groups that are matched on individual labour market value during apprenticeship training. Second, we calculate the returns to tertiary vocational education in comparison to tertiary academic education in a lifetime earnings approach using detailed administrative earnings spell data for the first half of the employees’ career. Third, we contribute to the discussion of the labour market acceptance of vocational careers in comparison to academic careers at the tertiary education level by comparing institutional differences between both education paths.

The paper is structured as follows. “ Tertiary vocational education ” describes the institutional background of tertiary vocational education in Germany. “ Data, sample and description ” presents our data and sample. “ Empirical method ” discusses our empirical method to calculate differences in lifetime earnings of employees with tertiary vocational and academic education. The results of the earnings comparisons are presented in “ Results ”. In “ Robustness Checks ”, several robustness checks are shown. “ Discussion ” discusses our results and concludes.

Tertiary vocational education in Germany

This paper calculates differences in earnings for people with tertiary vocational and academic education. In order to compare earnings of a homogeneous group of employees, we only include employees who in principle could have chosen both education tracks. More specifically, all employees in our sample completed an apprenticeship on the secondary level that is necessary to start with a tertiary vocational education and that is used by a substantial share of academics as a first degree before their tertiary education. The typical course of career events for people in our sample is depicted in Fig.  1 . In order to understand our sample of employees better, we first characterize the German vocational training system with its secondary and tertiary education levels.

Relevant career phases

The dual apprenticeship training system is an important and successful component of the German education system. Apprenticeship training in Germany traditionally provides general and vocational education at the upper-secondary level for the majority of the German workforce and it therefore is the backbone of medium-skilled occupational training. Until the year 2012, the highest occupational level of more than 50% of the German population was a completed dual apprenticeship. In 2016, this share slightly fell to 47.2% (Autorengruppe Bildungsberichterstattung 2018 , Table B5-4web). We have to take into account that in addition to about half of the population with a completed apprenticeship “only”, a substantial share of people with a tertiary education also completed an apprenticeship. This paper concentrates on the group of people with a completed tertiary education after their apprenticeship because providing career perspectives for employees who completed apprenticeship training is crucial to keep the apprenticeship system attractive and improves the pool of applicants for apprenticeship training.

The tertiary vocational education certificate (in Germany frequently called, “ Meister ” or “ Techniker ”) is a widely recognised education that allows a career in the framework of the German vocational education system. Around 20% of apprenticeship completers obtain a tertiary vocational education certificate. Footnote 1 In order to be allowed to attend tertiary vocational education, it is necessary to have completed an apprenticeship. The tertiary vocational education certificate guarantees general and transferable skills and it is granted by independent public bodies, the chambers of commerce and the chambers of craft. The certification therefore is analogous to apprenticeship training at the upper-secondary level, compare Acemoglu and Pischke ( 2000 ). The most important trait of the apprenticeship system is that the certificate is well known to most employers. In addition, the education contents are standardised and transparent, leaving the employer that contributed to education and their costs after completing foremen education is costless and possible directly after completion. Also analogously to apprenticeship training at the secondary schooling level, the costs for the foreman education are jointly borne by the state, employer and the employees. Footnote 2 The state subsidises occupational schools and the certification bodies. In addition, analogously to means-tested subsidies for students, there are also subsidies for tertiary vocational education. Footnote 3 About half of the foremen used public subsidies, mainly the Federal Training Assistance ( Aufstiegs-BAföG ) in the period 2012–2017 (DIHK 2018 ). The employers may provide practical training of those in tertiary vocational education at their own costs, about 30% of foremen received financial or other support from their employers (DIHK 2018 ). The employees either reduce their working hours (part-time education) or they stop altogether with their work (full-time education). In addition, they have to pay considerable education fees.

As an alternative to a vocational career, many apprenticeship completers also have the option to obtain an academic certificate from a university or a university of applied sciences. More than one fifth of apprenticeship completers already has a university entrance certificate ( Abitur ) (Adda et al. 2013 ) and this group can study at an academic institution directly after completing apprenticeship training or after a work spell without additional requirements. In addition, there are mainly two pathways for non-traditional students who are vocationally trained but do not have sufficient schooling to get direct access to academic education: they either take Abendschule (evening school) during or after apprenticeship training or an entrance exam provided by the academic institution for applicants with completed vocational training but without Abitur (Wolter et al. 2014 ). Footnote 4 Reasons mentioned for obtaining an apprenticeship certificate before an academic study are risk reduction (Büchel and Helberger 1995 ) and getting occupational practice for the academic job (Lewin et al. 1996 ). Some apprentices also may discover their career orientation during the apprenticeship training.

Tertiary vocational and some academic degrees are classified at the same level according to the International Standard Classification of Education, ISCED 2011 level 6. Footnote 5 The German tertiary vocational education is therefore comparable for example to the polytechnics vocational bachelor degrees obtained in Finland, Norway, the Netherlands (Böckerman et al. 2018 ) or Switzerland (Tuor and Backes-Gellner 2010 ). In 2014, around 40.000 individuals completed tertiary vocational training in Germany (BIBB 2016 ).

Although so many apprenticeship completers in Germany obtain a tertiary vocational education in Germany and the organisation of this education degree is comparable to the well-known dual apprenticeship system at the secondary education level, relatively little is known about the returns to education from it. The obvious comparison group of the effect of a foremen degree on earnings seems to be an academic degree at the same professional certification level.

Previous literature on returns to vocational and academic training

Brunello and Rocco ( 2017 , p. 106) summarize the discussion on differences between the returns to vocational and academic training as follows: “Education economists often point out that individuals with a vocational education face a trade-off between short term benefits and long term costs. In the short term, this type of education facilitates the transition from school to the labour market by providing ready to use skills. In the long term, however, vocational skills depreciate relatively fast and individuals who specialize in these skills are less capable of adapting to technical change than individuals endowed with a more academically oriented education.” The main argument for higher returns to vocational education at the start of the career is that vocational education provides ready to use skills, facilitates the transition from school to work, and therefore leads to a higher labour market value in comparison to general or academic training (Cörvers et al. 2011 ; Wolter and Ryan 2011 ; Fersterer et al. 2008 ). This advantage may however come at the price of vocational skills becoming quickly obsolete in modern economies characterised by rapid technological change (Bennett et al. 1995 ; Krueger and Kumar 2004 ; Golsteyn and Stenberg 2017 ; Hanushek et al. 2017 ; Brunello and Rocco 2017 ). Therefore, there may be a turning point during the career when lifetime earnings from academic education surpass earnings from tertiary vocational education (Bennett et al. 1995 ; Hanushek et al. 2017 ). It remains unclear however how strong the financial advantage of vocational tertiary education is and at which age occurs the break-even point.

Previous empirical contributions found mixed results on the returns to vocational in comparison to academic education. The first group of papers compares the returns to vocational vs. academic education including employees with several education levels. As the vocationally trained have a lower education level on average, the studies usually find higher earnings for those with an academic education in the long run and for lifetime earnings (compare Flake et al. 2016 and Rzepka 2018 for Germany, Hanushek et al. 2017 for a sample of 11 countries). For Switzerland, Tuor and Backes-Gellner ( 2010 ) however do not find differences in net earnings between those who obtained a foreman certificate or a university of applied science certificate and those who obtained a university certificate.

The second group of studies compares returns to education at the same education level and therefore it is closer to our approach. Most of these empirical papers therefore find that more general education contents in a given education track pay off only in the long run in comparison to more vocational contents (if at all), compare Dearden et al. ( 2002 ) for the UK, Bishop and Mane ( 2004 ) and Meer ( 2007 ) for the USA, Fersterer et al. ( 2008 ) for Austria, Cörvers et al. ( 2011 ) for Germany, the Netherlands, and the UK, Golsteyn and Stenberg ( 2017 ) for Sweden, Malamud and Pop-Eleches ( 2010 ) for Romania, Zilic ( 2018 ) for Croatia, and Brunello and Rocco ( 2017 ) for the UK.

Empirical research on the economic effects of education types mainly faces the task of controlling in a credible way the endogenous selection into different curricula and education tracks (Blundell et al. 2000 , 2005 ; Brunello et al. 2017 ). In other words, unobservables may have an important impact on education choice as well as on earnings. Some papers use ordinary least squares wage equations (Blundell et al. 2000 ). They can be interpreted as regression based linear matching (Heckman et al. 1998 ). The control function estimators aim at putting enough structure to completely model the selection decision into the schooling track. Many obvious drivers of earnings potential and career intentions such as motivation or ability are hard to control with this approach, however. Some papers therefore compare earnings of same-sex full siblings (Golsteyn and Stenberg 2017 ) or use matching functions (Rzepka 2018 ) in order to get rid of heterogeneity. Other studies on returns to education use instrumental variables estimators and attempt to control for the correlation between otherwise unobserved individual factors and schooling choices by way of an excluded instrument, which is an education determinant which is independent of earnings (Card 1999 ), compare Hanushek et al. ( 2017 ). The third group of studies uses natural experiments that ideally split homogeneous groups of people in a treatment group with changes in education requirements or options and a control group without these changes. Examples of exogenous variations used to calculate differences in earnings by education path are changes in the compulsory shares of vocational and general content of education (Malamud and Pop-Eleches 2010 ; Hall 2016 ; Zilic 2018 ), the addition of one or two years of compulsory schooling (Pischke and von Wachter 2008 ; Bhuller et al. 2017 ), or the unexpected closure of firms that offered apprenticeship training (Fersterer et al. 2008 ; Hanushek et al. 2017 ).

In order to calculate the earnings differences between vocational and academic education, this paper for the first time combines two important steps that reduce potential estimation biases. First, we only compare vocational and academic education at the same—tertiary—level. Second, for matching it is important that during the period before the treatment decision, treatment and non-treatment pairs are observationally equal. We therefore only compare people who pursue (and complete) an apprenticeship training before choosing tertiary education. Unobservable yet decisive factors for earnings potential and career orientation therefore should be comparable (Dearden et al. 2002 ; Brunello and Rocco 2017 ). Most academics in Germany for example do not have apprenticeship training and therefore do not regard their academic studies as an alternative to a vocational career option. In addition, apprenticeship completers who obtain a tertiary vocational education may not be comparable to the average apprenticeship completer with respect to skills and abilities. We therefore argue that academics with a completed apprenticeship and apprenticeship completers with a tertiary vocational education are more homogeneous comparison groups than all employees with a completed vocational training on the secondary level and all academics. Footnote 6

In addition to the sample reduction on people with completed apprenticeship training, we match employees with a tertiary vocational and employees with an academic education using propensity score matching. We argue in detail in the empirical methods section why using individual, occupation, and employer information from the apprenticeship training period captures the earnings potential of an employee better than using for example test results or other individual characteristics from school age as indicators for earnings capacity.

Data, sample and description

We use the longitudinal Linked Employer-Employee Panel Data of the Institute of Employment Research (IAB) in Nuremberg for a maximum period of 1993–2010 (LIAB 9310). Our observation period of maximally 17 years means that we can construct earnings profiles during the entire first half of the career for many employees after completing their apprenticeship. Our panel data set allows us to separate cohort from age effects. We therefore can control for business cycle effects at the first labour market barrier (start of the apprenticeship), during the tertiary education phase, and after having obtained the vocational or academic tertiary education degree in addition to birth year and age.

Individual social security records are linked with the employer survey of the IAB Establishment Panel. The employer data for example include information about the establishment size, industrial relations, and sector. It seems important to control for employer characteristics because apprentices from small and low-paying training employers might have a different market value and different incentives to obtain a vocational or academic tertiary education than those having obtained their secondary vocational degree from a prestigious, large and well-paying employer (Dellas and Sakellaris 2003 ). In addition, selection into large industrial firms and well-paying apprenticeship occupations is important information on the selection at the first labour market barrier that indicates the labour market value of the apprentice (Soskice 1994 ).

The administrative employee data include information about schooling plus occupational education, daily earnings, occupation, employment spells, apprenticeship spells, and unemployment spells, as well as age, tenure, gender, and work experience (Alda et al. 2005 ; Jacobebbinghaus and Alda 2007 ). The administrative individual data have the advantage that they are essentially free of reporting errors because this information is used to calculate social assistance, earnings taxes, and old age pension entitlements. There might be some problems with the schooling information because this variable might not be updated or reported with errors by the employer (Fitzenberger et al. 2005 ). We take our crucial information on completing tertiary vocational or academic education however from another variable in the data, the so-called “occupational status at the employer” ( Stellung im Beruf und Arbeitszeit ). This variable supposedly is more accurate than the schooling information because it is directly related to the topical work position of the employee. The work position however is more relevant for earnings than education level. Employers have to actively change the information on the work position of employees who have been first classified as skilled employees with a dual apprenticeship after they completed their vocational or academic tertiary level degree and now work in an adequate position for employees with a completed tertiary education. The same reasoning applies for employer changers who have been classified as apprentices or as skilled employees with a completed apprenticeship in an earlier employment spell and later are classified as academics or foremen. Footnote 7 We therefore can be sure that we observe only employees with an adequate position and drop employees from our sample who completed their vocational or academic tertiary level degree but still work as skilled employees at the upper-secondary level or founded their own business. Footnote 8

Another well-known problem of our data set is that we do not observe the number of hours worked per day for people in part-time employment. This information deficit however does not play a big role in calculating lifetime earnings because we are interested in cumulated absolute earnings and not hourly earnings. We therefore also include part-time employment spells. Finally, employees with earnings above the social security threshold have only the threshold reported and therefore right-censored income. As we mainly look at earnings during the first career years, the share of censored income observations is small, however. Footnote 9 We impute true earnings using a procedure proposed by Gartner ( 2005 ). We also check the robustness of our results when we only include observations without censoring.

In a first step, we identify all male apprentices who completed the dual apprenticeship training between 1993 and 2007 (N = 272,439). For this period, we have full information about the training and labour market biography. The restriction of the observation period to the year 2007 is necessary, in order to observe the apprentices with completed education for at least three years after they finished their apprenticeship. Studies have shown that males and females pursue different strategies in selecting educational tracks (Golsteyn and Stenberg 2017 ). Therefore, we only include males within our sample Footnote 10 because most occupations with a large share of foremen are dominated by males, for example those in the metal industry. In addition, we only keep occupations and professions for which vocational and academic education at the tertiary level is possible (e.g. no hairdressers).

The identification of a successful completion of vocational and academic education at the upper-secondary and tertiary level with Social Security Records data requires certain assumptions. The data only entail information on the status as apprentice, which makes it difficult to distinguish between dropouts and successful apprenticeship completion. About two thirds of dropouts however occur within the first year of apprenticeship training (BIBB 2016 ). Therefore, we drop all apprenticeship spells with a training period shorter than 1.5 years to ensure that only successful apprenticeship completers are included within our sample.

In a second step, we restrict our sample to apprentices who either complete tertiary vocational or tertiary academic education (N = 25,191 which is around 9.25% of the original sample). Further restrictions include a minimum age at the start of the apprenticeship of 15 years and a minimum age for foremen of 18 years. Further, we only include individuals who obtain their tertiary education after the apprenticeship. Our final sample before we perform the matching procedure includes 19,275 apprentices who either become foremen (N = 2213) or academics (N = 17,062). Footnote 11

Our spell data allow us to identify with daily accuracy the beginning and ending of the apprenticeship, the first employment spell(s) as skilled employee at upper-secondary level after apprenticeship completion, and the first employment spell(s) as skilled vocationally or academically skilled employee at the tertiary level (see Fig.  1 ).

From the apprenticeship period (decision phase), we determine the exact age at the beginning and ending of the apprenticeship at upper-secondary level, the schooling background of the apprentice, the year of the apprenticeship completion, and the daily wage at the end of the apprenticeship. We use the number of apprentices, the retention rate after apprenticeship training, the average income level within the training establishment and sector, size, and location as indicators of the quality of the apprenticeship training and the attractiveness of the training employer (Soskice 1994 ).

