essay on higher education versus skill acquisition

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Skill Acquisition vs. Higher Education? Why This Is A False Choice

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essay on higher education versus skill acquisition

Rising costs of tuition have left Gen Z’ers and Millennials strapped by student loan debt, with more young people than ever living at home with their parents after college and struggling to make it in today’s economy. Add to this the high-rates of inflation , the economic downturn following the COVID-19 pandemic, and an increasing move away from the traditional 9 to 5 corporate world to a Gig Economy , it’s understandable why colleges and universities have seen declining undergraduate enrollment .

What is the Debate Between Skill Acquisition vs. Higher Education?

These factors have led to the debate surrounding higher education that focuses on the push toward skills-based programs in lieu of a broader liberal arts-based college education. While employers today seek applicants with specific content expertise, they also desire a candidate pool who have developed the “soft skills” needed to succeed in the professional world — these include, proficient written and oral communication, problem solving, and teamwork abilities.

As a result, critics of traditional college degree programs argue that vocational and apprenticeship programs are better able to “produce more workers now who can do whatever is needed now, using short-term postsecondary certification programs ,” says George D. Kuh, Chancellor’s Professor Emeritus of Higher Education at Indiana University and co-author of Using Evidence of Student Learning to Improve Higher Education , in a piece for the Harvard Business Review . Proponents of vocational, skills-based educational programs have long criticized college and university undergraduate programs as providing “ relatively useless liberal education outcomes , including knowledge of world history and cultures and other ‘indulgences’ such as crafting understandable prose and judging the veracity and utility of information.”

However, these so-called “indulgences” may be more important over the long term than some may think.

Benefits and Drawbacks of a Traditional College Education vs. a Skills-Based Technical Education

Because both four-year college degree programs and skills-based educational programs have their benefits and downsides, we’ve laid out the pros and cons of each side of the debate.

College Education

Skills-Based Technical Education

Combining the best of both worlds by adopting competency-based approaches.

While it’s important to prepare students with the skills that are in demand today, forgoing a college education in favor of a skills-based education may not be the best option over the long term. Complex changes will take place in the world that will call for the type of broad foundation that a college education provides, including the critical thinking and analytical skills necessary to navigate what’s to come.

Additionally, shifting to a purely skills-based model may negatively impact the educational experience of low-income and minority students. And, as colleges and universities move toward outcomes-based educational programs to better prepare undergraduates with the skills that are most in demand, perhaps the emphasis should not be on moving away from the four-year degree model but, instead, toward a combination of both models, where college degree programs work directly with employers to offer hands-on programs for students.

“The future is less about credit accumulation and much more about skill acquisition,” as Madeline Pumariega, Miami Dade College president, noted to Fast Company , “which puts us in a good place to marry career technical education with new pathways to careers.” In Pumariega’s view, the ideal post-secondary curriculum combines the types of competencies achieved through a college education along with the practical skills that vocational training programs offer.

“I think the future of work relies on three sets of skills,” she explains. These include “applied knowledge,” achieved through classroom learning; “future-proof skills,” or “ soft skills ,” essential for all types of work; and technological skills to keep up with emerging and evolving fields including artificial intelligence and data analytics. Adds Roy Mathew of Deloitte Consulting’s higher education practice (via Fast Company ), “The need for these skills appeared so quickly — in a matter of a decade.”

Higher education can open doors for undergraduates to a variety of professional opportunities; however, historically, it has been largely left to students themselves to pursue these types of opportunities to develop their competence outside of the classroom.

Unfortunately, too few students pursue these opportunities to make the most of their college experience, while others may lack a full understanding of exactly “how to navigate the job market, [an] arrangement [that] is especially punishing to low-income, first-generation, and minority students,” explains Dr. Adrianna Kezar, director of the Promoting At-Promise Student Success Project at the University of Southern California’s Pullias Center for Higher Education. “Rather than telling students, ‘Go to the career center if you don’t understand the direction or potential of a major,’ faculty members need to speak directly about what students can do with a specific major, what it will mean for their job potential, and where they can find internships and apprenticeships,” Kezar shares with Fast Company .

Colleges and universities can benefit by implementing programs that push students to be more accountable for not only the work they do in class but also the co-curricular activities they engage in outside of class — likely the push they need to pursue experiential learning opportunities , such as internships and leadership-training programs.

“When a college or university intentionally designs and induces students to participate in high-impact learning activities inside and outside the classroom, the outcomes are much better contrasted with students who do not have such experiences,” says Kuh, per the Harvard Business Review. “The benefits of participating in high-impact practices such as writing intensive courses, undergraduate research, community service projects and internships are especially promising for historically underserved students who will make up a large fraction of tomorrow’s workers and community leaders.”

Examples of Competency-Based Approaches

So, what can be done to motivate students to participate in co-curricular programs and prepare them for finding work — and maintaining it, while promoting the concepts of lifelong learning and professional development — after graduation?

Mobile-friendly digital applications that promote student engagement and skill acquisition are key to bridging this gap. Solutions such as Suitable’s Guided Pathways provide competency-based , customized learning activities that help students develop the in-demand skills that employers seek. Gamification techniques that show evidence of individual student progress towards meeting specific competencies through external rewards, such as acquiring digital badges , motivate them to become more engaged. Undergraduates and recent grads can also use Suitable’s Co-Curricular Transcript to present a digital record of their co-curricular activities, projects, and experiences in real time, providing the kind of proof that employers and proponents of skills-based training seek — evidence that a college education can be not only theoretical but practical, too.

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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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PROGRESSIVE ENGLISH

Higher Ed vs. Skill Acquisition

Higher Education vs. Skill Acquisition: Which Path Leads to Success?

Introduction, definition of higher education, definition of skill acquisition, importance of the topic, higher education, overview of higher education, benefits of higher education, challenges associated with higher education, overview of skill acquisition, benefits of skill acquisition, challenges associated with skill acquisition, comparison between higher education and skill acquisition, differences between the two concepts, similarities between the two concepts, advantages and disadvantages of higher education and skill acquisition, advantages and disadvantages of higher education, advantages and disadvantages of skill acquisition, recommendations.