Simple comparisons between our groups of vocationally and academically trained employees including t tests show that employees with vocational tertiary education are about one year younger than academics when they complete their apprenticeship training, they earn a little less at the end of the apprenticeship, they are more likely to be trained in smaller establishments, and the average income level within the training establishment is lower. Footnote 12 All differences of means between foremen and academics within the decision phase on the tertiary education path are statistically significant. These differences point at a lower schooling and ability background of employees with tertiary vocational training in comparison to employees with tertiary academic training at the first labour market barrier (apprenticeship training at the secondary training level).

Our second measurement period is between the completion of the apprenticeship and the first employment as a completer of a vocational or academic tertiary education (education phase). Foremen gain more full-time working experience within this period than academics, they work less in part-time, they spend more days in unemployment and less time outside of the labour market, compare Table 1 . Again, all differences of means are significant and intuitive given that a vocational education on the tertiary level is closer to the labour market than an academic education. Foremen can choose between a full or part-time further education model. The education phase is about one year longer for academics than for foremen although they work less during their education.

Our third measurement period starts with the first employment as academic or foreman (return phase). Foremen are about 1.2 years younger when they start to work as foremen and they are employed in smaller establishments than academics (compare Table 1 ). Furthermore, the average income level of the establishments where foremen start is lower. Again, the differences of means are statistically significant. In contrast, the differences of means of the entry wages as academic or foreman are statistically insignificant.

We want to compare those foremen and academics who had a comparable labour market value and labour market prospects at the start into their labour market career after apprenticeship training. Therefore, we propose a matching method to find suitable homogeneous couples based on individual and employer characteristics during apprenticeship training.

Empirical method

To recover the average treatment effect on the treated, we choose a propensity score matching method (Rosenbaum and Rubin 1983 ; Heckman et al. 1998 ; Smith and Todd 2005 ; Biewen et al. 2014 ; Hanushek et al. 2017 ). The matching method tries to mimic ex-post a natural experiment by choosing a comparison group from among the non-treated such that the selected group is as similar as possible to the treatment group in terms of their observable characteristics (Dehejia and Wahba 1999 , 2002 ; Mueser et al. 2007 ). Our matching variables therefore aim to explain whether an apprentice chooses a vocational or academic tertiary education after completion and earnings during apprenticeship training. After adequately controlling for differences during the decision phase on tertiary education, we can interpret earnings differences after apprenticeship completion as treatment effect of a vocational versus an academic tertiary schooling choice (Heckman et al. 1998 ; Lechner 2002 ).

Although the sample reduction to employees with a tertiary vocational education and academics with a completed apprenticeship strongly reduces unobservable and observable differences in characteristics of employees with a vocational and with an academic education, both groups still show large differences in indicators of earnings potential and career intentions. We therefore use the 1:1 nearest neighbour matching to make foremen comparable to academics with respect to their tertiary education decision and their earnings potential (Stuart 2010 ; Rubin 1973 ; Smith and Todd 2005 ). The basic idea is to identify an academic who is as similar as possible to a foreman concerning all relevant pre-treatment characteristics. during the apprenticeship training period. As our control group is large enough, we perform matching without replacement to ensure, that every academic is matched only once. Footnote 13 After the matching procedure, we have 2079 foremen and the same number of matched academics. Footnote 14

We first assume that the quality of the apprenticeship training employer is an important indicator of earnings potential and career orientation because it indicates selectivity at the first labour market barrier for employees included in our sample (Von Wachter and Bender 2006 ). In Germany, is a clear hierarchy with respect to the attractiveness of apprenticeships and firms thoroughly screen their apprenticeship candidates (Soskice 1994 ; Winkelmann 1996 ). As a consequence, young people with a higher earnings potential and career orientation select themselves into larger and better paying training firms as well as into more attractive occupations and sectors (Soskice 1994 ). We therefore include the apprentice retention rate, size and sector of the training establishment, the number of apprentices, and the average income level in the training establishment are important matching variables.

Second, individual characteristics also reveal earnings potential and career orientation. Our individual indicators during apprenticeship training are occupation, age at the start of apprenticeship training (older apprentices frequently have a better professional orientation), prior education level, and length of apprenticeship period (more demanding apprenticeship programmes take longer). In addition, we use the labour market value of apprentices as revealed by their relative wage position within an occupation (compare Bhuller et al. 2017 ).

Finally, also the business cycle and temporary and regional labour market effects may influence the earnings potential and career decisions. Apprentices in depression phases may have higher incentives for obtaining tertiary education than apprentices with better options on the labour market directly after apprenticeship completion (Dellas and Sakellaris 2003 ). We therefore control for year and location in Western Germany. Footnote 15

Most papers on the returns to education rely on (mainly) cognitive tests or standardised ability test as indicators of earnings potential. Examples of tests are the International Adult Literacy Survey (IALS), the American Forces Qualification Test (AFQT) the Programme for the International Assessment of Adult Competences (PIACC), Intelligence Quotient (IQ) tests results, or the OECD Programme for International Student Assessment (PISA) (Hanushek et al. 2017 ; Bhuller et al. 2017 ; Stenberg and Westerlund 2015 ; Heckman et al. 2018 ). Other frequently used matching variables for earnings potential and career orientation are school grades (Rzepka 2018 ), family background variables including parents´ opinion on education, siblings or twins (Blundell et al. 2000 , 2005 ; Golsteyn and Stenberg 2017 ), the number of books in the household or the economic situation during the schooling period (Card 1999 ; Brunello et al. 2017 ). Basic cognitive ability measured years before labour market entry (such as in AFQT or PISA or the family situation during youth) or during adulthood (such as in IALS) may influence earnings potential and career orientation differently for different education tracks, however. It may be argued, for example, that cognitive skills play a larger role for jobs mainly performed by people with an academic education and non-cognitive skills may be more important for jobs performed by employees with a vocational education (Heckman et al. 2006 ; Kahn 2013 ). Another problem of using cognitive test results in order to control for differences in earnings potential and career orientation is that labour market value also is determined by non-cognitive skills (Heckman et al. 2006 ; Schönberg 2007 ; Kahn 2013 ; Mohrenweiser et al. 2020 ). Footnote 16 The importance of non-cognitive skills for earnings potential means that an important and independent dimension of ability is missing in most test indicators. Heckman et al. ( 2006 ) even argue that schooling and ability test scores obtained during and after schooling are correlated and might induce reverse causality (and therefore biases) in earnings estimations. As a consequence, according to our estimation strategy, also in the public training programme evaluation literature and in the returns to postsecondary education literature mainly earnings, individual labour market experience and labour market characteristics just before treatment are used as matching parameters (Heckman et al. 1998 , 1999 ; Mueser et al. 2007 ; Böckerman et al. 2018 ).

Blundell et al. ( 2000 ) and Blundell et al. ( 2005 ) compare returns to education with and without earnings potential indicators. Footnote 17 They find that the inclusion of family background, demographic and ability test information hardly changes the measured returns to education. The inclusion of topical job information (employer size dummies, union status and a public /private sector dummy) however has a strong impact on education returns. Past wage information therefore may be a better indicator of earnings potential and career orientation than ability indicators obtained before entry into the labour market (Kahn 2013 ). We therefore suggest to use previous earnings and labour market indicators instead of ability indicators from the time before the education is obtained as indicators for earnings potential and career orientation (Ryan 2001 ; Stenberg and Westerlund 2015 ; Biewen et al. 2014 ).

By conditioning on information during apprenticeship training such as market value or employer characteristics for our matching, we also control for state dependence that might be crucial for controlling for endogeneity. Early experience in the youth labour market has consequences for later decisions and labour market prospects (Ryan 2001 ). For example, apprentices in high quality apprenticeship training programmes may have a higher propensity to opt for tertiary academic education than apprentices in small firms.

Although we do our best to control for selection into the educational track, we cannot be sure whether unobserved attributes nevertheless drive the earnings potential and career orientation. As a negative selection by ability into the vocational track will be shown later, the ceteris paribus prediction would be lower earnings for participants if vocational studies had no effect. The earnings advantage of the vocational track is therefore likely to be genuine and may be even larger if selectivity bias could be further reduced (Ryan 2001 ).

We use the sum of earnings added from spell data instead of current earnings patterns constructed from yearly average earnings or earnings at a selected day per year. Earnings sums are the preferred measure of returns to education because they avoid life cycle bias incurred by cross-section estimations, compare Bhuller et al. ( 2017 ) or Brunello et al. ( 2017 ). We use longitudinal spell data covering most of the age spectrum, which allows us to disentangle cohort, age and time effects. We take into account that future income has to be discounted. We therefore adjust earnings for inflation and use a discount rate of 2.4% (Bhuller et al. 2017 ).

Quality tests show that the matching procedure is able to balance the distribution of the relevant matching variables in both the control and treatment group. We assessed the standardised bias as suggested by Rosenbaum and Rubin ( 1985 ). The standardised bias for each covariate is defined as the difference of sample means in the treated and matched control subsamples as a percentage of the square root of the average of sample variances in both groups. One problem of this approach is that there is no clear benchmark indicating the success of the bias reduction. However, if the standardised bias is reduced below 5% after matching, the method is considered effective (Caliendo and Kopeinig 2008 ). Figure  2 presents a graphical comparison of group differences before and after matching.The standardised bias for each covariate is lower than 5% after the matching procedure.

Differences in characteristics between academics and vocationally trained before (2.213 foremen and 17.062 academics) and after matching (2.079 matches.) Note: occupations on a 2 digit level and 24 economic sections are included in our matching, but not shown in the graph

We also control for the matching quality using a two-sample t test to check whether there are significant differences in covariate means for both groups (Rosenbaum and Rubin 1985 ). The tests show no significant differences after matching (see Table 2 for details).

The main finding is that the matched employees´ earnings during their apprenticeship training are equal and we therefore assume that apprentices in both groups have comparable earnings ability.

Figure  3 shows the differences in log daily earnings of vocationally educated compared to their matched academics up to 16.5 years after their dual apprenticeship training (198 months). After our successful matching, there are no significant earnings differences during the apprenticeship period (see months −24 to 0). After the end of the apprenticeship, vocationally educated employees earn significantly more than academics. For example, five years (60 months) after the apprenticeship training, vocationally educated employees earn on average 165% more. Even 10 years after their apprenticeship training, the difference between log wages is still 45%. This big advantage in earnings for vocationally educated is mainly a consequence of the fact that academics have a somewhat longer education phase and therefore start their professional working phase later in life. In addition, during vocational tertiary education chances to be employed are higher than during academic education.

Earnings differences between matched vocationally and academically educated people after completed apprenticeship (N = 2079 matched pairs)

A comparison of cumulative earnings differences in both groups shows that individuals with vocational tertiary education hold a substantial advantage in earnings (the maximum is at 122.000€, see Fig.  4 ). This advantage is higher than several average yearly earnings for both groups and it is only gradually reduced in later career years. Footnote 18 As a consequence of the fact that entry earnings of those who just completed vocational tertiary education are higher than their academic matching partner, on average the turning point from which the earnings advantage starts to get reduced is only reached about thirteen years after the completion of apprenticeship training of the matched individuals (see Fig.  4 ). Even at the end of the observation period of more than 16 years after apprenticeship training, foremen have a substantially higher life time earnings level. More specifically, 16 years after apprenticeship training, foremen on average have an advantage in cumulative earnings of 107.000€ compared to the academically educated employees matched to them.

Differences in cumulative earnings between matched foremen and academics (N = 2079)

If we assume that the decline in the financial advantage of master craftsmen between the years 13 and 16 continues at the same pace, the financial advantage would have disappeared more than 20 years later or about 35 years after the end of the apprenticeship training. The foremen and academically educated employees in our dataset would be 57 years old by then.

Robustness checks

We first compare our main results with a calculation of cumulative earnings without any matching procedure but still using a sample of academics with a completed apprenticeship training as comparison group. Footnote 19 As shown in Appendix Figs.  5 and 6 , the earnings advantage of foremen is a lot smaller (max. 61,300€) and declines already eight years after the apprenticeship training. 16 years after the apprenticeship, the financial advantage of foremen declined to not even 8500€. The big differences between matched and unmatched samples may be a result of the fact, that without an adequate matching procedure, foremen are compared with academics in actually not comparable occupations, at different times in their working career, and without comparable earnings potential already during the apprenticeship.

Earnings differences between vocationally and academically educated people after completed apprenticeship (2213 foremen and 17,062 academics)

Differences in cumulative earnings between foremen and academics after completed apprenticeship before matching (2213 foremen and 17,062 academics)

To make sure that our results are not driven by specific individuals in our matching sample, we also calculate earnings differences of matched sub-samples such as university (732 matches) and polytechnic (1365 matches) academics. The matching in these sub-samples works effectively and we have similar earnings of foremen and their matched academics during the apprenticeship training. The log wage differences pattern looks similar to our results of the whole sample. The comparison of cumulative earnings between university academics and foremen shows that the higher earnings especially at the beginning of their career leads to a substantial advantage of 123.000 € after 10 years and about 166.000€ after 16 years (see Appendix Fig.  7 ). Compared to polytechnic academics, the earnings advantage of foremen is still substantial but lower. After 10 years foremen earn 99.000€ more and after 16 years the earnings advantage is still 83.000€ (see Appendix Fig.  8 ). The sub-sample comparison suggests, that university academics might reach higher earnings than foremen, but later (after our observation phase) in their working careers.

Differences in cumulative earnings between matched foremen and university academics (N = 732)

Differences in cumulative earnings between matched foremen and polytechnic academics (N = 1365)

Additional sub-samples such as vocationally educated employees with highest education at the tertiary level with and without higher secondary schooling background ( Abitur ), apprentices in certain occupations or industries confirm our results (due to sample size restrictions, no detailed results are shown).

As we compare future earnings, discount rates have to be taken into account. Academics have higher earnings later in their career and therefore the discount rate might have an effect on the earnings comparison. We used different discount rates (see the results for zero and 5% discount in Appendix Figs.  9 and 10 ). The results are only slightly affected by discount rates and we therefore chose a discount rate of 2.4% that has also been used in the previous literature (Bhuller et al. 2017 ).

Differences in cumulative earnings between matched foremen and academics with discount rate 0% (N = 2079)

Differences in cumulative earnings between matched foremen and academics with discount rate 5% (N = 2079)

In addition to the nearest neighbour matching method described above, we also compare earnings differences between vocationally and academically educated employees who completed their apprenticeship within the same year, in the same training establishment, and in the same occupation (on a two digit level). In our matching model, we do not use exact matching on these variables and therefore matched employees may come from different employers (we only match on employer size, location and sector, but it doesn’t necessarily have to be the exact same employer) and have different occupations, for example. If we assume that the “formative years” during apprenticeship are decisive for the earnings potential, an exact matching on occupation and employer gives us a more adequate earnings comparison. The robustness check of course has the disadvantage that the number of comparable observations is strongly reduced and mainly comes from large training firms. In our twin sample we have 181 foremen and 350 academics because we only can include establishments with at least two apprentices who end their apprenticeship within the establishment in the same year and in the same occupation. The “new comparison confirms our previous findings and leads to an even higher financial advantage of foremen until the end of our observation period. More specifically, five years after the apprenticeship training, future foremen already earn 182% more than their academic counterpart. Thus, the earnings advantage is 17% bigger than in our previous findings (see Appendix Fig.  11 ). The comparison of cumulative earnings of our new comparison groups shows, that 10 years after the apprenticeship, foremen hold a financial advantage of 117,500€ (almost 10,000€ more than before). Thus, 16 years after the end of the apprenticeship training, the earnings advantage of foremen is about the same as in our matching sample (106,300€ instead of 107,000€). Appendix Fig.  11 reveals that we however get wide confidence intervals in our new comparison because the sample size is small.

Earnings differences between alternative comparison groups (181 foremen and 350 academics)

Policy choices lead to institutional differences in the provision of academic and vocational education and to differences in shares of people who choose one of the tracks and the labour market outcomes of these choices (Hanushek et al. 2017 ).

We match individuals who are as similar as possible during their formative first labour market years, i.e. during their apprenticeship training. We therefore compare earnings of foremen with selected academics who have the same earnings capacity and career intentions during the period in which they decide whether to choose a tertiary vocational or academic education. The rich information about daily earnings plus the high quality matching results during the apprenticeship period allow us to interpret differences in the earnings developments during the tertiary education phase and after the first employment as foreman or academic as causal earnings effects of a tertiary level vocational vs. an academic education for employees in our sample.

This paper shows that employees with a tertiary vocational education earn more during the first years of their career than comparable academics. This is a strong result because it demonstrates that a vocational tertiary education is an attractive alternative to a more general academic education for comparable groups of employees. Our calculation includes the earnings advantages of tertiary vocational education obtained from better earnings opportunities during education and the shorter education period in comparison to an academic education. Our approach therefore deviates from many studies on returns to education that compare earnings levels after the completion of an education track, for example on the basis of the classical Mincer earnings equation. We however think that a life time earnings approach better depicts the relevant individual decision situation of young people who have both options, vocational and academic tertiary education. The vocational career options at the tertiary level also may increase the attractiveness of vocational training at the upper-secondary level given the path dependence in educational choices and advantages (Böckerman et al. 2018 ). Education options at the tertiary level with a strong vocational content could therefore help to avoid that vocational training at the upper secondary level is seen as a dead-end for low achievers such as is frequently the case for example in France, the USA or the UK (Ryan 2001 ). An apprenticeship instead may be attractive for young people who are uncertain whether a vocational or academic track is the right choice for them because they can use it as a career phase in which they can learn about their skills and preferences without giving up the option to get into an academic track (Ryan 2001 ). Tertiary vocational education also could be an efficient alternative for academic training in countries without a developed vocational education system at the level. Vocational tertiary education is relatively cheap in comparison to academic tertiary education (see the Tables B1 in OECD 2008 ) and it nevertheless produces comparable individual returns on the labour market and a comparable productive value on the labour market in the first half of the career. Especially in countries with a weak labour market performance of tertiary educated academics and/or strongly increasing tuition costs and the accumulation of large student debts, tertiary vocational education may be a good education option (Reyes et al. 2016 ).

This paper concentrates on the internal validity of measuring accumulated earnings for people with tertiary vocational training in comparison to academic training. We cannot generalize our findings to the bigger question of the returns of vocational vs. academic training in Germany or the (hypothetical) earnings effect of introducing tertiary vocational training in countries that do not have this option so far. In order to reduce biases of earnings differences to a minimum (rigor), we decided to select a sample of academics with completed apprenticeship training and therefore trade off some external validity of our findings (relevance).

We find that foremen earn significantly more during the first years after completing apprenticeship training than academics. Their financial advantage flattens off relatively fast, however. We show that foremen have on average achieved a cumulative earnings advantage of 122,000€. Even 16 years after the apprenticeship, foremen still have an earnings advantage of 107,000€. We also show that foremen start in an adequate job when they are about one year younger than academics. The age difference until an adequate job after tertiary education is found additionally increases the gap in cumulative earnings academics have to close during their working lifetime.

It remains a topic for future research whether also the lifetime income of foremen is higher in comparison to their comparison group of academics because our data cover only the first 16 years after completing apprenticeship training. If we assume that the reduction in the financial advantage of foremen decreases at the same pace as during the first years after the peak advantage for foremen, we obtain a reduction of the financial advantage to zero at about 57 years of age. Academics with a completed apprenticeship training therefore on average have a higher lifetime income than foremen.

Availability of data and materials

The data used in this contribution (LIAB9310) are publicly accessible at the Research Data Centre (FDZ) of the Federal Employment Agency (BA) at the Institute for Employment Research (IAB) in Nuremberg, Germany.

The shares can be constructed by dividing the number of people participating in further training provided by the chambers of commerce or chambers of craft by the number of people who completed an apprenticeship training, compare DIHK ( 2018 ). The exact figures are 23% for 1995 and 21% for 2017.

A full-time foreman education costs about 5000€, BMBF ( 2019 ).

See https://www.bundesregierung.de/Content/DE/Artikel/2015/10/2015-10-14-dritte-novelle-meister-bafoeg.htm .

Some academic institutions even offer academic education specifically for apprenticeship completers without university entrance exams, for example the so-called cooperative study with integrated apprenticeship training ( Kooperatives Studium mit integrierter Ausbildung ).

Before the introduction of the Bachelor and Master system, vocational tertiary education was classified at the same level as a diploma from Universities of Applied Sciences ( Fachhochschulen ). After the introduction of both academic levels during the Bologna process, they are classified at the same level as a Bachelor’s degree at universities and a Master’s degree at universities of applied sciences.

Concentrating on tertiary vocational and academic education has the additional advantage in comparison to studies on the returns to education of employees with secondary education that the education obtained usually is the highest education. We cannot exclude that earnings later during the career are influenced by differences in learning on the job and continuing training participation. These differences in personnel development are regarded as part of the package included by the education track choice, however. Cörvers et al. ( 2011 ) argue that employees with general training may profit more from training than vocationally trained employees.

For the sake of briefness, we will call those working adequately with vocational degree at the tertiary level “foremen”.

We cannot exclude mis-reporting by employers with respect to occupational status and therefore there might be some employees who are indicated to work in a foremen position without having obtained a formal foremen certificate.

Censored income observations are below 2% in our sample.

Males have relatively stable aggregate labour-force participation patterns. Our sample therefore avoids biases in returns to education because there are cohort-specific changes in work selection by females, see Hanushek et al. ( 2017 ).

The relatively low share of foremen in our sample in comparison to the share of people with a foreman certificate relative to academics with an apprenticeship certificate in the total population can be explained by two specificities of our sample: more foremen than academics found their own business and entrepreneurs drop out of the sample because it only covers employees. In addition, more foremen than academics do not work in an adequate occupational or professional position.

See Table 1 for detailed descriptive information before matching.

Matching with replacement can be helpful in settings with smaller control groups, see Dehejia and Wahba ( 1999 ).

Nearest neighbour matching with replacement and different specifications of kernel matching have been performed. As the results remain robust, we chose the most straight forward 1:1 nearest neighbour matching without replacement.

It has been shown, that the selection of relevant covariates is more important than the selection of the propensity score matching method (Cook et al. 2008 ; Pohl et al. 2009 ; Shadish et al. 2008 ).

Heckman et al. ( 2006 ) for example show on the basis of the National Longitudinal Survey of Youth, 1979 (NLSY79) that non-cognitive skills measured by the Rotter Locus of Control Scale and the Rosenberg Self-Esteem Scale have a comparable impact on for example earnings as cognitive ability measured by the Armed Forces Qualifications Test (AFQT).

They use detailed test scores at age 7 and 11, mother’s and father’s education, age, father’s social class when the child was 16, mother’s employment status when the child was 16 and the number of siblings the child had at 16 and school variables to control for ability.

The earnings advantage amounts to about 4 2/3 yearly entry earnings for academics (27.444€, compare Appendix Table 1 ).

The alternative calculation is based on the sample described in Table 1 .

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Lukesch, V., Zwick, T. Does tertiary vocational education beat academic education? A matching analysis of young men’s earnings developments. Empirical Res Voc Ed Train 12 , 16 (2020). https://doi.org/10.1186/s40461-020-00104-w

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Vocational Education in the United States of America (U.S.A.): The Case of the United States of America (U.S.A.)

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This chapter begins by providing a history of youth and work in the U.S.A.. Next, it offers a brief history of V.E. in the United States. It discusses both positive and negative outcomes of work for youth. It also reviews both government- and non-government related organizations’ input into policy development and curricular design for vocational education. Then, it discusses trends in Career and Technical Education (C.T.E.) participation in the U.S.A. It ends with discussing the standards that guide current career and technical education in the United States.

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Congress established the United States Office of Education, a division of the Federal Government, within the Department of Health, Education, and Welfare in 1867. The U.S. Office of Education sought to advance the country’s educational system. The Division of Vocational and Technical Education in the Office of Education is responsible for administering the vocational education arm of the system, including funding to states.

Between 1870 and 1930, the concept of the “priceless child” emerged in the middle-class community. This idea supported youths’ enrolment in school instead of employment in the labor market (Dreeben, 1968 ).

For example, youth comprised more than 50% of the textile operators in Rhode Island in 1820. Other substantial percentages of youth worked in mills in the south as well (Zelizer, 1985 ).

Whereas less than 5% of the school-aged population graduated from secondary school in 1890, the percentage rose to over 50% in 1940 (Historical Statistics of the United States, 1997). However, these statistics still point to the fact that many families could not afford to or chose not to allow their children to attend secondary school during this period (Kett, 1978 ).

The Joint Apprenticeship Council took responsibility for this.

Retail and service sectors offered the most interesting opportunities for youth at this time.

YouthBuild trains participants for construction opportunities.

Another example is Wagner-Peyser employment services which match youth with employment.

With both public and private institutions of higher education struggling based on both the slow economic and the effects of the Covid-19 crisis, institution of higher education are grappling with the possibility to offer short-term certificate programs in a variety of fields. The programs seek to increase enrollment, offer necessary certificates for work, and strengthen the financial state of the institutions.

Forty-six percent of students are at least at 22 and are working part-time.

A program evaluation of the Project QUEST program found that “…participants earned significantly more than equivalent control group members who were not randomly selected into the program. By year nine, this gap was over $5000 per year in additional earnings for graduates of the program.”

A survey by the U.S. Government Accountability Office cited by MIT’s the Future of Work report (2020) highlighted the importance of job training programs that help to match those seeking jobs to jobs in local communities (Autor et al., 2020 ).

Single- and multiple-country studies offer great potential to understand youth’s vocational development across cultures. The case studies in this book address one facet of this discussion.

Stress at work also negatively affects adolescents’ decision-making capability.

Unlike nationalized educational systems in other countries, each state determines the types and number of vocational education programs.

Schools phase out programs that lose enrollment.

Those jobs do not require a baccalaureate degree.

China experiences the same problem.

Study Abroad programs like that at St. John’s University in New York also provides students with this student teaching situation in which students earn credit by working with teachers and students in local schools in Rome, Italy.

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500 Words Essay on Importance of Vocational Education

Vocational education, also known as technical education, has gained significant attention in today’s rapidly evolving job market. It is an education that directly prepares individuals for a specific trade, craft, or career, offering a practical alternative to traditional academic paths. This essay will delve into the importance of vocational education, highlighting its benefits and its potential impact on the future workforce.

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The significance of vocational education extends beyond individual benefits. It plays a vital role in shaping the future workforce. As industries evolve, the need for specialized skills grows. Vocational education, with its emphasis on practical skills, ensures a steady supply of skilled workers, capable of adapting to the changing demands of the job market.

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The study aims to analyze the leading researchers of vocational education and training from dimensions of individuals, institutions and countries. This article utilises the scientific information measurement software—CiteSpace—to conduct a scientometric analysis of 2,024 articles on vocational education and training from the Web of Science (W.o.S.). According to the research results, some useful conclusions can be drawn as follows: (1) vocational education and training research has become interdisciplinary and subject involved are “psychology”, “sociology”, “economics” and “pedagogy”; (2) the United States, the Netherlands and Australia make the majority of contributions and there are numerous collaborations among countries; (3) Univ Amsterdam, Univ Utrecht and Univ Melbourne were the main research institutions; (4) J Vocat Educ Train, Rev Educ Res, Thesis Elev, Econ Educ Rev and J Educ Work were the top 5 highly cited journals; (5) “Engagement”, “Program”, “Self-efficacy”, “High school”, “Predictor” and “Labor market” have become major research hotspots currently.

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Introduction.

Nowadays the importance of vocational education and training has been highlighted by the rapid economic and social development with relatively mature vocational education and training systems established in countries like the United States, Germany, Australia, the United Kingdom and the Netherlands. Subsequently, researchers with academic backgrounds in economics 1 , 2 , 3 , management 4 , 5 , 6 , and information technology 7 , 8 , 9 around the world have paid close attention to the courses 10 , 11 , professions 12 , entrepreneurship 13 , 14 , skills 15 , 16 and evaluations 17 of this field.

Social changes are manifested in greater mobility of workers, shifting labor markets, frequent changes of professions, the disappearance of several professions and the emergence of new ones 18 , 19 . The emergence of artificial intelligence tools, which are transforming the entire landscape of the labor market, is becoming a significant risk and challenge. The need to learn constantly and throughout life and the instability of professional development make vocational education and training the most important and defining sector of education 20 , 21 . Many researchers agree that its role will constantly grow and cover all sectors of professional implementation 22 , 23 . Bibliographic analysis of the field of research in the field of vocational education is rapidly evolving, but there are fewer review works on this sector than it requires 24 .

Vocational education and training are studied from the point of view of assistance from the state administration or municipalities in the retraining of employees 6 , 16 ; many country case studies provide insight into the differences in the educational context of individual countries 2 , 3 , 11 , 14 . Experimental studies on combining vocational education and work or other types of employment make it possible to assess the potential of problems that require solutions 25 , 26 , 27 . The use of technical and digital tools within vocational education is also being devoted to more and more research 9 , 28 , 29 .

The existing research results have laid an important foundation for the reform and development of vocational education and training. However, vocational education and training still have a series of problems that need to be solved, such as the large gap between the skill supply of vocational education and the skill demand of the labor market, and the low enthusiasm of enterprises to participate in vocational education and training 4 , 9 . In addition, although many scholars use a variety of research methods from different dimensions to explore related issues of vocational education and training, few studies have investigated vocational education and training comprehensively and systematically 23 , 30 . There is an urgent need for bibliometric analysis to identify areas of development, areas of greatest interest among researchers, and stratification of research by country, institution, and area. This will allow the efforts of new researchers to be more targeted and their quality improved.

The objectives of this study are as follows:

Analyze the leading researchers of vocational education and training from dimensions of individuals, institutions and countries;

Figure out the distribution of journals related to vocational education and training;

Delve into the main research topics and knowledge structure in this field;

Aggregate the research hotspots and frontiers in this field.

The data used in the study were obtained through advanced retrieval from the Web of Science Core Collection (WOSCC): "Science Citation Index Expanded (SCI-E) (2004–2020)"; Social Science Citation Index (SSCI) (2004–2020)"; "Conference Proceedings Citation Index-Science (CPCI-S) (2004–2020)". These data are intended to provide comprehensive, scientific and systematical research on the existing literature related to vocational education and training. The retrieval strategy was as follows: TS = ("Vocational Education" or "Technical and Vocational Education and Training" or "Technical Education" or "Technical and Further Education" or "Technical and Further Education" or ((VET) or (TVET) and (education))), and with language options of "English" and literature type selection "Article". Here VET is the "Vocational Education and Training" abbreviation and TVET "Technical and Vocational Education and Training" abbreviation.

Indeed, 644 data sources were retrieved from SCI-E, 697 from SSCI, and 693 from CPCI-S. A total of 118 duplicate articles were identified. The cleansing of a sample of data sources was carried out manually by carefully studying the content of abstracts and excerpts from the sources or full versions if they were available. Finally, a total of 2,024 bibliographic citations were obtained (Fig.  1 ).

Literature related to vocational education and training from 2004 to 2020.

Research tools

Information visualization is the process of representing and visualizing abstract data with the help of computer software, which can enhance researchers' perception of abstract information 31 . Based on the existing literature, visualization analysis can adopt the method of dynamic graphic visualization to reveal the trends, hotspots and frontiers of scientific research. Therefore, information visualization can facilitate researchers to understand and predict the frontiers and trends of scientific research opportunely and break new grounds for new ideas amid complex information.

In this study, the analysis software CiteSpace 5.7 was used to conduct research cooperation, cited references and co-occurrence analysis of keywords in literature pertinent to vocational education and training. CiteSpace is an important software in bibliometrics 32 . CiteSpace visualized knowledge maps can be used to identify, display and predict research trends and elucidate knowledge structure and development 33 . Therefore, CiteSpace's visualized knowledge map was adopted in this study to analyze literature in the field of vocational education and training. The analysis elements included Author, Institution, Country, Cited authors, Cited journals, Cited journals, and Cited references.

A network of cited references, co-authors and keywords co-occurrence can represent the scientific knowledge domains 34 . The network provides a systematic and scientific description of the evolving field of scientific knowledge through knowledge mapping, a novel method of literature analysis, enabling researchers to better understand knowledge structures, research collaborations and the hotspots and trends of research 35 .