Determine your career goals: What you want to achieve in your career will help you decide which option is best for you. For example, if you’re looking for a specific role within an organization that requires a degree, then higher education might be the best option.
Evaluate your learning style: How do you learn best?
Weigh up costs: Higher education can be expensive and take several years to complete. In contrast skill acquisition can be less time-consuming and less expensive than traditional college degrees.

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Higher Education vs. Skill Acquisition: Navigating the Crossroads of Career Advancement

By: Nimas Ayu Nawal Maulida

In today’s dynamic world, the decision between pursuing higher education or acquiring specific skills has become increasingly crucial. Both paths offer distinct prospects for career trajectories and long-term aspirations.

Higher education, encompassing undergraduate and postgraduate degrees, provides a broad and in-depth foundation of knowledge in a chosen field. This opens doors to diverse career opportunities, particularly in areas requiring specialized expertise, such as science, technology, and law. While higher education offers deep knowledge, critical thinking skills, professional networking opportunities, and research exposure, it can be financially demanding, time-consuming, and does not always guarantee employment in the desired field.

Skill acquisition, on the other hand, focuses on developing specific skills sought after by industries. This can be achieved through various avenues, including vocational training courses, bootcamps, apprenticeships, or self-directed learning. Skill acquisition offers lower costs, shorter durations, industry-relevant skills, and adaptability to industry shifts. However, it may not provide the same depth of knowledge, professional networking opportunities, or research exposure as higher education.

Ultimately, the choice between higher education and skill acquisition depends on individual interests, career goals, and financial circumstances. For those seeking in-depth knowledge in a specific field and aspiring for careers requiring specialized expertise, higher education may be the optimal choice. However, for individuals seeking industry-specific skills and aiming for quick employment, skill acquisition may be more suitable.

The key lies in selecting the path that aligns with personal aspirations and facilitates the achievement of career objectives. Carefully evaluate your options, consider your aspirations, and make an informed decision that aligns with your long-term career goals. Remember, there is no right or wrong answer. The decision to pursue higher education or acquire specific skills is a personal one. Embrace the path that aligns with personal strengths and empowers the realization of full potential.

The ever-evolving landscape of the workforce necessitates a continuous reevaluation of how we prepare ourselves for career success. The traditional path of higher education, while still holding significant value, now faces competition from a burgeoning ecosystem of skill acquisition programs. Both approaches have their merits and drawbacks, and the optimal choice hinges on a nuanced understanding of personal aspirations, industry demands, and financial considerations.

Beyond the Degree: Higher Education’s Evolving Role

Higher education institutions have long been considered the gateway to professional success. Degrees signaled not only expertise but also the intellectual ability and commitment to persevere through rigorous academic challenges. This traditional perspective still holds weight in fields like medicine, engineering, and law, where specialized knowledge forms the bedrock of professional practice. Higher education fosters critical thinking skills crucial for analyzing complex problems, developing research methodologies, and effectively communicating findings. Additionally, universities cultivate vibrant social and professional networks that provide invaluable connections throughout careers.

However, the rising cost of higher education, coupled with an increasingly dynamic job market, has led to a reevaluation of its return on investment. Graduates often face a saturated job market, and degrees alone no longer guarantee immediate employment. Employers are increasingly seeking individuals with demonstrably relevant skills, regardless of the pedigree of their educational background. As a result, higher education institutions are adapting, offering more flexible and specialized programs that bridge the gap between theoretical knowledge and practical application. Internships, capstone projects, and experiential learning opportunities are becoming increasingly integrated into curriculums, preparing graduates to hit the ground running upon entering the workforce.

The Rise of Skill Acquisition: A More Agile Approach

Skill acquisition programs have emerged as a compelling alternative, offering a more targeted and cost-effective approach to career development. These programs, encompassing bootcamps, online courses, and vocational training, focus on equipping individuals with the specific skillsets demanded by high-growth industries like coding, data analytics, and digital marketing. The duration of these programs is often significantly shorter than traditional university degrees, making them a more attractive option for individuals seeking a faster entry into the workforce. Additionally, the ability to tailor learning paths to specific industry needs allows skill acquisition programs to remain agile and responsive to market fluctuations.

However, skill acquisition programs come with their own limitations. The depth of knowledge and critical thinking skills fostered by higher education may be less emphasized in these programs. While they equip individuals with the technical skills needed for employment, they may not provide a strong foundation for long-term career progression. Additionally, the lack of a formalized credential and established professional networks associated with traditional university degrees can be a disadvantage for some job seekers.

Finding the Perfect Blend: A Hybrid Approach to Career Development

The dichotomy between higher education and skill acquisition is becoming increasingly less relevant. A blended approach that leverages the strengths of both offers a promising path forward. Individuals with a strong foundation in theoretical knowledge from a university degree can enhance their skillsets and marketability through targeted skill acquisition programs. Conversely, individuals who pursue skill acquisition programs can later return to higher education, leveraging their industry experience to deepen their knowledge and pursue leadership roles. Additionally, the rise of micro-credentials – certifications offered by universities and online platforms acknowledging mastery of specific skills – allows for continuous learning and career advancement throughout one’s professional journey.

The Future of Learning: Embracing Lifelong Learning

The future of work promises to be characterized by constant change and disruption. Automation may displace certain jobs, while new skill sets will be required to navigate emerging technologies. In this dynamic environment, a lifelong learning mindset will be crucial for professional success. Higher education institutions can play a critical role by offering flexible and modular learning opportunities that cater to the needs of working professionals. Online learning platforms and open educational resources can further democratize access to knowledge and skill development opportunities. Ultimately, the most successful individuals will be those who embrace continuous learning, adapt their skillsets to meet evolving industry demands, and navigate the ever-changing landscape of the workforce with agility and resilience.

As the world of work continues to evolve at an unprecedented pace, the decision between pursuing higher education or acquiring specific skills remains a critical one. Both paths offer unique advantages and disadvantages, and the optimal choice depends on individual circumstances, career aspirations, and industry demands. Embracing a lifelong learning mindset and a willingness to adapt and upskill will be essential for success in the dynamic and ever-changing workforce of the future. Whether pursuing a traditional university degree, engaging in targeted skill acquisition programs, or utilizing a hybrid approach, individuals must be proactive in charting their own career paths and developing the skills and knowledge necessary to thrive in an increasingly competitive and technology-driven world.

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CGPSC 2024 Mains, Paper II, Essay: Higher Education Vs Skill Acquisition

Higher Education Vs Skill Acquisition

In an era where the landscape of the professional world is rapidly evolving, the debate between the pursuit of higher education and skill acquisition has become increasingly relevant. This essay aims to explore the nuances of both paths, their impact on individual careers, and their roles in the broader economic context.

Understanding Higher Education

Higher education traditionally refers to the formal education acquired at universities and colleges, leading to degrees like bachelors, masters, or doctorates. This form of education is often seen as a gateway to a plethora of career opportunities. It offers an in-depth understanding of a particular field, fosters critical thinking, and promotes a broader worldview. As the Indian philosopher Dr. Sarvepalli Radhakrishnan rightly said, “The true teachers are those who help us think for ourselves.” Higher education is not just about acquiring knowledge; it’s about learning to think critically and independently.

The Essence of Skill Acquisition

Skill acquisition, on the other hand, is more focused and practical. It involves the direct learning of skills that are applicable in specific jobs or industries. These skills can be obtained through vocational training, apprenticeships, or even through online courses and workshops. The primary aim here is proficiency in a particular task or set of tasks, often with immediate application in the job market. As the famous saying goes, “Knowledge is of no value unless you put it into practice.” Skill acquisition embodies this principle, emphasizing practical application over theoretical understanding.

The Pros and Cons of Higher Education

Higher education, while offering a broad base of knowledge, often comes with its challenges. It can be time-consuming and expensive, with no guarantee of job security in the current economic climate. However, it does provide a comprehensive understanding of a subject, encourages intellectual development, and often opens doors to higher-paying job opportunities. In a world where interdisciplinary knowledge is increasingly valued, higher education can provide a competitive edge.

The Practicality of Skills

Skill acquisition is generally more cost-effective and time-efficient. It is highly targeted, equipping learners with specific skills that are in demand in the job market. This approach is particularly beneficial for those who require immediate employment or wish to quickly start a career. However, it may lack the breadth of knowledge and the development of critical thinking skills that higher education provides.

The Interdependence of Higher Education and Skills

It’s important to note that higher education and skill acquisition are not mutually exclusive. In fact, they are often interdependent. Many higher education programs now incorporate practical skill training as part of their curriculum. Similarly, those who pursue skill acquisition may find that a certain level of formal education enhances their understanding and effectiveness in their chosen field.

Economic Perspectives

From an economic standpoint, both higher education and skill acquisition play crucial roles. A well-educated workforce is essential for the advancement of technology, science, and culture. However, skilled workers are the backbone of many industries, driving practical applications and innovations. The global economy requires a diverse range of talents and capabilities, and thus, both higher education and skill acquisition are vital.

The Personal Dimension

On a personal level, the choice between higher education and skill acquisition depends on individual goals, interests, and circumstances. For some, the pursuit of an academic degree is a journey of intellectual fulfillment and a stepping stone to a desired career path. For others, acquiring specific skills is a more direct and practical route to employment and career progression.

Conclusion: A Harmonious Blend for Future Success

In conclusion, both higher education and skill acquisition are essential components of personal and professional development. They each have their unique strengths and limitations. The key lies in finding a harmonious blend that suits one’s personal aspirations and the demands of the evolving job market. As Rabindranath Tagore beautifully expressed, “The highest education is that which does not merely give us information but makes our life in harmony with all existence.” The future will likely see a more integrated approach, where academic learning and skill training coexist and complement each other, paving the way for a more versatile and adaptable workforce. This balanced approach will not only benefit individuals but also contribute to the broader socio-economic development, leading to a more prosperous and enlightened society.

MCQ BASED ON ESSAY

Question 1: What is the primary focus of higher education? Option 1: Direct job-specific skills Option 2: In-depth understanding of a field Option 3: Short-term vocational training Option 4: Immediate employment opportunities

Correct Answer: In-depth understanding of a field

Question 2: What is the main benefit of skill acquisition? Option 1: Comprehensive subject knowledge Option 2: Development of critical thinking Option 3: Cost-effectiveness and practicality Option 4: Pursuit of academic research

Correct Answer: Cost-effectiveness and practicality

Question 3: Which Indian philosopher is quoted regarding the true purpose of teachers? Option 1: Swami Vivekananda Option 2: Dr. Sarvepalli Radhakrishnan Option 3: Rabindranath Tagore Option 4: Jiddu Krishnamurti

Correct Answer: Dr. Sarvepalli Radhakrishnan

Question 4: What does the essay suggest about the relationship between higher education and skill acquisition? Option 1: They are mutually exclusive Option 2: They are essentially the same Option 3: They are interdependent Option 4: No relationship is suggested

Correct Answer: They are interdependent

Question 5: What is a major challenge of higher education mentioned in the essay? Option 1: Lack of practical skills Option 2: Time-consuming and expensive Option 3: Limited career opportunities Option 4: Overemphasis on technology

Correct Answer: Time-consuming and expensive

Question 6: Which of these is a primary aim of skill acquisition? Option 1: Academic research Option 2: Intellectual development Option 3: Proficiency in a specific task Option 4: Interdisciplinary knowledge

Correct Answer: Proficiency in a specific task

Question 7: What role does skill acquisition play in the economy? Option 1: It has no significant impact Option 2: Drives practical applications and innovations Option 3: Only supports academic research Option 4: Reduces job opportunities

Correct Answer: Drives practical applications and innovations

Question 8: What personal factors influence the choice between higher education and skill acquisition? Option 1: Economic status only Option 2: Geographical location Option 3: Individual goals and interests Option 4: Age of the individual