Research process

In this study, a visual analysis of the bibliography of vocational education and training was conducted through CiteSpace. The research process was as follows: Firstly, the basic knowledge cluster of vocational education and training was constructed according to the reference literature of the field. This cluster is necessary for the next steps to identify the main clusters in the knowledge graph and highlight the most influential literature in this field of knowledge. Also, the basic knowledge cluster will help to study the evolution of each cluster, and future trends and identify key literature from a timeline perspective.

Secondly, the hotspots and frontiers of vocational education and training can be identified based on the frequency of the keywords in the related literature. Meanwhile, keyword bursts can also reveal the evolution of vocational education and training and determine the latest research trends. Burst refers to the significant change in the value of a variable over a relatively short period, which is adopted by Citespace to identify research frontiers.

Finally, the researchers, research institutions and countries were visualized to identify the major contributors to the evolution of knowledge in vocational education and training.

Research limitations

The results obtained may be limited to searching only the Web of Science Core Collection (WOSCC) database, without considering Scopus or other relevant data sources. Also, the sample may not contain sources that directly relate to the topic under study but did not use the corresponding keywords in the article description or other identifiers, and this happens.

Knowledge clustering of vocational education and training research

The emergence and development of any new knowledge are based on existing research and findings, and so are vocational education and training. In general, the frontiers of research in a particular discipline can be represented by journal papers to a certain degree, and the cited references form the knowledge base for the journal paper. The important references can be clustered and the co-cited clustering can be determined with the help of specialized computer software, an important step in figuring out the knowledge base for vocational education and training.

The distribution of selected bibliographic citations by year is presented in Fig.  1 and Table 1 . First, one should evaluate the relatively uniform growth in the number of works devoted to the topic under study throughout the entire period under study. The only exception is the sharp increase in the number of studies in 2012.

In Eq.  1 \({c}_{ij}\) represents the number of co-occurrences of i and j, \({s}_{i}\) is the frequency of occurrence of i, \({s}_{j}\) is the frequency of occurrence of j.

After running CiteSpace, the knowledge mapping was obtained.

Cluster names related to the field of vocational education and training were extracted with the application of MI (Mutual Information). The formula is calculated as Eq.  2 , where \({g}_{st}\) is the number of shortest paths from node s to node t; \({n}_{st}^{i}\) is the number of shortest paths through node i among the \({g}_{st}\) shortest paths from node s to node t. 166 clusters were generated based on the co-primer clustering information with 10 main clusters.

Modularity Q is a measure of visual networks ranging from 0 to 1. The formula is calculated as Eq.  3 ; \(P(w|{c}_{i})\) is the co-occurrence probability of w and c, \(P(w)P({c}_{i})\) is the frequency of occurrence of w, \(P({c}_{i})\) is the frequency of occurrence of i-type values). The higher the value, the better the network clustering. In general, Modularity Q ranging from 0.3 to 0.8 indicates that network clustering is acceptable. Weighted Mean Silhouette S is a homogeneous indicator of network clustering ranging from − 1 to 1. The larger the Weighted Mean Silhouette S, the higher the clustering homogeneity. In general, Weighted Mean Silhouette S below 0.5 means that the clustering results are acceptable, and above 0.7 means that the clustering results are more reliable 36 . Figure  2 shows the Modularity Q value of 0.392 and the Weighted Mean Silhouette S value of 0.9641 for the visual network in the field of vocational education and training. Weighted Mean Silhouette S values of all 10 major clusters are above 0.8. The above data demonstrate that knowledge mapping is a high-quality clustering of the knowledge domain of vocational education and training.

Co-cited literature clusters.

Table 2 further provides a more detailed description of each of the knowledge clusters depicted.

It can be concluded from Table 2 that Vocational Interests (#0) ranked first in the knowledge cluster that includes job quality, linkage, occupation, completion, ring-biased Technological change, Labour market entry and dual training system, including 62 literature, most of which were published around 2014. The Weighted Mean Silhouette S value of the cluster is 0.966, indicating the high homogeneity of the 62 literature in the cluster. Among them, General Education, Vocational Education, and Labor-Market Outcomes over the Life-Circle, by Hanushek et al. 37 on Journal of Human Resources , are the articles with the highest citation (60% of the articles in this cluster cited this article); Vocational Education and Employment over the Life Cycle by Forster et al. 38 on Sociological Science , ranks the second (34% of the studies in the cluster cited this article); Educational Systems and the Trade-Off between Labor Market Allocation and Equality of Educational Opportunity by Bol and Van de Werfhorst 18 on Comparative Education Review ranks the third (27% of the studies in the cluster cited this article).

The second clustering is Workplace Simulation (#1) with 55 articles, and the Weighted Mean Silhouette S value of the cluster is 0.879. The most cited article was Students' Learning Processes during School-based Learning and Workplace Learning in Vocational Education: A Review by Schaap et al. 40 on Vocations and Learning . Forty percent of the studies in the cluster cited this article. The third cluster, Task Shifting (#2), consisted of 42 articles. The Weighted Mean Silhouette S value of the cluster is 0.967, a high homogeneity. The detailed information of each major cluster is shown in Table 3 .

In addition, widely recognized studies can be identified based on the number of citations. The top 3 studies with the highest citations (over 20 citations) are as follows: General Education, Vocational Education, and Labor-Market Outcomes over the Life-Cycle published by Hanushek et al. 37 on Journal of Human Resources (37 citations); Students' Learning Processes during School-based Learning and Workplace Learning in Vocational Education: A Review by Schaap et al. 40 (22 citations) on Vocations and Learning ; Vocational Education and Employment over the Life Cycle by Forster et al. 38 on Sociological Science (20 citations).

Given the lack of expansion of the thematic field of research after 2013, as shown further in tables, it can be assumed that the Vocational Interests knowledge cluster has focused the most interest of researchers and perhaps provided the most topics for further in-depth research. It is the state of the labor market and the relationship with employment that has received the most attention. researchers in connection with vocational education.

Distribution of countries

The number of papers published by different countries and their academic influence can be elaborated on in Table 4 . It can be inferred that the United States was the most productive among the top 10 countries followed by the Netherlands and Australia in the field of vocational education and training with 260 papers published from 2004 to 2020, accounting for about 14% of all literature. However, China ranked sixth with 88 papers, accounting for 4.8% of all papers, far lower than that of the United States. In terms of betweenness centrality value, the USA (0.67), England (0.36) and Germany (0.27) ranked in the top three, indicating a significant academic influence on the field of vocational education and training. Betweenness centrality indicates the strength of a node's influence on the flow of information in the graph. This is a measure of the influence of a separate node in a whole network 33 . The United States ranked first regarding the academic influence in the field of vocational education and training research while China is still in a relatively disadvantaged position. A more complete visual representation of the distribution of academic influence by country is presented in Fig.  3 .

Network of countries distribution for VET.

Burstiness (Table 4 the last section) is an increase and decrease in activity or frequency of publications that disrupts the continuity or pattern of distribution. In this case, the higher this indicator, the more uneven the participation of publications from this university in the research field being studied. The Burstiness results of countries more active in the field of vocational education and training (Table 4 , Burstiness section) showed that: Turkey ranked first with a value of 12.38, followed by England which has been more active in this field. However, although Sweden and New Zealand are not very active in this field, academic attention has been drawn to them.

Distribution of research institutions

In terms of the production of research institutions in the field of vocational education and training, Univ Amsterdam ranked first with 30 articles, followed by Univ Utrecht (28 articles) and Univ Melbourne (22 articles) (Fig.  4 ).

Network of institutions for VET research.

However, the ranking of research institutions based on betweenness centrality demonstrated significant influence from other research centers. The top three universities with betweenness centrality were IZA (0.09), Univ Turku (0.09) and Univ Helsinki (0.07), indicating the importance and influence of these three universities in the field of vocational education and training. Regarding the post surge capacity, Gazi Univ was in the lead with a surge of 5.52, followed by Leiden Univ (5.02) and Univ Utrecht (4.24). See Table 5 for details.

Cited journals

In the citation network of journals, the larger the circle, the higher the citation frequency (Fig.  5 ).

Cited journals network.

Totally 233 pieces of literature on J Vocat Educ Train were cited; 208 on Rev Educ Res ; 181 on Thesis Elev ; and 156 on Econ Educ Rev (Table 6 ).

However, from 2004 to 2020, Thesis Elev ranked first in burst detection with a burst value of 31.74. Other journals with relatively high emergent detection values include SOC SCI Res, Comp Educ, Teach Teach, Econ J, J Labor Econ, etc. These journals mainly come from the fields of psychology, sociology, economics and pedagogy, the source of knowledge in the field of vocational education and training.

Hotspots and trends of the research on vocational education and training

The research hotspot is the focus of researchers' attention shared by a group of interrelated papers in a relatively short period. Keywords are the gist and soul of an academic paper, a highly summarized and refined research problem, and an important index of research hotspots. Therefore, the research hotspots and main characteristics of a certain field can be abstracted from the change in keyword frequency. In this study, "Keyword" was selected from the CiteSpace node types for Keyword co-occurrence network analysis. The larger the node, the more important the node.

In terms of keywords frequency (Table 6 ), related research mainly focused on vocational education and training in vocational education, the transition, inequality, gender, perception, attitude, and the program, work, school, and skill, among which, the keyword "vocational education" ranked first for appearing 399 times, followed by education (234 times) and vocational education and training (181 times). Betweenness centrality higher topics include health, adolescent, perspective, gender, employment, model, etc.

Meanwhile, keyword selection was carried out to clearly show the research hotspots in different years and their interrelation and evolution. Since none of the keywords identified during the study were localized for the period after 2013, we can conclude that the thematic field of research after this time developed almost exclusively intensively, and not extensively, that is, the research hotspots that had already been emphasized earlier were explored (Fig.  6 ).

Timeline of co-citation clusters from 2004 to 2020.

Keywords that appeared more than 25 times were selected and checked for betweenness centrality, as shown in Table 7 .

Compared with previous research 23 , 24 , this research uses CiteSpace V to analyze the research hotspots and research frontiers of vocational education and training from 2004 to 2020, and finds that:

First, the annual volume of research literature is steadily increasing, but the growth rate is relatively low. This is the same as the result of Hui's research 23 . The reasons for this result are as follows: The first is that the academic level and subject status of vocational and technical education are not yet mature, and its knowledge fields and subject boundaries are not clear enough, which causes the subject of vocational and technical education to face multiple identity crises 27 , 28 . The second is that the interdisciplinary nature of vocational education makes its research power scattered in many disciplines such as pedagogy, economics, management, and sociology, while there are fewer academic groups specializing in vocational and technical education 3 , 7 .

Second, from the perspectives of research countries, institutions, authors and journals, the main drivers of research in the field of vocational education and training come from the United States, the Netherlands and Australia, with Univ Amsterdam, Univ Utrecht and Univ Melbourne as the leading institutions. De Bruijn from Utrecht University, Christopher Winch from University of Westminster Univ Westminster, Pietty Runhaar from Deakin University, Martin Mulder from King's College, and Derek G Shendell from Rutgers State University, were the major contributors to vocational education and training. Literature on J VOCAT Educ Train was the most highly cited (233 times), followed by the top five journals including Rev Educ Res (208 times), Thesis Elev (181 times), Econ Educ Rev (156 times) and J Educ Work (150 times). This is different from Yu and Zhou's research results 24 . Through analysis of 719 literature titles, Li proposed that the main research countries for vocational education and training are European countries and the United States 12 . The reasons for the difference between the two may be: The first is the sample size. This study uses 3844 literature titles in the Web of Science database, which has a larger sample size coverage and more effective results; while Li's research has only 719 literature titles and a smaller sample range. The second is the time frame. This research uses 15 years of literature from 2004 to 2020, which represents the latest research characteristics in the field of vocational education and training; while Li uses literature from 2000 to 2009, which can only represent the characteristics of previous research.

Third, in terms of the most popular research topics, growth, vocational education and training, politics, university, secondary education, the environment, China, and other aspects of inequality took the lead from 2004 to 2015, and after 2015 20 , 24 . Other researchers agree with the results obtained in that study showing that the field started to focus on inequality, the teacher, professional development, engagement, program, self-efficacy, high school, the predictor and labor market, among which, the fields of engagement, program, self-efficacy, high school, predictor and labor market are still active and may become future research directions 16 , 24 . This is consistent with Hui's research results 23 . Technological changes and socio-economic development require vocational education and training to gradually shift the focus to students’ cross-industry abilities, and to pay close attention to the dynamic needs of the labor market. In addition, this has a certain relationship with the gradual change of vocational education research from macro to meso and micro.

Although an effective visual analysis of the relevant studies in the field of international vocational education and training from 2004 to 2020 was conducted, the obtained data cannot fully represent the overall picture of the development of international vocational education and training. Limited by research conditions, the related studies of international vocational education and training from the Web of Science were downloaded from 2004 to 2020. Significant potential for future research is to explain the observed spillovers in the influence and contributions of different countries and institutions over significant periods and how they change due to market influences, changes in technology, and other possible factors. Future researchers are encouraged to use a wider range of journals over a longer period.

Conclusions

By drawing the scientific knowledge map of international Vocational Education and Training from 2004 to 2020, this paper intuitively demonstrates the growth law of papers, knowledge sources, author contributions, institutional cooperation and national cooperation in this research field. It also analyzes the research hotspots in the field of vocational education and training, and draws the following conclusions from a comprehensive perspective:

Paper growth law. From 2004 to 2009, the development of Vocational Education and Training research was relatively slow. Since 2010, new Vocational Education and Training research has shown a vigorous development trend. The amount of new media research will reach its peak in 2020. The author predicts that in the future, Vocational Education and Training research will continue to show a trend of vigorous development.

Knowledge source. In the field of Vocational Education and Training, 12 journals have been cited more than 120 times. These journals mainly focus on psychology, sociology, economics and pedagogy. This shows that the knowledge in the field of Vocational Education and Training mainly comes from the above four disciplines.

Author contribution. Hanushek Ea, Forster AG, Bol T, Schaap, Akkerman, McGrath, Brockmann, Kuijpers, Nylund and other highly cited authors have provided high-quality papers and belong to high-impact authors.

Institutional cooperation. The most researched institution in the field of Vocational Education and Training is Univ Amsterdam (30 articles), followed by Univ Utrecht (28) and Univ Melbourne (22 articles), Maastricht Univ (22 articles), and Univ Helsinki (22 articles). On the whole, there is a lack of cooperation and exchanges between institutions, and no large-scale cooperation network has been formed.

Country cooperation. The country with the most research in the field of Vocational Education and Training is the USA (260 articles), followed by NETHERLANDS (251) and AUSTRALIA (217). Although there are many research results in the field of Vocational Education and Training in various countries, the cooperation network between countries needs to be strengthened urgently.

Research hotspots. The relatively high intermediary centrality in the field of Vocational Education and Training is health (0.13), adolescent (0.13), gender (0.1), employment (0.1), and model (0.1). This shows that the above content is a research hotspot in this field.

Data availability

Data will be available from the corresponding author (Xueshi Wu) on request.

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Tian, Y., Liu, J., Xu, X. et al. Knowledge mapping of vocational education and training research (2004–2020): a visual analysis based on CiteSpace. Sci Rep 13 , 22348 (2023). https://doi.org/10.1038/s41598-023-49636-7

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Multiple Health Risk Factors in Vocational Education Students: A Systematic Review

Prince atorkey.

1 School of Medicine and Public Health, University of Newcastle, Callaghan, NSW 2308, Australia; [email protected] (J.B.); [email protected] (C.P.); [email protected] (J.W.); [email protected] (B.B.); [email protected] (F.T.)

2 Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW 2287, Australia

3 Hunter Medical Research Institute, Kookaburra Circuit, New Lambton Heights, NSW 2305, Australia

4 Priority Research Centre for Health Behaviour, Faculty of Health & Medicine, University of Newcastle, Callaghan, NSW 2308, Australia

Judith Byaruhanga

Christine paul, john wiggers, billie bonevski, flora tzelepis, associated data.

No new data were created or analysed in this study. Data sharing is not applicable to this article.