Correct Answer: Individual goals and interests

Question 9: What is a disadvantage of skill acquisition, according to the essay? Option 1: High cost Option 2: Lack of critical thinking skills Option 3: Time-consuming nature Option 4: Overemphasis on theory

Correct Answer: Lack of critical thinking skills

Question 10: Who is quoted in the essay about harmony with all existence? Option 1: Mahatma Gandhi Option 2: Dr. APJ Abdul Kalam Option 3: Swami Vivekananda Option 4: Rabindranath Tagore

Correct Answer: Rabindranath Tagore

Question 11: What is the essay’s perspective on the future of education and skill training? Option 1: They will remain separate Option 2: A more integrated approach Option 3: Skill training will become obsolete Option 4: Formal education will be phased out

Correct Answer: A more integrated approach

Question 12: According to the essay, what does higher education often open doors to? Option 1: Specific technical skills Option 2: Immediate job placements Option 3: Higher-paying job opportunities Option 4: Manual labor jobs

Correct Answer: Higher-paying job opportunities

Question 13: What does the essay suggest about the economic value of higher education? Option 1: It has limited economic value Option 2: Essential for cultural advancement only Option 3: Crucial for technological and scientific advancement Option 4: Unrelated to the economy

Correct Answer: Crucial for technological and scientific advancement

Question 14: What does the essay imply about the breadth of knowledge in skill acquisition? Option 1: It is extensive and comprehensive Option 2: It is limited to practical skills Option 3: It is focused on academic research Option 4: It is irrelevant

Correct Answer: It is limited to practical skills

Question 15: How does the essay describe the impact of skill acquisition on employment? Option 1: Negligible impact Option 2: Decreases employment opportunities Option 3: Quick start to a career Option 4: Leads to academic careers

Correct Answer: Quick start to a career

Question 16: According to the essay, what is important for a more versatile and adaptable workforce? Option 1: Focus solely on higher education Option 2: Neglect skill-based training Option 3: Balanced approach to education and skill training Option 4: Emphasis on technology only

Correct Answer: Balanced approach to education and skill training

Question 17: What is a major benefit of higher education in the context of the job market? Option 1: Immediate job placement Option 2: Short-term skills Option 3: Competitive edge Option 4: Manual labor skills

Correct Answer: Competitive edge

Question 18: How does the essay view the role of higher education in interdisciplinary knowledge? Option 1: It has no role Option 2: Plays a minor role Option 3: Significant role Option 4: Discourages interdisciplinary knowledge

Correct Answer: Significant role

Question 19: What does the essay suggest is crucial for personal and professional development? Option 1: Exclusively pursuing higher education Option 2: Ignoring formal education Option 3: A mix of education and skill acquisition Option 4: Focusing only on practical skills

Correct Answer: A mix of education and skill acquisition

Question 20: According to the essay, what is the role of vocational training in skill acquisition? Option 1: It has a minimal role Option 2: Primary method of acquiring skills Option 3: Only suitable for certain professions Option 4: Not recommended

Correct Answer: Primary method of acquiring skills

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Skills vs College Degrees: Key element reinventing the future of work

Given the estimates of the world economic forum – more than 1 billion jobs, almost one-third of all jobs worldwide are likely to be transformed by technology in the coming decade..

SNS | New Delhi | October 29, 2021 5:42 pm

(Representational Image: iStock)

Colleges have been in existence for ages. Right from the advent of humanity, colleges have been a go-to place to learn, acquire knowledge and get exposure to the outside world. Generations have spent the first third of their lives in colleges to acquire a degree and create a bright future ahead. However, the world as we see it today isn’t the same as it was two decades ago. The degrees obtained were the only proof of eligibility to get placement in the industry, which of course is no longer true.

According to the facts, around 3.7 Cr students are enrolled in higher education (Source: 2019 Aishe.nic.in report) across multiple degrees and colleges. Although the number of jobs rolled out and the so-called successes measures is less than 10% i.e., not even 37 Lacs students are getting jobs after completing their degrees. This represents the future of work will not be just about college degrees and qualifications.

With the emergence of the gig economy, the nature of work is more about skills. Given the estimates of the World Economic Forum – more than 1 billion jobs, almost one-third of all jobs worldwide are likely to be transformed by technology in the coming decade. The accelerated digital adoption has already made this happen. For instance – the conventional way of buying groceries, ordering medicines and other essential items have already transformed and become digital. Now even small stores or retailers are moving to app-based businesses to increase their customer base and retain the existing ones. This has opened up several avenues for people to work in a digitally-driven world.

Further, the COVID-19 downturn has given ample reasons to students and professionals to join upskilling and skilling programs to accelerate their careers in the modern economy. The shift in the focus from college degrees to skills is enabling diversity and inclusion in the workforce. Apart from this, it fills the widening employment gaps by selecting the candidates based on their talent, not just merit or degrees.

Modern, talent-based education

In the traditional old school corporates skills used to generally take a back seat and candidates with a college degree used to get a job because they were the only available handful of resources. However, India is soaring with new unicorns every single day. The country is becoming a global leader in the startup ecosystem and the whole paradigm has been shifted towards a massive number of hirings based on skills.

Startups are agile, result-oriented and focused on deliverability with little-to-no hierarchy. Startups are setting the tone of modern work culture and they choose people who can get the work done. That’s the topmost parameter, “Get Work Done” and thus, skills have now taken a front-seat then come college degrees.

Acquisition of soft skills

As the world has moved towards digitalization, soft skills have become key to the modern economy. They refer to the personal attributes mainly – interpersonal skills of a person who can interact, convince and win a deal. They cover a wide array of skills such as working in diversity, teamwork, management, inclusion at the workplace, etc. Unfortunately, colleges and universities do not include learning these skills in their curriculum.

According to the World Economic Forum’s Future of Jobs report – complex problem solving, critical thinking, creativity, people management and emotional intelligence will be the most important skills required in the workplace by 2025. The emergence of unicorns and new-age startups are proving to people that developing soft skills is the need of the hour in order to win a business deal or accelerate a career.