Health risk factors such as tobacco smoking, inadequate fruit intake, inadequate vegetable intake, risky alcohol consumption, physical inactivity, obesity, anxiety and depression often commence during adolescence and young adulthood. Vocational education institutions enrol many students in these age groups making them an important setting for addressing multiple health risk factors. This systematic review examined (i) co-occurrence of health risk factors, (ii) clustering of health risk factors, and (iii) socio-demographic characteristics associated with co-occurrence and/or clusters of health risks among vocational education students. MEDLINE, PsycINFO, EMBASE, CINAHL and Scopus were searched to identify eligible studies published by 30 June 2020. Two reviewers independently extracted data and assessed methodological quality using the National Heart, Lung and Blood Institute Quality Assessment Tool. Five studies assessed co-occurrence and three studies clustering of health risks. Co-occurrence of health risk factors ranged from 29–98% and clustering of alcohol use and tobacco smoking was commonly reported. The findings were mixed about whether gender and age were associated with co-occurrence or clustering of health risks. There is limited evidence examining co-occurrence and clustering of health risk factors in vocational education students. Comprehensive assessment of how all these health risks co-occur or cluster in vocational education students is required.

1. Introduction

Noncommunicable diseases (NCDs) such as cancer, diabetes and cardiovascular diseases are the leading cause of death globally [ 1 ]. Modifiable behavioural health risk factors such as smoking tobacco, inadequate fruit consumption, inadequate vegetable intake, risky alcohol consumption, physical inactivity and obesity have consistently been found to be associated with increased risk of NCDs and mortality from such diseases [ 2 , 3 , 4 , 5 ]. Often, these health risk factors can co-occur or cluster with psychological distress such as depression and anxiety [ 6 , 7 , 8 , 9 ]. Co-occurrence of health risk factors refers to concurrent engagement in two or more health risk factors and clustering refers to the association between co-occurring health risk factors [ 10 ]. Concurrently engaging in two or more health risk factors and clustering of health risk factors increase the risk of non-communicable diseases and deaths compared to no health risk factors [ 2 , 11 ]. For instance, a longitudinal study that examined the combined effect of four health risk behaviours (i.e., smoking, inadequate fruit and vegetable intake, alcohol intake and physical inactivity) among British adults revealed that the risk of mortality was greater among those engaging in all four health risk behaviours compared to those engaging in one health risk behaviour [ 3 ]. Addressing multiple health risk factors may therefore maximise health benefits and result in a greater reduction in health care costs [ 12 , 13 ]. As part of primary preventive strategies to reduce the global chronic disease burden, the World Health Organization recommends approaches that tackle these multiple health risk factors instead of targeting single health risk factors [ 14 ].

Health risk factors often commence during adolescence and become established during early adulthood [ 15 , 16 ]. Vocational education institutions are therefore an important setting to address multiple health risk factors in students because most students who enrol in vocational education are adolescents or young adults [ 17 ]. Vocational education settings include trade schools, technical schools, community colleges, colleges of further education, institutes of technology, apprenticeship training, career and technical education and polytechnic institutions [ 18 ]. Vocational education settings prepare students for specific occupations in trade or craft as technicians, or in professional vocations such as dentistry [ 17 ]. This training can be offered at the secondary, post-secondary, non-tertiary, further education, or higher education level [ 18 ].

The transition into vocational education may be characterised by the individual’s growing independence that may lead to unhealthy lifestyle choices such as smoking tobacco, frequent consumption of fast foods rather than fruit and vegetables, risky consumption of alcohol, inadequate physical activity, increase in body weight, and the experience of psychological distress such as anxiety and depression [ 19 , 20 , 21 ]. Factors such as the cost of healthy foods being greater than unhealthy fast foods [ 22 ], the high cost of using the gym, busy lifestyles, cognitive-emotional factors (i.e., lack of confidence), social smoking and drinking with peers may contribute to multiple health risk factors in vocational education students [ 22 , 23 , 24 ].

Furthermore, vocational education students compared to university students are more likely to engage in health risk behaviours and to experience psychological distress [ 25 , 26 , 27 ]. This may be due to additional competing demands and/or life circumstances as vocational education students are more likely to work full time than university students, have low socio-economic status and be part of minority groups [ 25 , 28 ].

Two systematic reviews have examined clustering of multiple health risk behaviours [ 29 , 30 ], although not specifically within the vocational education setting. The systematic review by Meader and colleagues identified which risk behaviours (i.e., tobacco smoking, low fruit and vegetable intake, alcohol misuse, physical inactivity, illicit drug use, and sexual risk) cluster or co-occur and the socio-demographic factors associated with co-occurrence or clustering of health risk behaviours [ 30 ].

The systematic review by Noble and colleagues examined clustering of smoking tobacco, nutrition, alcohol, and physical activity (SNAP) health risk behaviours and socio-demographic characteristics associated with SNAP health risk clusters [ 29 ]. More than half of the studies included in this review reported clustering of smoking tobacco and alcohol use [ 29 ]. Among the five studies that examined the clustering of health risk behaviours among university students, three studies reported clustering of alcohol use and smoking tobacco [ 29 ]. None of these reviews included studies that examined obesity, depression, and anxiety. Furthermore, none of the existing reviews included studies that examined the co-occurrence and/or clustering of multiple health risk factors among vocational education students.

In relation to young adults, the existing systematic reviews on multiple health risk factors focused on university students but not vocational education students [ 29 , 30 ]. This is despite a substantial proportion of young adults attending vocational education settings and not universities [ 17 ], highlighting a need to also examine multiple health risk factors in this important sub-group of young adults. Therefore, a systematic review that synthesises studies investigating multiple health risk factors among vocational education students is necessary to address the existing gap in the literature and to inform the development of effective health promotion interventions targeting multiple health risk factors among vocational education students. This systematic review aims to examine among vocational education students:

• The co-occurrence of key multiple health risk factors responsible for NCDs (i.e., at least two of smoking tobacco, inadequate fruit intake, inadequate vegetable intake, risky alcohol consumption, physical inactivity, obesity, anxiety and depression);
• Clustering patterns of these health risk factors;
• Socio-demographic characteristics associated with co-occurrence of health risk factors or identified clusters.

2. Materials and Methods

2.1. design and registration.

The systematic review was a narrative synthesis of studies registered with PROSPERO (International Prospective Register of Systematic Reviews) (registration number: CRD42019118161) and was conducted following the guidelines in the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) [ 31 ].

2.2. Literature Search

The following electronic databases were searched: MEDLINE, PsycINFO, EMBASE, CINAHL and Scopus to identify studies published by 30 June 2020 that examined multiple health risk factors in vocational education settings. The search was undertaken using keywords and medical subject heading searches (MesH). Boolean Operators “AND” and “OR” were used to combine search terms where appropriate. “OR” was used for within group combinations while “AND” was used for between group combinations. The search was restricted to studies with human participants. The reference lists of included articles were also checked to identify other eligible articles that may not have been captured during the database search. Table 1 outlines the search strategy.

Search strategy.

* Different forms of words or plurals.

2.3. Inclusion Criteria

2.3.1. type of studies.

Only quantitative studies published in English in peer-reviewed journals and published thesis or dissertations were included.

2.3.2. Study Design

Studies were included if they used any of the following designs: cross-sectional, longitudinal/cohort studies or baseline data from randomised controlled trials where co-occurrence and/or clustering of any combination of smoking tobacco, fruit intake, vegetable intake, alcohol consumption, physical activity, obesity, anxiety and depression was reported.

2.3.3. Participants

Studies were included if they surveyed students attending a vocational education institution only or subgroup analysis was available for the vocational education students.

2.3.4. Outcomes

Studies were included if they analysed together at least two of the following outcome measures:

• Smoking tobacco: any measure assessing current tobacco smoking behaviours (e.g., cigarette smoking);
• Fruit intake: any measure assessing fruit intake (e.g., daily serves of fruits);
• Vegetable intake: any measure assessing vegetable intake (e.g., daily serves of vegetables);
• Alcohol use: any measure assessing alcohol consumption (e.g., standard drinks per day);
• Physical activity: any measure of physical activity (e.g., minutes of moderate or vigorous physical activity);
• Obesity: any measure of obesity (e.g., body mass index, waist circumference);
• Depression: any measure of depression (e.g., having low interest in doing things);
• Anxiety: any measure of anxiety (e.g., feeling nervous or on edge).

Co-occurrence of multiple health risk factors was defined as concurrent engagement in two or more health risk factors and clustering was defined as association between co-occurring health risk factors [ 10 ].

2.4. Study Exclusion Criteria

Studies were excluded if they reported co-occurrence of multiple health risk factors where the percentage contained a majority (i.e., at least 4) of health risk factors not addressed by this review (e.g., illicit drug use, carrying a weapon, non-use of seat belts or crash helmets, physical fighting). Studies were also excluded if they were conducted in the vocational education setting but assessed the staff rather than the student population. Conference proceedings, non-peer reviewed articles, commentaries, protocols, systematic reviews, case control studies and non-English publications were all excluded.

2.5. Screening

All articles during the electronic search were exported into Endnote (Version 9, Clarivate Analytics, Philadelphia, PA, USA and duplicates removed. After deduplication, articles were exported into Covidence for title and abstract screening. Title and abstract screening was completed independently by two members (P.A. and (F.T. or J.B.)) of the review team based on the inclusion and exclusion criteria. If the eligibility of the study could not be determined during the title and abstract screening the full text of the article was obtained. Full-text screening was completed independently by two members (P.A. and (F.T. or J.B.)) of the review team. Discrepancies were resolved between the two reviewers. Reasons for exclusion during the full-text screening were recorded. Using Cohen kappa, inter-rater reliability between the two raters was k= 0.80, demonstrating substantial agreement [ 32 ].

2.6. Data Extraction

Data extraction was performed independently by two members of the review team (P.A. and J.B.). The reviewers discussed any discrepancies until resolved and if required consulted a third reviewer to resolve disagreements (F.T.). The following data were extracted from each of the included studies:

• Publication details: author(s), publication year, country of study and year data were collected;
• Study setting: type of vocational education setting;
• Study design: cross-sectional studies, longitudinal studies, and baseline data from randomised controlled trials;
• Sample characteristics: socio-demographic characteristics (e.g., age, gender, education, employment status, socio-economic status, marital status, country of birth, area of residence), sample size, recruitment methods used, eligibility criteria, consent rates;
• Measures: type of tobacco smoking, fruit intake, vegetable intake, alcohol use, physical activity, obesity, depression, and anxiety measures used;
• Outcomes: co-occurrence of two or more health risk factors, clustering of multiple health risk factors and socio-demographic characteristics associated with co-occurrence of multiple health risk factors and/or identified clusters.

2.7. Methodological Quality Assessment

The National Heart, Lung and Blood Institute (NHLBI) standardized Quality Assessment Tool for Observational Cohort and Cross-sectional studies [ 33 ] was used to assess the methodological quality of eligible studies. This quality assessment tool has 14 items with three response options (Yes, No, and other (i.e., CD, cannot determine; NA, not applicable, and NR, not reported). Quality of studies was judged as “good”, “fair” or “poor” based on the ratings of the items in the tool. This was done independently by two members (P.A. and F.T.) of the team. These two reviewers discussed any discrepancies until resolved.

2.8. Data Analysis and Synthesis

A systematic narrative synthesis was conducted as heterogeneity across the included studies did not allow for meta-analysis. The characteristics of studies, co-occurrence of health risk factors or clustering of health risk factors were presented using tables and narrative summaries. We followed the Guidance of the conduct of Narrative synthesis in Systematic Reviews [ 34 ]. P.A. performed all analysis and synthesis with the guidance of the other members of the review team.

Figure 1 presents the PRISMA diagram for screening and selection. A total of 2789 records were identified during the database search, and after duplicates were removed, 2688 records were screened. During the title and abstract screening, 2503 records were excluded leaving 185 full-text records which were assessed for eligibility ( Figure 1 ). Overall, 177 of the full-text records were excluded and reasons for exclusion are presented in Figure 1 . Eight studies [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] were deemed eligible and were included in the review.

PRISMA diagram of screening and selection process.

3.1. Study Characteristics

Table 2 describes the characteristics of included studies. Two studies were conducted in the United States [ 37 , 39 ] and one study in each of Australia [ 36 ], the Netherlands [ 35 ], France [ 38 ], Switzerland [ 42 ], Germany [ 40 ] and United Kingdom [ 41 ]. All eight studies were published from 2007 onwards. Seven studies used a cross-sectional design [ 35 , 36 , 37 , 38 , 39 , 41 , 42 ], and one study used a longitudinal design [ 40 ]. The sample size ranged from 142 [ 37 ] to 5688 [ 40 ]. Five studies reported mean age which ranged from 17.4 years [ 38 ] to 22.75 years [ 37 ]; one study reported a median age of 18 years [ 42 ], and one study recruited participants 16 years and older [ 36 ]. Five studies [ 35 , 36 , 37 , 39 , 42 ] reported a majority of female participants whereas two studies [ 38 , 40 ] reported a majority of male participants. For recruitment method used, two studies recruited students using an information sheet distributed to students weeks prior to the data collection [ 35 , 36 ]; one study displayed posters, distributed handouts around campuses and advertised via community college newspapers and email [ 37 ]; one study recruited all adolescents who attended the National Defence and Citizenship Day (JDC) [ 38 ]; one study recruited students during a regular school lesson reserved for health education [ 42 ]; one study recruited students by sending questionnaire packs to their advisors who distributed them during their study day [ 41 ], and two studies did not report recruitment method [ 39 , 40 ]. Across the eight studies the response rate ranged from 66% [ 41 ] to 99.5% [ 39 , 42 ].

Characteristics of studies examining the co-occurrence and clustering of health risk factors.

* = Other risk behaviours measured by the included studies but were not the focus of this review.

3.2. Combinations of Health Risk Factors Measured

Three of the studies measured two health risk factors [ 38 , 40 , 41 ]. The combinations assessed were smoking cigarettes/tobacco and drinking alcohol for all three studies. Three studies measured three health risk factors [ 35 , 37 , 42 ]. The combinations explored were alcohol drinking, depression and anxiety [ 37 ], hazardous drinking, smoking and physical inactivity and cigarette smoking, binge drinking and depression [ 35 , 42 ]. One study measured four health risk factors (i.e., tobacco use, alcohol use, leisure time physical activity and overweight/obesity) [ 39 ], whereas one study measured six of the health risk factors (i.e., smoking tobacco, alcohol consumption, fruit consumption, vegetable consumption, physical activity and obesity/overweight) [ 36 ]. None of the studies measured all eight health risk factors examined in this review.

3.3. Co-Occurrence of Multiple Health Risk Factors

Five studies reported the co-occurrence of multiple health risk factors among vocational education students [ 36 , 37 , 38 , 41 , 42 ]. Across the five studies, vocational education students’ engagement in two or more health risk factors ranged from 29% [ 42 ] to 98% [ 36 ].

3.4. Clustering Patterns of Health Risk Factors

Three studies examined the clustering of health risk factors [ 35 , 39 , 40 ]. Bannink et al. reported two clusters (i.e., “substance use” cluster characterised by binge drinking, cannabis use and cigarette smoking and “problem behaviour” cluster characterised by students who were delinquent, truant and incurred debts) using principal component analysis [ 35 ]. The study by Jeffries et al. reported three clusters (i.e., cluster 1: “active, binge drinkers with healthy dietary intake”, cluster 2: “non-active moderate-smokers and non-drinkers with poor dietary intake” and cluster 3: “moderately active, non-smoking and non-drinkers with moderately healthy dietary intake”) using Latent Class Analysis (LCA) [ 39 ]. Finally, Tomczyk et al. reported three clusters (i.e., “low users” characterised by students who reported low use of cigarettes, alcohol and cannabis/marijuana, “alcohol users” comprised of students who reported high use of alcohol and average scores for smoking cigarettes and “polysubstance users” characterised by students who reported high use of cigarette smoking, alcohol use and cannabis/marijuana) using Latent Transition Analysis (LTA) [ 40 ].

3.5. Socio-Demographic Characteristics Associated with Co-Occurrence of Multiple Health Risk Factors and/or Identified Clusters

3.5.1. gender.