Digital learning

The outbreak of the COVID-19 pandemic has taught the world that online learning is possible. Infact, it has become a key to learning and exchanging skills. It is the potential of digital connectivity that makes skill-based education easily accessible for people across the globe. Even international universities are collaborating with edtech platforms to facilitate digital learning and enroll students in modern education programs. Presently, 3 out of 5 students are now enrolled in online courses learning through ed-tech platforms to cope up with the outdated-college curriculum.

College or no-college has been a heated debate of this decade. Even many billionaires and successful entrepreneurs who have dropped out of college claim that colleges are losing their essence. Thus, skills definitely have many reasons to support the modern economy than the abilities of college degrees.

(By Pallavi Hirwani, Head of Business Growth, GetWork)

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Please note you do not have access to teaching notes, learning in higher education: towards knowledge, skills and competency acquisition.

International Journal of Educational Management

ISSN : 0951-354X

Article publication date: 18 September 2019

Issue publication date: 1 October 2019

Considering the importance of human capital in innovation, entrepreneurship and thus economic development, this study attempts to examine formal learning as a mechanism of human capital development in institutions of higher learning. Ironically, students in such institutions are automatically assumed to learn and accumulate pertinent capacity, which would then enable them to compete in the business world or pursue further studies in future. Consequently, lack of this cognizance culminates in little being known about how students learn to accumulate knowledge, skills and requisite competencies. Notwithstanding this, the challenges posed in the twenty-first century require well-rounded students those especially who can address the global transformations witnessed in the business arena. The purpose of this paper is an attempt to fill this gap using data from the University of Dubai (UD) to examine how formal learning takes place in an institution and what determines it.

Design/methodology/approach

Learning is conceptualized in terms of knowledge, skills and competencies accumulated as proxied by cumulative general point aggregate. All the data used came from the UD. In addition to in-depth descriptive analysis, the study uses limited dependent techniques to identify the most significant determinants of institutional learning.

The empirical results generated indicate that demographic characteristics such as age, nationality and gender had a positive effect on learning. Moreover, a student’s initial condition influenced his/her learning positively. Whereas the mode of study under personal preferences did not seem to affect learning, the number of course sections taken had a positive influence on learning. As anticipated, student transfer had a negative influence on learning. The number of credit hours accumulated affected learning positively.

Research limitations/implications

The main limitation of this study is that results are only applicable within a limited geographical scope, and thus they cannot be generalized for global consumption. Nonetheless, the discussion and results obtained make insights to any future-related studies.

Originality/value

As pointed out in the previous sections, learning will be conceptualized in the form of knowledge, skills and competency acquisition. In a school setting, knowledge, skills and competencies are better captured by the grade attained in each subject. The general student learning can, therefore, be equally captured by the cumulative grade point aggregate. The authors purport that learning can be visualized, or in other words conceptualized, as a complex process that is determined by five main factors that include demographic characteristics; student initial condition; personal preferences and choices; and time factor curriculum and anticipated future career.

Competencies
Limited dependent models

Gachino, G.G. and Worku, G.B. (2019), "Learning in higher education: towards knowledge, skills and competency acquisition", International Journal of Educational Management , Vol. 33 No. 7, pp. 1746-1770. https://doi.org/10.1108/IJEM-10-2018-0303

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ORIGINAL RESEARCH article

Basic skills in higher education: an analysis of attributed importance.

$\r\nLourdes Aranda*$

1 Department of Research Methods and Diagnosis in Education, University of Málaga, Málaga, Spain
2 Department of Developmental and Educational Psychology, University of Granada, Granada, Spain

Today, the skills-based approach is increasingly in demand by companies due, in large part, to the fact that it favors the management of human resources by focusing on individual capabilities; which, finally, improves the job profile of a company. As a result, choosing the right candidates has become increasingly selective. Universities, therefore, need to teach skills to improve the incorporation of graduates into the workplace making it as successful as possible. For this reason, it is of special relevance to know if college students consider that the acquisition of skills is key for their incorporation into the workplace. The main objective of this study was to analyze and compare the importance assigned to the acquisition of basic skills in the university education of 694 students studying four different bachelor degrees: pedagogy, early childhood education, primary education, and psychology. For this purpose, a Likert-type questionnaire on basic skills was distributed with four possible options and the following five dimensions that grouped basic skills: organizational and planning capacity; access to information sources; analysis and synthesis of texts, situations, and people; teamwork; and problem solving. The results show that as a whole all students across different bachelor degrees gave a high score to the acquisition of basic skills, with early childhood education students giving it greater importance compared to the students from other disciplines and, more specifically, differences were observed in some dimensions depending on the bachelor degree that they have started.

Introduction

In recent decades, a continuous and profound change has been taking place in social and labor reality, necessitating universities to regularly adapt to the new professional needs that the labor market demands from future graduates ( Martínez-Clares and González-Morga, 2018 ; Pineda-Herrero et al., 2018 ; Rodríguez-Gómez et al., 2018 ). In fact, it is well known that the prestige of universities depends on the success of graduates, and this is one of the pillars of the triple helix, along with industry and government ( Etzkowitz and Leydesdorff, 2000 ).

With the old university model, educational institutions sought to prepare professionals without paying much attention to the labor insertion of these people once they had completed their university studies, and without concern about whether they would be able to acquire a job associated with their qualification. However, in Spain, BOE (1983) , resulted in the implementation of a new training model based on skills, and university education has undergone an important transformation which has generated a new university model in which a great interest can now be seen in all aspects concerning the insertion in the job market of professionals trained at universities ( Eslava-Suanes et al., 2018 ; García-Blanco and Cárdenas, 2018 ; Gutiérrez et al., 2019 ; Baquero and Ruesga, 2020 ). According to Torres and Vidal (2015) , “To talk about employability is to talk about aptitudes and attitudes, about a vital syllabus and about good personal qualities; that is, better or worse possibilities of access and adaptation to the job world” (p. 65).

If not addressed, the expense that this education entails would represent a relevant social and economic “loss,” since the money and resources spent on training these students would not be economically or socially profitable, nor would there be any benefit from the time and resources used ( Galcerán, 2010 , p. 94).

One of the key aspects in this transformation of the teaching–learning processes in European universities, and specifically Spanish ones, is the syllabus design based on learning by skills ( Pozo and Bretones, 2015 ; Calderón et al., 2018 ). However, even though more than two decades have passed since the implementation of a syllabus based on the acquisition of skills in European universities, the member states point out a multitude of difficulties in implementing this methodology ( Ramírez-García, 2016 ).

In a more general sense, the term “skills” refers to the norms, techniques, procedures, attitudes, and abilities that future graduates acquire as they go through university, to perform their professional functions appropriately ( Biccoca, 2018 ; Martínez-Clares and González-Morga, 2019 ; Gargallo et al., 2020 ). Therefore, the emphasis on skills “would mark the importance given to the student’s own learning and to the development of their ability to interact creatively with the environment” ( Galcerán, 2010 , p. 104).

In the Tuning Educational Structures in Europe Project, an exhaustive distinction of skills or competences is presented: “[…] skills can be divided into skills related to a field of expertise (specific to a field of study), and generic skills (common for different courses)” ( Tuning Project, 2007 , p. 37). The generic or basic skills identify shared attributes which could be general to any degree, such as the capacity to learn, decision making capacity, project design and management skills, which are developed in all study programs. On the other hand, subject-specific skills refer to theoretical, practical and experimental skills and knowledge for a specific area or study program. Therefore, it can be said that transversal, generic, or basic skills refer to the elements common to any degree, while specific skills refer to the elements of each degree. In Spain, Ministry of Education and Science (2007) by which the organization of official university education was established, reference was already made to the establishment of two types of skills in college education with the purpose that the knowledge, skills, and abilities acquired in universities can be adequately adapted to the demands of the job market.

Nevertheless, there is still a significant gap between the knowledge, skills, and abilities that students acquire in their college studies and the required demands of the job market ( Planas, 2010 ; Wild and Schulze-Heuling, 2020 ). Following this line, some authors point to the existence of a clear mismatch between the capacities and abilities learned by students in universities and the professional capacities required in the labor market for a successful performance of the tasks and functions in different jobs ( Martínez-Clares and González-Morga, 2018 ; Aranda et al., 2021 ). This mismatch is currently presented as a great problem in the higher education system and, therefore, it is recommended that all the agents that make up the educational system reach consensus on the practical training of students ( Pujol-Jover et al., 2015 ; Cabezas-González et al., 2017 ).

It is recommended that, at all levels in educational institutions, the development and acquisition of skills is promoted, and especially of transversal, generic, or basic skills, which are those that really provide the student body with great flexibility in different work functions and the ability to adapt to different jobs ( Méndez et al., 2015 ; Rodríguez-Gómez, 2018 ). In this sense, there are various works that are relevant to the role of praxis by teaching staff, since they consider that professors are really those who are trained to improve and innovate the learning of college students ( Biesta, 2015 ; La Rosa, 2015 ; Méndez et al., 2015 ).

Less importance has been given to the figure of the student body. However, college students must be motivated to acquire skills. Previous research shows that, even in stages prior to university, student interest is a key factor for adequate academic training ( Rodríguez et al., 2020 ). All of this, together with the increasingly active role of the student body in their training ( Aranda et al., 2015 ; López-Núñez et al., 2019 ), renders the attitude and motivation of students in university education with regard to skills as relevant ( Centeno and Cubo, 2013 ).

Previous research analyses the perception of students in the acquisition of competences in the different university degrees ( Gimeno-Santos and Martín-Cabello, 2007 ; Gómez-Puertas et al., 2014 ; Belmonte-Almagro et al., 2019 ). It is worth highlighting the work carried out by Belmonte-Almagro et al. (2019) , where it is shown how, at a global level, students value the acquisition of competences in universities acceptably. Following this same line of research, in the study by Gimeno-Santos and Martín-Cabello (2007) , a high score was also obtained in the importance attributed to the acquisition of competences in the Degree of Psychology by the students. More specifically, in the work of Gómez-Puertas et al. (2014) , it is concluded that the students of the Degree in Journalism manifest a positive assessment in the acquisition of skills related to the capacity for critical and reflective analysis on their own actions.

The fact that students value the acquisition of competences very positively is of special relevance, since, if university students do not value training through the acquisition of competences, they will not be motivated and, therefore, they will not be adequately trained professionally. It is important that students value skills favorably, since they are an active part of the teaching-learning process.

Therefore, the general objective of this research was to analyze the importance assigned to the acquisition of generic or basic skills by college students in 1st-year study of different degrees and to identify if there are differences in said assessment depending on the degree under study. This research attempted to answer the following questions: What assessment do students give to the acquisition of skills in higher education when they begin their undergraduate studies? Are there differences among the students regarding the importance attributed to the acquisition of skills depending on the degree they are studying?

Materials and Methods

Participants.

The sample was selected through a non-probabilistic and intentional sampling, based on accessibility criteria. This sample consisted of 694 students belonging to four disciplines in the faculties of Educational Sciences and Psychology at the Universities of Malaga, Granada, and Seville, specifically in pedagogy, early childhood education, primary education, and psychology (see Table 1 ). Of the total participants, 6.9% were men and 93.1% were women. The difference in ratio between male and female students is due to the fact that the degrees considered in this research are biased by gender. As is well known, the educational trajectories between women and men differ and in some subjects one gender prevails over another. Specifically, in the degrees considered in this study, the female gender predominates over males.

Table 1. Distribution of students by bachelor degree.

Instruments

To assess the importance given to basic skills, a questionnaire consisting of 52 items was used, adapted from Gimeno-Santos and Martín-Cabello (2007) . The response format used was a Likert 4-point scale with the following options (1 = not at all, 2 = little, 3 = fairly, and 4 = a lot).