One study reported that females were less likely to engage in (a) hazardous drinking and tobacco smoking but more likely to engage in (b) hazardous drinking and physical inactivity; (c) tobacco smoking and physical inactivity and (d) hazardous drinking, tobacco smoking and physical inactivity [ 42 ]. All three studies that examined the clustering patterns of health risk factors did not find an association between gender and the identified clusters [ 35 , 39 , 40 ].

One study reported that vocational education students aged 17 years and older were more likely to engage in hazardous drinking and physical inactivity whereas those aged 21 years or more were more likely to smoke tobacco and be physically inactive [ 42 ]. Participants older than 18 years were more likely to engage in hazardous drinking, tobacco smoking and physical inactivity [ 42 ].

The study by Jeffries et al. reported that for every additional year in age, participants were 8% more likely to belong to the “active, binge drinkers with healthy dietary intake” cluster [ 39 ]. Tomczyk et al. did not find any association between age and the clusters reported in their study [ 40 ] while Bannink and colleagues reported no association between age and the substance use cluster [ 35 ].

3.5.3. Socio-Economic Status (SES)

Only one study examined whether SES was associated with clusters and found no significant association between SES and “low users,” “alcohol users” or “polysubstance users” [ 40 ].

3.5.4. Education

Haug et al. found that those with secondary school education were less likely than those with no educational qualification to engage in hazardous drinking and tobacco smoking [ 42 ]. The remaining studies did not examine whether level of education was associated with engaging in multiple health risk factors or clusters [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ].

3.5.5. Ethnicity

Bannink et al. reported that participants of non-Dutch ethnicity were less likely to belong to the “substance use” cluster [ 35 ]. In the study by Haug et al. participants who had both parents born outside Switzerland were less likely than those with none of their parents born outside of Switzerland to engage in (a) hazardous drinking and tobacco smoking and (b) hazardous drinking and physical inactivity but more likely to engage in tobacco smoking and physical inactivity [ 42 ].

3.6. Methodological Quality Assessment

Table 3 outlines the methodological quality of the eight included studies in relation to 14 items and the overall quality rating. In terms of the overall quality rating one study was rated as good [ 40 ], six studies were rated as fair [ 35 , 36 , 38 , 39 , 41 , 42 ] and one study was rated as poor [ 37 ]. All studies adequately reported the research question and reported their participation/consent rate to be above 50%. Six studies [ 36 , 38 , 39 , 40 , 41 , 42 ], adequately reported the study population using demographics, locations, and time period whereas two studies [ 35 , 37 ] did not clearly specify and define the study population. Seven studies reported the eligibility criteria used to recruit the sample [ 35 , 36 , 37 , 38 , 39 , 41 , 42 ]. None of the studies provided a justification for the sample size. Five studies [ 35 , 37 , 39 , 40 , 42 ] did not report if outcome assessors were blinded and the longitudinal study did not report the follow-up rate [ 40 ]. Four studies did not provide information to indicate whether potential confounding factors were measured and adjusted for [ 36 , 37 , 38 , 41 ]. We could not determine if the outcome measures used were validated for six studies [ 35 , 36 , 38 , 40 , 41 , 42 ]. None of the studies measured the exposure variables more than once. Seven studies did not assess the exposure variables before the outcome variables were measured and did not allow a sufficient timeframe to see any effect [ 35 , 36 , 37 , 38 , 39 , 41 , 42 ].

Methodological quality assessment of eligible studies.

NA = Not applicable; CD = cannot determine; NR = Not reported.

4. Discussion

This is the first systematic review to examine the co-occurrence of multiple health risk factors, clustering of health risk factors and socio-demographic characteristics associated with co-occurrence of multiple health risk factors and/or identified clusters among vocational education students. Eight studies were included in the review. Five studies [ 36 , 37 , 38 , 41 , 42 ] reported the co-occurrence of health risk factors but only one of these studies reported the socio-demographic characteristics associated with co-occurrence of health risk factors [ 42 ]. Three of the eight studies examined the clustering of health risk factors and socio-demographic characteristics associated with cluster membership [ 35 , 39 , 40 ].

Across five studies, vocational education students’ engagement in two or more health risk factors ranged from 29% [ 42 ] to 98% [ 36 ]. This evidence highlights that a substantial proportion of vocational education students engage in multiple health risk factors. However, there were no studies that included all of the eight health risk factors examined in this review. All eight studies measured alcohol consumption [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]; seven studies measured smoking cigarettes/tobacco [ 35 , 36 , 38 , 39 , 40 , 41 , 42 ]; three measured physical activity [ 36 , 39 , 42 ]; two measured depression and/or anxiety [ 35 , 37 ]; two measured obesity/overweight [ 36 , 39 ], and one study measured fruit and vegetable consumption [ 36 ]. This highlights that substance use factors were more frequently reported than other health risk factors among vocational education students. Future studies should therefore take a broader approach to measuring the co-occurrence of multiple health risk factors in vocational education students by including a more comprehensive list of factors related to physical and mental health.

The three studies that reported the clustering of health risk factors reported clustering of alcohol use and tobacco smoking among vocational education students [ 35 , 39 , 40 ]. This is consistent with previous studies among university students and adult populations that have reported a strong clustering pattern of tobacco smoking and alcohol use [ 7 , 29 ]. Other health risk factors found to cluster together were (i) physical activity, binge drinking, and healthy diet [ 39 ] and (ii) physical inactivity, smoking and poor diet [ 39 ]. This emphasises the need to take a holistic approach to behaviour change in the vocational education setting. Multiple health risk factor interventions that address health risks simultaneously or sequentially may be particularly beneficial for vocational education students. However, importantly none of the existing studies examined clustering of all eight health risk factors together in vocational education students. Future research should assess how all eight health risk factors cluster together in vocational education students in order to inform the development and delivery of effective, comprehensive preventive health interventions in the vocational education setting. Clustering between physical activity and alcohol consumption has not received much attention with regards to policy. Further research should explore this relationship.

Only four [ 35 , 39 , 40 , 42 ] of the eight studies examined socio-demographic characteristics associated with the co-occurrence of multiple health risk factors or clustering of health risk factors. Gender and age were examined as characteristics that may be associated with co-occurrence of health risk factors or clusters in all four studies [ 35 , 39 , 40 , 42 ]. In relation to gender the findings were mixed with only one of the four studies reporting an association between gender and co-occurrence of health risk factors [ 42 ]. Specifically, females were found to be (i) less likely to engage in hazardous drinking and tobacco smoking but more likely to engage in (ii) hazardous drinking and physical inactivity, (iii) tobacco smoking and physical inactivity and (iv) hazardous drinking, tobacco smoking and physical inactivity. In terms of age, two of the four studies reported a significant association, specifically Haug and colleagues reported that participants aged 17 years and above were more likely to engage in hazardous drinking and physical inactivity, participants aged 21 years and above were more likely to report they smoked tobacco and physical inactivity and those aged 19 years and older were more likely to engage in hazardous drinking, tobacco smoking and physical inactivity [ 42 ]. In the study by Jeffries et al. for every additional increase in age, participants were more likely to belong to the ‘active, binge drinkers and healthy dietary intake’ cluster [ 39 ]. The findings by Haug et al. [ 38 ] are consistent with previous studies [ 43 , 44 , 45 ] that reported females were more likely to belong to clusters characterised by physical inactivity, hazardous drinking, and tobacco smoking among young adults in universities. Further research is needed among vocational education students to strengthen the evidence-base about potential associations between gender, age, SES, education and ethnicity and the co-occurrence of health risk factors or clustering of multiple health risk factors.

Given that vocational education settings have a large number of students, they are an ideal setting for targeting multiple health risk factors [ 17 ]. Vocational education settings also have facilities such as gyms which could be helpful for modifying health risk factors [ 46 ]. Furthermore, vocational education students are often adolescents or young adults [ 17 ] which provides opportunity to modify health risk factors earlier in life in an effort to produce positive health outcomes in the short- and long-term.

Limitations

This systematic review has a number of limitations. Firstly, all studies defined health risk factors differently and measured these health factors using different measures. This contributed to the heterogeneity in this review. Secondly, all three studies that reported clustering of health risk factors used different statistical techniques to identify clusters. The different statistical techniques used to identify clusters makes comparison between studies challenging. Thirdly, some studies we excluded measured more than one health risk factor but failed to analyse and report the co-occurrence or clustering of multiple health risk factors. This illustrates that health risk factors in vocational education students are often considered in isolation rather than a holistic approach adopted of analysing multiple health risk factors collectively. Finally, the methodological quality assessment was based on information available in the published article and it is possible that inadequate reporting influenced the ratings.

5. Conclusions

This systematic review identified limited high-quality evidence about the co-occurrence of multiple health risk factors, clustering of health risk factors and associated socio-demographic characteristics in vocational education students. Given that no studies examined all eight health risk factors associated with NCDs, further research is needed to conduct a more comprehensive assessment of how these multiple health risk factors co-occur or cluster in vocational education students. This could inform the design of multiple health risk interventions that holistically target vocational education students’ health risk behaviours and mental health concurrently instead of targeting them in isolation.

Acknowledgments

Infrastructure support was provided by the School of Medicine and Public Health, Hunter New England Population Health and Hunter Medical Research Institute.

Author Contributions

P.A., F.T., C.P., B.B. and J.W. conceived and designed the study. P.A. and F.T. developed the search strategy with assistance from a Librarian, and P.A. conducted the search. P.A., J.B. and F.T. screened the studies for inclusion. P.A. and J.B. extracted data, and P.A. and F.T. assessed the methodological quality of the included studies. P.A. drafted the manuscript. All co-authors contributed to the revision of the manuscript and approved the final version for publication. All authors have read and agreed to the published version of the manuscript.

P.A. was supported by a 50/50 Faculty of Health and Medicine, University of Newcastle PhD Scholarship. F.T. was supported by a National Health and Medical Research Council (NHMRC) Career Development Fellowship (APP1143269). The sponsors had no role in the design of the study and analysis and interpretation of data, in the writing of the manuscript, or in the decision to submit the paper for publication.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Essay on Vocational Education for Students in English [Easy Words]

January 12, 2021 by Sandeep

Essay on Vocational Education: Skill based learning for students focused mainly on gaining knowledge and expertise in a particular educational field for employment is termed as vocational education. People who cannot afford conventional means of education due to the costs or age factor can switch to vocational education. After course completion, the candidate shall be awarded a certificate of training. Vocational training centers are on the rise. They provide hands on experience for skill based employment.

Essay on Vocational Education 500 Words in English

Below we have provided Vocational Education Essay in English, suitable for class 6, 7, 8, 9 & 10.

Over the years, education has become the fundamental right of everyone. Education differentiates human beings from other living beings. It helps in the all-round development of a person. It has helped humans to evolve as the smartest creature on the earth. It gradually develops persons to face challenges in life efficiently. However, what differentiates vocational education from traditional education make a huge impact. It is a way of learning which directly gives practical knowledge & helps in specific skill development.

It is skill-based training which makes a person gain knowledge in a particular discipline. Vocational education is diversified in various fields like food, beverages, tourism, medical, manufacturing, banking & finance, art & culture etc. There is no age limit for this type of training. It can be done in secondary, higher secondary, graduation or at a higher level. It helps people get hands-on experience on the things that help them grab better job opportunities.

Vocationalisation signals major transformations in counties education system & economy. This helps in increasing the productive capacity of the country. As a skilled worker can add more value to the job, they perform. In countries like Japan, Germany, the US focus mainly on the development of technicians & skilled workforce as they are flooding with technologies. It helps a person choose its career early with formally trained in that field.

Benefits of Vocational Training

Vocational training is beneficial for skill development not only at the individual level but also at the national level. Few of the benefits of how it helps in creating values are listed below.

Career Enhancement: It gives stress on development practical experiences & new skills so those who already have a job can opt for these. It helps those who want to acquire new skill for their enhancement in the job role. Besides professionals, students & dropouts can also choose to pursue this course in the field of their interest.

Education Cost: The cost of vocational training is quite economical & affordable. Those who cannot afford the cost of education can opt for these courses. Many vocational courses provide new employment options in lesser time & lower cost.

Economic Development: The skilled & semi-skilled professional requirements are in high demand in all the sectors. The skilled manpower is always paid higher than the unskilled ones. Existence of skilled human resources helps the development of society and the economy of the country. In developing Nation like Indian, the impact is appreciatable. It reduced the provision of importing workforce from other counties.

Individual Development: Vocational training enhances competency & efficiency at the individual level. This training makes a person job-ready in the respective fields & helps earn a decent livelihood. Moreover, acquired people can even think about starting their own business instead of searching for a job with the skills. It opens the door for self-employment.

Vocational Education in India

In 1964 the Education Commission laid particular emphasis on Vocational Education to bring education in closer to production. To harmonize the diversity & cost, National Skills Qualification Framework was developed in 2013. Till then, the central government has tried to implement the same in all the states through different funded projects.

Professions like fashion designing, hair salons, beauty parlours, candle making, stitching, jewellery making, catering, cooking, interior designing, footwear designing, boutique, advertising, event planning, electronics repairing, painting, bag designing, tourism, music, dance, nutrition & health, gym, toy making, public relation, paramedical, agriculture & many more have witnessed a surge in demand by both consumers & the professionals.

Now the all India Council for Vocational education (AICVE), under MHRD, is responsible for planning, guiding and coordinating the programme at the national level. In the state level, State Council for Vocational Education (SCVE) performs similar functions. The need to focus on the skills of the informal sector is surging as it is projected that the share of jobs in India will be mainly from this sector. It employees up to 93% of the workforce with a 60% contribution to GDP (Gross Domestic Product).

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Vocational Education Essay | Essay on Vocational Education for Students and Children in English

Vocational Education Essay: Education is the fundamental right of every Indian citizen. It is an important pre-requisite for the progress of an individual and of the nation. Takshashila ajid Nalanda Universities were the earliest universities of India. In India, education is provided by both the Government and private sectors. Other than the primary and secondary education, vocational education is also catching up fast with today’s generation.

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Long and Short Essays on Vocational Education for Kids and Students in English

Given below are two essays in English for students and children about the topic of ‘Vocational Education’ in both long and short form. The first essay is a long essay on Vocational Education of 400-500 words. This long essay about Vocational Education is suitable for students of class 7, 8, 9 and 10, and also for competitive exam aspirants. The second essay is a short essay on Vocational Education of 150-200 words. These are suitable for students and children in class 6 and below.

Long Essay on Vocational Education 500 Words in English

Below we have given a long essay on Vocational Education of 500 words is helpful for classes 7, 8, 9 and 10 and Competitive Exam Aspirants. This long essay on the topic is suitable for students of class 7 to class 10, and also for competitive exam aspirants.

Vocational education refers to a system or course of study which prepares individuals for jobs that are based on manual or practical activities. The plethora of opportunities available in diverse fields today means that exams are not the end of the world. Gone are the days when students only opted for a traditional career in engineering or medical courses. Today, youngsters look for satisfaction in the jobs they do and thus they prefer to pursue a career or field of their interest.

Vocational education basically consists of practical courses through which one gains skills and expertise directly linked to a career in future. Moreover, with Indian economy expanding, different sectors are growing and so is the demand for professionals in various fields. Professions like hair cutting, fashion designing, jewellery designing, palmistry, salon, boutique, footwear designing, advertising, public relations, catering, interior designing, lighting, wedding planning, gift packing, candle making, card designing, toy making, paintings and flower making, bag designing, tourism industry, mobile and gadget repairing, music and dance, acting, nutrition and fitness industry, gym culture and many more, have witnessed a surge in demand by the people availing these services, and has resultantly pulled a large number of aspirants into these vocations.

Not only these professions offer umpteen opportunities and glorious career most of the time they do not require any major academic qualification. All that is needed, is the honed skill required for the profession, the enthusiasm to learn and the passionate desire to create something new and unique. Then sky becomes the limit. In fact, through hard work and creativity one can be far more successful and famous in the world than those pursuing the regular field of study. There are endless personalities who did not fare well in exams but by choosing the career of their own choice and working hard in the field they loved they have made a distinguished name for themselves. Pablo Picasso, Walt Disney, Shiamak Davar, Lata Mangeshkar, Bill Gates, Jawed Habib, Ritu Kumar, Sachin Tendulkar and many more have not pursued an academic career, yet are extremely successful today.

The growing demand of professionals has led to the opening up of institutes and training colleges to provide training for the same. While some promise excellent dance courses, others guarantee a perfect course in cooking. A formal vocational training follows a structured training programme and provides certificates, diplomas or degrees, recognised by State/Central Government or other reputed concerns; in-formal vocational training helps in acquiring some marketing expertise, which enables a person to pursue the profession of his/her choice.

The prescribed training also lays down standards in respect of syllabi, equipment, scales of accommodation, duration of courses and methods of training. It also conducts tests in various trade courses and lays down standards of proficiency required for passing the examination leading to the award of the certificate.

In 1976-77, the Vocational Education Programme (VEP), under the purview of the Ministry of Human Resources Development (MHRD), was started in general education institutions. While Vocational Education is a part of formal education system and the courses are offered in school grades 11 and 12, Vocational Training is outside formal education system and is open to students who leave school anywhere from grades 8 to 12. The purpose of the programme is to enhance individual employability, reduce the mismatch between demand and supply of skilled manpower and provide an alternative for those pursuing higher education without particular interest or purpose.

Short Essay on Vocational Education 200 Words in English

Below we have given a short essay on Vocational Education is for Classes 1, 2, 3, 4, 5, and 6. This short essay on the topic is suitable for students of class 6 and below.

The All India Council for Vocational Education (AICVE), under MHRD, is responsible for planning, guiding and coordinating the programme at the national level. State Council for Vocational Education (SCVE) performs similar functions at the State Level. There is a need to focus on the skills for the informal sector as it is estimated that the largest share of new jobs in India is projected to come from the unorganised sector which employs up to 93% of the national workforce and produces 60% of GDP.

“Educate a woman, and you educate the whole family.”

With regard to women’s education, it can be said that educating or providing practical training to women can go a long way in making them independent. DGET (Directorate General of Employment and Training) launched Women’s Vocational Training Programme, which aimed at bringing more women as skilled employees in the organised sector. If all the sectors of India join hands in providing the different education patterns under one roof, it can boost India’s employment rates greatly. Vocational education will not only provide jobs, but give many a reason to live a worthy and independent life.

Vocational Education Essay Word Meanings for Simple Understanding

• Plethora – overabundance, excess
• Honed – to make more acute or effective, improve, perfect
• Umpteen – innumerable, many
• Enthusiasm – absorbing or controlling possession of the mind by any interest or pursuit, lively interest
• Proficiency – ability, skill, competence purview – the range of operation, authority, control, concern etc
• Employability- a person’s capability for gaining and maintaining employment
• Boost – to increase, raise

Essay on Vocational Education for Children and Students in English

Table of Contents

Vocational Education Essay: Vocational Education is the skill-based training provided to students through diverse courses available in several career fields such as health care, banking and finance, computer technology, trade, tourism and so on. The education imparted to students focuses more on providing manual training and giving more practical exposure.

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Every industry or company today is looking for skilled and efficient employees. Vocational education helps students apply their learning practices and expertise in a specific field. It also gives opportunities to students unable to cope with academic education. Vocational educational organizations generate skilled manpower to meet the job demands. Here are essays on Vocational Education of varying word lengths to help you with the topic in your exam/school assignments. You can select any Vocational Education essay as per your need and requirement:

Long and Short Essay on Vocational Education in English

Below we have provided long and short Essays on Vocational Education of varying lengths in English.

This Vocational Education Essay will let you understand the meaning and significance of vocational education and acknowledge its importance.

After going through the essays, you will know how vocational education plays a significant role in the life of youths and also in the overall development of the nation.

Essay on Vocational Education – Essay 1 (200 words)

Vocational education is the education that trains people to work in various jobs such as technician, trade and craft. It refers to the career and technical education that prepares students for a specific career. The vocational programs provide students with hands-on instruction and training that leads them to certification or a diploma. Vocational schools provide vocational training on post-secondary, higher, and further education levels. Students can choose certificate or diploma programs, apprenticeship and associate degree programs.

Earlier, most vocational training programs took place in a classroom or on the job site professionals in the field. However, online vocational education has now become popular and easy for students to learn various skills from professionals. Earlier the training was also limited to certain jobs like welding, carpentry, and automotive services. Still, with the changing times, training has expanded to various job functions like tourism management, food and beverage management, computer network management, retail training, paralegal management and so on.

Vocational education focuses more on providing practical skills and hands-on instruction in a particular job. Students get a real working environment during vocational programs. Vocational education is evolving prominently and generates skilled and trained workers for specific jobs.

Essay on Vocational Education in India – Essay 2 (300 words)

Introduction

Vocational education, also known as career and technical education, enables students to gain specialized skills and training in various fields such as trade, craft or technical. Vocational education involves less academic learning and basically focuses on manual or practical activities and training. The students develop expertise in specific techniques or technology.

Vocational Education in India

Vocational education aims to prepare students for a particular profession, trade or vocation. These courses are specifically designed to make students job ready. The employability of graduates in India has become a major concern. Only 25% of the graduates from all streams are considered to have employable skills, indicating the need for high-quality vocational education to train the youth for Jobs. Vocational training is important to supplement formal education and improve youth employment in India.

There is a growing need for specialist and skill-based employees in India. Vocational education will help job-seekers get employment and meet the need for skilled professionals in India. It is important that sufficient training and skills are provided to the youth. The youth’s skill set in India plays a vital role in the country’s growth. Central Board of Secondary Education (CBSE) India offers various vocational courses at the senior secondary level and secondary level.

The courses are diverse and can be classified into various categories: commerce, home science, hospitality and tourism, health and paramedical, engineering, agriculture and others. These courses are offered in association with organizations such as NIFT, ROLTA, MED, WWI, NHMIT, etc., to train and upgrade the professional skills of youth. The students can choose from the diverse courses available as per their interest to gain skills in their chosen field.

Vocational education will provide tremendous opportunities to youth in various sectors. It will help build a skilled and educated workforce that is the need of the hour.

Essay on Importance of Vocational Education – Essay 3 (400 words)

Vocational education refers to the training that emphasizes skills and knowledge needed for a specific job, trade or craft. Vocational education is provided for various job functions in various sectors like tourism, food and beverage, computer networking, banking and finance, fashion designing, property management, etc. Students can choose from diverse courses available as per their skills and interest.

Importance of Vocational Education

• In today’s fast-paced and competitive world, it is really hard to find a good Job. Vocational education is an advantage as VET programs offer practical skills and hands-on training that trains students for specific jobs. The students who develop practical skills for a particular field are more confident and perform better in interviews and jobs than those with a general academic background.
• Vocational education, also popular as technical or career education, provides a clear edge in career goals as it provides expertise and knowledge in a specific discipline. The courses prepare them for a specific job. Vocational education programs are of short duration and are less expensive than conventional academic educational programs. They eliminate the disadvantages of rote learning and give a practical learning experience that makes the student’s job ready.
• Not only are the students at an advantage, but there is also a growing need for skilled labor. High-quality vocational education and skilled manpower is prerequisite for economic development. The graduates with conventional academic learning and degrees are not job-ready and mostly lack the skills to meet job expectations. There is a high demand for skilled manpower in various industries worldwide. High priority is given to skilled manpower globally. Some of the profiles for which skilled manpower is in high demand worldwide include computer specialists, nuclear technicians, fashion designers, electricians, cardiovascular technologists and web-developer.
• Vocational education helps youth to acquire practical experience and learn modern methods of diverse vocations. Students are now aware of their skills and choose their careers wisely. Vocational education prepares students to take up highly rewarding jobs and helps them become independent at a young age.

With changing times, people have started understanding the importance of vocational education. More skill and knowledge-based jobs will be generated in future. Close cooperation between industries and educational organizations about vocational training is essential to ensure that the education offered is relevant to the market demand and job expectations.

Essay on Growing Need for Vocational Education – Essay 4 (500 words)

Vocational education is the course of study that prepares students for handling the jobs practically rather than understanding their aspects theoretically. Vocational education is mostly non-academic and is related to a specific trade, occupation or vocation. Vocational education is gaining importance, and people are opting for such courses online and offline to gain skills in their interests. Traditionally, vocational education focused on a few trades like welding and automobile mechanic and was mainly enrolled by lower social classes.

Growing Need for Vocational Education

With the development of our nation, there is a growing need for skilled manpower, and vocational education prepares students for a job. Demand for skilled labour has increased both in the business and government sectors. There has been a speedy increase in vocational education owing to the increasing demand for skilled professionals. Vocational education has immensely diversified over the period. Demand for skilled professionals has increased in various industries such as tourism, information technology, banking and finance, retail management, BPO, hospitality and traditional crafts. Various institutes provide vocational training to the youth to make them job-ready.

Present-day education puts more emphasis on rote learning and not on practical work. There is a lot of pressure on students due to the rise in competition. Vocational learning allows students to choose the career of their interest, gain practical knowledge and get groomed.

In India, there is a disparity between the skills of educated youth and demand in various sectors. There is a greater need for a skilled workforce to meet job expectations. Vocational education can train students to meet job expectations. To meet the job demand and expectations, students should be motivated to take up vocational education.

Students in India are encouraged to score well and seek admission to a good college, whether it imparts vocational training. Students should get the opportunity to pursue their careers per their interests and according to their calibre rather than pushing them to become doctors and engineers even if they don’t have the required mindset. They must seek admission in courses that offer vocational training and don’t focus solely on the theoretical part. The absence of skilled professionals in various technical fields is costing us economically.

Some students may come as a surprise package when they get the opportunity to be trained and enhance their natural skills and talents. They become highly successful in their field and fetch good pay packages. The good news is the growing demand and scope for diverse skills globally. Sometimes the grades on mark sheets don’t matter. Most of the students can be good when it comes to displaying their practical skills. It is seen that many students who are not very good academically in their school prove to be good employees and attain great heights professionally.

There is a growing need for vocational education to develop skilled professionals in all occupations for our country’s social and economic growth. Students with low academic performance should not be discouraged by their parents and society. There are diverse options for students, and they should be free to choose whatever their interests and skills lead them.

Essay on Benefits of Vocational Education – Essay 5 (600 words)

Vocational education is skill-based education in a specific field which enables students to acquire training and practical skills in a particular trade, vocation or occupation. It is also known as career and technical education, as students develop skills and expertise in a specific discipline through manual practice. Vocational courses focus more on the application-based study.

Diverse job functions from various sectors, such as banking and finance, food and beverage, tourism, computer network, designing, healthcare, cosmetology, skilled trades etc., are included in vocational education.

Benefits of Vocational Training

• Job Ready: Vocational education makes student employment ready. It provides students required skills and training for a particular job, such as Interior Designing, Fashion Designing, Computer Networking, etc. Along with the classroom instructions, students also get practical knowledge. This makes the students job-ready and experts in their field.
• Low Education Cost: Private and Government institutes provide vocational education, and such courses’ fees are quite economical. Vocational courses are an easy and cheaper alternative for students who do not want to take a three-year degree course and cannot afford the hostel fees, commuting and added costs. Many vocational courses are as good as degree courses and employ students. A vocational course is the best option for those who cannot manage the expenses of a college degree.
• Easy Employment: Vocational training makes it easy for students to find employment opportunities. There is a growing need for skilled and efficient manpower in various sectors. The students with vocational training have an advantage over the college pass outs. Students with vocational training are preferred as they possess the right skills, education and knowledge for the job. Thus, easy and fast employment is a major advantage that students with vocational training have. Vocational education and skills can also provide students with employment opportunities in foreign countries.
• Career Advancement: Vocational education is the best alternative for people who already have a job and want to acquire further skills to enhance their careers. The course duration is quite less than the degree courses but the skills imparted are quite important and useful. Professionals can improve their career prospects and be successful. Students who are less interested in academic studies or dropouts can choose from the diverse courses available and enhance their skills in the field of their interest. Vocational education can help students make successful careers.
• Meet Market Demand: Employers in various industries rely on training organizations to impart knowledge and skills to the workers. These training organizations need to train the workers and ensure that their services meet the needs of employers and the students are job ready. Students who pursue vocational courses at the college level do not require undergoing such training programs. This saves the company cost spent on training.
• Economic Development: There is a growing need for skilled professionals in various sectors across the world. The existence of a skilled workforce is beneficial to society and also for the economic development of the nation. There would be a lesser need to import workforce from foreign countries at higher wages.
• Job Satisfaction: There are also various indirect benefits. For instance, vocational education boosts the student’s confidence, and they are well-groomed and trained, making them eligible for specific jobs. It also increases job satisfaction and results in high productivity.

Students who complete VET programs perform better in jobs than those with mere academic education. Vocational education is an asset to our economy. There is a high demand for skilled labour in the business and government sectors. Vocational education benefits students, employers, society and the nation.

Long Essay on Vocational Education – Essay 6 (800 Words)

Vocational Education refers to an education preparing students for specific industrial or commercial engagements. It provides an option other than traditional professional courses like engineering and medicine. Vocational training prepares interested students for specific trades or occupations. It is an opportunity for someone who doesn’t want to or couldn’t enroll in professional courses for some reason or another.

Skilled instructors give students hands-on training and experience in their specific subject. Every year some new fields are included in vocational training courses, providing the students with a good number of options to choose from.

Types of Vocational Programs

Vocational Education prepares students for industrial or commercial employment. There are many options available through which vocational training could be acquired. Many trade institutes offer vocational training courses, or else in-job training programs for specific fields of interest could acquire them.

Many vocational courses have been integrated into the syllabus of CBSE (Central Board of Secondary Education), a national-level board of education in India controlled by the Government of India. Some of the most opted among these vocational courses include – Accountancy and Auditing, Marketing and Salesmanship, Banking, Business Administration, Electrical Technology, Automobile Technology, Civil Engineering and IT Application etc. Any student can opt for the subject of their choice at the senior secondary level.

Where is Vocational Education Provided?

For the convenience of students and keeping in mind the interests of working professionals, the government of India provides vocational training in both full-time and part-time courses. Full-time training is provided through Industrial Training Institutes (ITIs), while State Technical Education offers part-time courses. Thus, Polytechnics – privately owned ITIs or Government owned ITIs are the best place to acquire vocational training.

Students can also opt for the subject they want to be trained in at the senior secondary level.

Advantages of Vocational Education

Vocational Education is an unconventional method to generate a skilled workforce having practical knowledge and experience. These students are trained in real practical situations, making them instantly employable in their trades.

It requires less time than professional courses and is much cheaper to pursue. At a relatively young age and in considerably less time, a vocational student learns the skills of the trade and gains practical working experience, securing his career and growth.

The availability and quality of vocational education in a country determines its industrial and economic progress. Industries get young and skilled employees with hands-on experience and probably long commitments. This is a win-win situation for the industry/company.

Being cheaper to pursue and with no age bar, vocational education provides an option to students from economically weaker sections or for the elders who never had the opportunity to study. Therefore, vocational education reduces unemployment and hence the poverty graph of a nation. More skilled students mean more employability quotient and more jobs, resulting in the nation’s overall growth.

Schemes Offered by the Government of India

The Government of India offers many schemes to provide vocational training to the underprivileged or economically backward sections. Some of the most significant such schemes are given below.

1) Udaan: This program is specifically designed for the state of Jammu and Kashmir. The program has a five-year duration and offers vocational training and employment in Information Technology, BPO and retail.

2) Polytechnics: Polytechnics are a kind of Industrial Training Institute present in almost all states of India. It provides three-year diploma courses in various disciplines of Engineering and computer science.

3) Industrial Training Institutes: Industrial Training Institutes offer vocational training in various engineering and non-engineering disciplines. ITIs are managed by the Directorate General of Training and Employment, Government of India.

4) NRLM (National Rural Livelihood Mission): Launched in June 2011, NRLM is specifically targeted at BPL (Below Poverty Line) group. It aims to provide vocational training in various trades to people below the poverty line, differently able and women, to make them self-employable.