The items were grouped into five dimensions, each related to the basic skills expected of college students: Organizational and planning capacity (OP; e.g., “Have the necessary information to be able to carry out an academic work”); access to information sources (AF; e.g., “Knowing how to search in a library or newspaper archive for all the information you need”); analysis and synthesis of texts, situations, and people (AT; e.g., “Be able to synthesize a text”); teamwork (TE; e.g., “Actively listen to people”); and problem solving (RP; e.g., “Ability to understand that the same situation can have different ways of solution”).

The reliability of the questionnaire was calculated using Cronbach’s Alpha test based on the analysis of the responses of the 694 male and female students surveyed, and shows a high index of internal consistency (α = 0.895). For each scale, the reliability values were also adequate; specifically, for organizational and planning capacity, the α value was 0.716; access to information sources, 0.849; analysis and synthesis of texts, situations, and people, 0.835; teamwork was 0.725; and finally, in the problem-solving dimension, the α value was 0.800.

All data were collected during the second term of the academic year 2018–2019 and 2019–2020 at the Universities of Málaga, Granada, and Sevilla. Table 2 shows the distribution of students by universities and degrees.

Table 2. Distribution of students by universities and degrees.

At the beginning of each data collection session, a brief explanation of the test was given to the participants, urging them to answer the question “if you were a professional of… do you regard it as important.” In addition, informed consent was requested and provided, and the confidential nature of the information collected was communicated.

Data Analysis

The methodology used in this research was quantitative. First, a descriptive analysis of the variables among the degree courses and the different dimensions contemplated in the questionnaire was conducted. Subsequently, a t -test analysis to assess gender differences, and an analysis of variance (ANOVA) test was run to determine if there were differences in the importance given to skills based on the course taken. Then, in order to verify the differences between the groups, Tukey’s post-hoc test (multiple comparisons) was performed. Finally, to estimate the effect size, Cohen’s d for t -test and partial eta square (η 2 p ) for ANOVA was applied, with the following considerations in terms of value: for Cohen’s d values of 0.1 represents a small effect size, 0.3 represents a medium effect size and 0.5 represents a large effect size ( Field et al., 2012 ); for partial eta square: 0.0099 = small, 0.0588 = medium, and 0.1379 = large ( Richardson, 2011 ).

First, the means and standard deviations by dimension were analyzed, and the findings were that students, in general, attribute a high or very high average score to the importance of basic skills, with values exceeding three points out of four (see Figure 1 ). Therefore, it can be said that the skills perceived by students as more important or necessary for their professional development would be those framed in dimension 1 (organizational and planning capacity) followed by dimension 5 (problem solving), while those perceived as the least important for their professional career would be in dimension 2 (access to information sources).

Figure 1. Mean scores of basics skills.

Regarding gender, significant differences were observed between men and women in the importance given to Capacity for organization and planning ( t (687) = −3.675, p < 0.001, d = 0.374) and Problem solving ( t (687) = −3.476, p = 0.001, d = 0.354). In both cases, women scored higher than men in the importance given to these basic skills. In the case of Capacity for organization and planning, women scored on average 3.701 (SD = 0.375) and men 3.55 (SD = 0.385), for Problem solving women’s scores were on average 3.647 (SD = 0.350) and for men 3.521 (SD = 0.359).

Subsequently, an ANOVA was carried out to explore whether there were differences in the importance given to basic skills according to university degree ( Table 3 ). The results in all the analyses were significant, so the degree taken influences the importance attributed to the skills. The effect sizes were in all cases medium, with the lowest being for teamwork (0.039) and the highest for organization and planning capacity (0.070) and problem solving (0.066).

Table 3. One-way Analysis of Variance (ANOVA).

To determine the differences between groups, the Tukey post-hoc contrast test was performed. The mean scores for each dimension by bachelor degree are shown in Table 3 .

With reference to the first dimension analyzed (capacity for organization and planning), significant differences are observed between the importance given to this dimension by the early childhood education degree students, whose score is significantly higher than students in the pedagogy degree ( p < 0.001; 95% CI = [0.1446, 0.3603]), primary education degree ( p < 0.001; 95% CI = 0.1333, 0.3149]) and psychology degree ( p < 0.001; 95% CI = [0.0696, 0.2980]).

An analysis of the second dimension (access to information sources), shows that primary education degree students score significantly lower in this dimension compared to students in pedagogy ( p < 0.001; 95% CI = [−0.3431, −0.0814]), early childhood education ( p < 0.001; 95% CI = [−0.3668, −0.1302]), and psychology ( p < 0.01; 95% CI = [−0.3246, −0.0452]) degrees.

In the case of the third dimension (analysis and synthesis of texts, situations, and people), the Tukey test revealed differences in the scores of studying early childhood education degree compared to primary education ( p < 0.001; 95% CI = [0.1133, 0.3088]) and psychology ( p < 0.05; 95% CI = [0.0185, 0.2645]) degrees, with early childhood education degree students scoring the highest in this dimension. In addition, students of the degree in pedagogy scored higher than those in primary education degree ( p < 0.05; 95% CI = [0.129, 0.2291]).

Referring to the analyses carried out on the fourth dimension (teamwork), statistically significant differences are once again observed between students of the pedagogy and early childhood education degrees ( p < 0.05; 95% CI = [−0.2104, −0.0031]), and between the early childhood education degree students and those taking the primary education ( p < 0.001; 95% CI = [0.0855, 0.2599]) and psychology degrees ( p < 0.01; 95% CI = [0.0456, 0.2651]), respectively. In all cases, the group of early childhood education degree students attributed greater importance to the teamwork dimension.

Finally, if we consider dimension 5 (problem solving), again the students of the early childhood education degree obtain a significantly higher score when compared with the students of the pedagogy ( p < 0.01; 95% CI = [0.0794, 0.2815]), primary education ( p < 0.001; 95% CI = [0.1211, 0.2912]) or psychology ( p < 0.001; 95% CI = [0.1226, 0.3366]) degrees.