5) Craftsmen Training Scheme: This scheme provides vocational training in various engineering disciplines as well as in the fields of paramedical, agriculture and commerce etc. The Directorate of Vocational Education and Training governs it.

Vocational Education is nothing less than a blessing for those who cannot go for professional courses for some reason or another. It provides a wonderful and affordable opportunity to acquire technical skills and improve their employability. A quality vocational education provided by skilled trainers will generate a young and efficient workforce, contributing immensely to the nation’s progress. It also provides an opportunity to generate self-employment for people below the poverty line who are both able and women. Such people are taught skills to start their own business in a trade of their choice.

More on Education:

• Article on the Importance of Education in our Life
• Article on the Importance of Education in Society
• Article on the Importance of Education for Children
• Article on the Importance of Education for Women

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Essay on Vocational Education

Vocational education is a special learning course apart from normal studies, which aims to provide a better concept of learning to the students. It includes courses in various fields like healthcare, graphic, web designing, cinematography, electrician, artesian, computer programming, etc. It basically helps in making students learn things with a proper practical approach and training. It benefits the students by making them skilled and ready for jobs.

Short and Long Essays on Vocational Education in English

I hope these essays here will help you to better understand everything about Vocational Education .

Vocational Education Essay 10 Lines (100 – 150 Words)

1) The education that aims to prepare students for jobs is termed as vocational education.

2) Vocational education provides more practical knowledge to the students.

3) It is also referred to as career-oriented technical education.

4) Vocational education helps students in opening more job opportunities.

5) Beautician, technicians, animation, etc are some examples of vocational education.

6) Vocational education is offered by many universities with fees less than academic education.

7) People of any age group can attain vocational knowledge.

8) Vocational knowledge is less successful due to a lack of awareness.

9) Vocational knowledge encourages entrepreneurship.

10) Government should promote vocational education to reduce unemployment.

Essay 1 (250 Words) – Vocational Education

Introduction

Vocational education can be called education which is job-oriented. Generally, we see that a person is completing the academic education and after the completion, search or opt for some job opportunities. Academic education is providing with a vast background of study which is theoretical and concept-based. Vocational education provides us with a more practical aspect for any of the vocational courses.

How Vocational Education helps us

Vocational education helps the student to become skilled in any discipline by learning and training process. There are many Universities offering various vocational courses. These courses help in the skill development of the student and make them ready for the jobs. We have often seen that many of the students are not willing to choose academic courses and thus vocational courses are helping them to escape from the vast academic course. They can learn the techniques and become trained in the field in which they desire to work.

Vocational education provides the nation with skilled manpower. Vocational education can be attained by a person at any age. The course fee is also less as compared to the academic or professional course. This provides a chance for the students to develop themselves in the fields which they are fond of. Secondly, they get a chance of improving their skills and get hired by different industries.

The vocational education courses must be emphasized by the government so that students can go for these courses and further build up their careers. Vocational education helps the country’s economy to boost up as it provides skilled manpower.

Essay 3 (400 Words) – Vocational Education: Need and Challenges

Vocational education is designed to make the students ready for jobs. It can also be called career education. It basically focuses on the skill development and practical aspect of any discipline.

The need for Vocational Education

Vocational education makes a student ready for a job or we can say it helps in producing skilled people. It is seen that many of the students go through a financial crisis and they need to earn for the survival of their family. The academic courses are having a vast curriculum as also do not favor skill development and a larger practical approach. And the vocational courses provide better skill development in the required field and make them eligible for jobs.

The students who are not interested in doing the academic programs are compelled to study and for degrees in the colleges and complete the academic course. These students instead of just blocking the seats or studying without any interest can opt for vocational programs. They can join the course of their interest. The maximum qualification for doing vocational courses is either ten or ten plus two. These courses provide us with a certificate or diploma degree.

Vocational education helps us in learning new skills or improves our skills. In this era when there are limited job opportunities. The industries and firms require a skilled or trained candidate. These courses help us in getting jobs.

Challenges of Vocational Education in India

• Many of the students are not able to get the proper information about the vocational courses and therefore they have to opt for academic education.
• The government is also paying less attention to promoting the importance of vocational courses.
• The financial help and funds are not sufficient to make these courses to run successfully, as these courses require the use of machinery and technology.
• The teachers involved in these courses either are not having proper resources to teach the students or are not knowledgeable.
• The universities and colleges offering these courses are not having proper practice and training facilities. The students without any practical knowledge cannot work in any industry.
• The tools and techniques need to be updated with the development of technology. It will be of no use if the old concept is taught.

Vocational education has become important. It helps people to make their careers in the field in which they are interested along with getting a way to earn their living.

Essay 3 (500 – 600 Words) – Vocational Education versus Academic Education and Its Benefits

As we all know that our country is a developing country the development of which depends upon its people. So, vocational education is one of the helping aids in its development. Vocational education courses play an important role in making students become skilled and get employed. It lays an emphasis on the practical aspect of the relevant course or field. It includes various streams like art and craft, electrician, trade, technology, etc.

Vocational Education versus Academic Education

In our country India, there is a concept of academic education which is prevailing for years. Academic education offers vast course syllabi and theoretical concepts. Practical learning is only in laboratories and internships. The academic course requires a longer time to be completed and involves a higher expenditure of money. The students after completion of the course are awarded a degree. There are many of the students who graduated and post-graduated each year, but they cannot get jobs easily and remain unemployed as they lack in skill.

The vocational education courses are helping us in developing our skills by providing us with a practical approach to the course. They help in the process of learning by providing training and workshops related to the course. This helps the student to develop the required skill and have prior experience of the work. Therefore the skilled students are easily hired by different industries and are employed.

Benefits of Vocational Education

• Vocational education courses can be completed in a short period of time. The person receives a certificate or diploma degree after the completion of the course.
• These courses can be done at any age, and with less expenditure of money. There are many courses, out of which some are full time and some are part-time courses.
• Vocational education is connected with the practical approach to the subject. It provides the student to apply the concept to real work functioning. The students opting for vocational education and training are hired easily by the recruiters as they have practical skills in a particular field.
• There are many courses under vocational education that can be completed online or by distance learning.
• There is a high demand for skilled professionals in the market. The students who have opted for these courses are employed by the industries as they are skilled.
• Vocational education courses are a job providing courses as they help in producing skilled manpower. This helps in contributing to the economic development of the country.
• Vocational education courses can be done only after completing 10 th or 12 th standards.
• Vocational education also helps students to start their own business, after they are acquired the skill of entrepreneurship. They can start their business independently.

Towards a New Era for Vocational Education in India

The former HRD minister Fakhruddin Ali Ahmed addressed that, getting jobs as a student requires becoming skilled. The skilled population in India accounts for only 25% of the whole. As the development of the country is increasing day by day, so these courses will become the need of the time.

The New education policy has introduced many vocational courses like artificial intelligence, tourism, information technology, mass media, etc. These courses will be introduced from this year only and will be applicable from the 6-9 th class. According to CBSE, these skills will lead to developing the creative and reasoning skills in the students. Thus these courses will make them work globally.

CBSE has started three courses – Design Thinking, Physical Activity Trainer, and Artificial Intelligence which will be implemented for class 11 th students in 2020-21.

CBSE has 40 vocational courses which had been since 2014. For strengthening the vocational education and with a strong determination to provide benefit to each and every student; many of the courses have been introduced with the partnership of various companies like Rolta India Limited, NIFT, WWI, NHMIT, etc from which students will be benefited with these strategies as they get a proper platform for training and carrier development.

Vocational education courses must be encouraged in our country. There are many sectors that have a requirement for skilled professionals, but unfortunately, the skilled and trained professionals are few in number. This creates a misbalance in demand and availability of the industries for skilled manpower. Vocational education is an urgent need today as it can help in solving the issue of reduced skilled manpower.

FAQs: Frequently Asked Questions

Ans . Charles Allen is regarded as the father of vocational education.

Ans . Vocational education helps us in better learning and prepares us for getting good job opportunities.

Ans . There are a total of 40 vocational courses.

Ans . The duration of vocational courses is from two months to two years depending upon the course.

Ans . Vocational education started in India in 1956.

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• Progress & Info (2019)
• Progress & Info (2018)
• Progress & Info (2017)
• Progress & Info (2016)
• Targets & Indicators

Achieving inclusive and equitable quality education for all will require increasing efforts, especially in sub-Saharan Africa and Southern Asia and for vulnerable populations, including persons with disabilities, indigenous people, refugee children and poor children in rural areas.

• In 2014, about 2 in 3 children worldwide participated in pre-primary or primary education in the year prior to official entry age for primary school. However, in the least developed countries, the ratio was only 4 in 10.
• Despite considerable gains in education enrolment over the past 15 years, worldwide, the adjusted net enrolment rates were 91 per cent for primary education, 84 per cent for lower secondary education and 63 per cent for upper secondary education in 2014. About 263 million children and youth were out of school, including 61 million children of primary school age. Sub-Saharan Africa and Southern Asia account for over 70 per cent of the global out-ofschool population in primary and secondary education.
• Even though more children than ever are going to school, many do not acquire basic skills in reading and mathematics. Recent learning assessment studies show that in 9 of 24 sub-Saharan African countries and 6 of 15 Latin American countries with data, fewer than half of the students at the end of primary education had attained minimum proficiency levels in mathematics. In 6 of 24 sub-Saharan African countries with data, fewer than half of the students who finished their primary schooling had attained minimum proficiency levels in reading.
• Equity issues constitute a major challenge in education according to a recent assessment. In all countries with data, children from the richest 20 per cent of households achieved greater proficiency in reading at the end of their primary and lower secondary education than children from the poorest 20 per cent of households. In most countries with data, urban children scored higher in reading than rural children.
• The lack of trained teachers and the poor condition of schools in many parts of the world are jeopardizing prospects for quality education for all. Sub -Saharan Africa has a relatively low percentage of trained teachers in pre -primary, primary and secondary education (44 per cent, 74 per cent and 55 per cent, respectively). Moreover, the majority of schools in the region do not have access to electricity or potable water.
• On the basis of data from 65 developing countries, the average percentage of schools with access to computers and the Internet for teaching purposes is above 60 per cent in both primary and secondary education. However, the share is less than 40 per cent in more than half of sub-Saharan countries with data.
• Official development assistance (ODA) for scholarships amounted to $1 billion in 2015, a decrease from $1.2 billion in 2014. Australia, France and the United Kingdom of Great Britain and Northern Ireland were the largest contributors.

Source: Report of the Secretary-General, "Progress towards the Sustainable Development Goals", E/2017/66

More than half of children and adolescents worldwide are not meeting minimum proficiency standards in reading and mathematics. Refocused efforts are needed to improve the quality of education. Disparities in education along the lines of gender, urban-rural location and other dimensions still run deep, and more investments in education infrastructure are required, particularly in LDCs.

• At the global level, the participation rate in early childhood and primary education was 70 per cent in 2016, up from 63 per cent in 2010. The lowest rates are found in sub-Saharan Africa (41 per cent) and Northern Africa and Western Asia (52 per cent).
• An estimated 617 million children and adolescents of primary and lower secondary school age worldwide—58 per cent of that age group—are not achieving minimum proficiency in reading and mathematics.
• In 2016, an estimated 85 per cent of primary school teachers worldwide were trained; the proportion was only 71 per cent for Southern Asia and 61 per cent for sub-Saharan Africa
• In 2016, only 34 per cent of primary schools in LDCs had electricity and less than 40 per cent were equipped with basic handwashing facilities.

Source: Report of the Secretary-General, The Sustainable Development Goals Report 2018

Despite the considerable progress on education access and participation over the past years, 262 million children and youth aged 6 to 17 were still out of school in 2017, and more than half of children and adolescents are not meeting minimum proficiency standards in reading and mathematics. Rapid technological changes present opportunities and challenges, but the learning environment, the capacities of teachers and the quality of education have not kept pace. Refocused efforts are needed to improve learning outcomes for the full life cycle, especially for women, girls and marginalized people in vulnerable settings.

• In 72 countries with recent data, approximately 7 in 10 children aged 3 and 4 were developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development and learning.
• In 2015, an estimated 617 million children and adolescents of primary and lower secondary school age worldwide – more than 50 per cent – were not achieving minimum proficiency levels in reading and mathematics. Of these, about two thirds were attending school but were not learning in the classroom, or dropped out school.
• Some 750 million adults – two thirds of them women – remained illiterate in 2016. Half of the global illiterate population lives in South Asia, and a quarter live in sub-Saharan Africa.
• Many developing countries still lack basic infrastructure and facilities to provide effective learning environments. Sub-Saharan Africa faces the biggest challenges: at the primary and lower secondary levels, less than half of schools have access to electricity, the Internet, computers and basic drinking water.
• ODA for scholarships amounted to $1.3 billion in 2017. Australia, France, Japan, the United Kingdom of Great Britain and Northern Ireland and institutions of the European Union accounted for nearly two thirds of this total.
• Globally, there has been little progress in the percentage of primary school teachers who are trained: it has been stagnating at about 85 per cent since 2015. The proportion is lowest in sub-Saharan Africa (64 per cent).

Source: Report of the Secretary-General, Special edition: progress towards the Sustainable Development Goals

• Despite progress, the world failed to meet the Millennium Development Goal of achieving universal primary education by 2015. In 2013, the latest year for which data are available, 59 million children of primary-school age were out of school. Estimates show that, among those 59 million children, 1 in 5 of those children had dropped out and recent trends suggest that 2 in 5 of out-of-school children will never set foot in a classroom. The Sustainable Development Goals clearly recognize that this gap must be closed, even as the international community more explicitly addresses the challenges of quality and equity.
• Measuring learning achievement, starting in the early grades, will help to identify where schools are failing to meet their commitments to children and to formulate appropriate remedial action. For example, data for 2013 from 15 Latin American countries show that in six countries, fewer than 50 per cent of third graders had a minimum level of proficiency in mathematics; in three countries, fewer than half were proficient in reading.
• At the end of primary school, children should be able to read and write and to understand and use basic concepts in mathematics. However, in 2014, between 40 per cent and 90 per cent of children failed to achieve even minimum levels of proficiency in reading, in 10 African countries, and in nine of those countries, between 40 per cent and 90 per cent of children failed to achieve minimum levels of proficiency in mathematics.
• The end of lower secondary education often coincides with the end of compulsory education. By this stage, young people should be able to master subject-related knowledge and skills and possess personal and social skills. Data from 38 countries in the developed regions show that, in the majority of those countries, at least 75 per cent of young people achieved at least a minimum proficiency in reading and/or mathematics; the same was true for only 5 out of 22 countries, in developing regions, for which data were available.
• Completion rates for both primary and lower secondary education has been rising steadily since 2000. Completion rates for primary education in both developed and developing regions exceeded 90 per cent in 2013. At the lower secondary level, the gap between developed and developing regions has narrowed substantially, but still stood at nearly 20 percentage points in 2013 (91 per cent for developed regions and 72 per cent for developing regions).
• Quality early education provides children with basic cognitive and language skills and fosters emotional development. In the majority of the 58 countries with available data for the period 2009-2015, more than half of children between the ages of 3 and 4 were developmentally on track in at least three of the following domains: literacy, numeracy, physical development, social-emotional development and learning.
• Goal 4 strongly supports the reduction of persistent disparities. Worldwide, in 2013, two thirds of the 757 million adults (aged 15 and over) who were unable to read and write were women. Globally, in 2013, 1 in 10 girls were out of school, compared to 1 in 12 boys. Children from the poorest 20 per cent of households are nearly four times more likely to be out of school than their richest peers. Out-of-school rates are also higher in rural areas and among children from households headed by someone with less than a primary education.
• To fulfil the promise of universal primary and secondary education, new primary school teachers are needed, with current estimates showing a need for nearly 26 million of them by 2030. Africa faces the greatest challenges in this regard, with nearly 7 in 10 countries experiencing acute shortages of trained primary school teachers. In 2013, only 71 per cent of teachers in sub-Saharan Africa and 84 per cent in Northern Africa were trained in accordance with national standards.
• Official development assistance for educational scholarships amounted to around $1.1 billion annually from 2011 to 2013. It totalled $1.2 billion in 2014, with Australia, France and Japan being the largest contributors.