In short, there are statistically significant differences between all the degrees participating in this research with slight nuances although, after the analyses, the students in early childhood education degree stand out as the group that placed the highest values on the five dimensions measured by the questionnaire, as basic and necessary skills required by an educational professional.

The objective of this paper was to evaluate the importance assigned to the acquisition of skills by 1st-year college students of different degrees and to identify if there are differences in such assessment depending on the type of studies, since different studies ( Rabanal et al., 2020 ; Sarceda and Barreira, 2021 ) show that academic training in competencies is one of the key points in the face of labor insertion, a comprehensive training that considers both personal and social motivations so highly valued in the world of work.

Overall, the results obtained show high scores in the importance attributed to basic skills by the four degrees considered in this research. Although a positive assessment by the students of the different groups is observed, according to our results, on the one hand, statistically significant differences were observed between the different study groups (degrees) and by gender, although with a moderate effect size. The sample of this work had a greater number of female participants, something common in education and psychology degrees in Spain. The two skills that have shown significant differences are usually associated with males, since there are gender stereotypes in relation to educational skills such as problem solving ( Zhu, 2007 ). It is possible that women, considering that they possess these skills to a lesser extent, attach more importance to their development than men.

On the other hand, we note that the early childhood education students placed highest value on the five basic skills included in this research compared to the three remaining groups (pedagogy, primary education, and psychology). All these differences observed between the different degrees can be explained, at least in part, by the characteristics of each degree and the target audience they are targeting.

Following this line of thought, the study undertaken by Meroño et al. (2018) indicates that, in addition to the perception of teachers and educational agents, it is necessary to be aware of the perception of students in their own skills learning since their opinion is essential to improve the learning processes in terms of skills. This is especially important in students with special educational needs, since the development of their abilities and skills require specialized attention from teachers ( Tanu and Kakkar, 2018 ; Kakkar, 2020 ).

This aspect arouses great interest, since the students’ perceptions of their own knowledge, the importance they give to the teaching methodology, and the motivation toward their teaching process is key to achieving greater involvement in their own training ( Castells et al., 2015 ; Martínez-Clares and González-Morga, 2018 ). In fact, one of the great challenges of the university is that the students become the main figure in their entire college learning process by actively participating in their training ( Silva, 2017 ; Pegalajar, 2020 ).

The importance of this research has to do with a recently coined term, “academic commitment,” which could be defined as a concept that includes a wide variety of student behaviors and academic practices such as time spent on academic tasks, adaptability, social and academic integration, and teaching methodology ( Kahu and Nelson, 2018 ). Basically, this concept refers to the importance of the opinions and well-being of the students in every way in order to achieve adequate academic preparation that helps them face the important changes that are taking place in society and specifically the demands of the job market ( Martínez-Clares and González-Lorente, 2018 ).

Therefore, it becomes necessary to remove one of the major drawbacks to planning and developing teaching–learning methodologies taught in universities such as the importance that has always been ascribed to the theoretical aspect of the subjects compared to the practical function. Several authors have pointed out that, in general, at university much importance is given to the theoretical content of subjects, while the job market demands that future workers “know how to do it” ( Alonso et al., 2009 ; Jackson, 2012 ; Torres and Vidal, 2015 ). This explains why some authors demand greater coordination between university training and the demands of the job market ( Cabrera et al., 2016 ).

Similarly, Ellwanger and Andreucci (2017) refer to the need for college professor teachers to undertake comprehensive training of students, so that in addition to theoretical knowledge, students develop practical and motivational skills. Regarding the development of practical skills, an important issue must be kept in mind, that is, to efficiently implement skills in the current academic curriculum design in universities ( Calderón et al., 2018 ; Glaesser, 2019 ; Ahmed and Khairy, 2020 ). This inevitably leads us to reflect on the training of professors in higher education to apply teaching–learning strategies based on skills, particularly basic skills. At this point, several problems in universities can be highlighted, the main issue being that despite working in a higher-level institution the vast majority of university teaching staff have not had specific training outside of the skills of their field of expertise, let alone received pedagogical training to carry out their professional careers, unlike the other educational levels. This is a paradox since they are required to teach skills without having previously received any training in this regard. Faced with this professional challenge, the pedagogical training of professors is key to professional success ( Más-Torello, 2011 ).

Another problem faced by professors is that they generally have very high ratios in the number of male and female students, and this renders a more personalized teaching among professor-students that favors the acquisition of skills impossible. Furthermore, the time availability of college teaching staff must be considered since, very often, professors do not have the available time to enable them to propose subjects, including the skills to be developed and the way to assess them ( Villarroel and Bruna, 2014 ). For this reason, it is essential that teachers participate in and grant special dedication to the inclusion of basic skills in their methodological strategies ( Villarroel and Bruna, 2014 ). It is essential for professors to reflect on and review these methodological strategies when considering the perception and importance placed by students on the acquisition of transversal, generic, or basic skills in their college studies ( Rodríguez-Gómez et al., 2018 ), as it has been possible to verify after the results of this research, since the 5 groups of students have a great motivation toward learning by competences.

Based on the above, we can affirm that, if students consider the inclusion of skills in the syllabus to be important, they will show a predisposition to be part of their skills learning and, with this, progress can be made in two basic aspects in the higher educational context. One of these aspects would be the progressive increase in the participation of students in their own college education, thus achieving a more autonomous and active role ( López-Núñez et al., 2019 ); and the other would be motivation in teaching methodologies, which is key to performance and would lead to academic success.

Within the inclusion of skills in the syllabus of the different degrees of our universities, the so-called generic, transversal, or basic skills are of special interest since, if the development of these most basic abilities and skills is encouraged, students will learn to adapt more satisfactorily in the social sphere and, more specifically, in the workplace in increasingly changing contexts. In this sense, Brussels has proposed the preparation of students for their adequate adaptation to the increasingly profound changes in the job market, training citizens of increasingly digital and global societies ( Consejo de la Unión Europea, 2018 ).

This study has some limitations: Although the sample is large, the data was collected at a single point in time. In the future, longitudinal studies should be added to establish the importance given to skills changes as students advance through the years. On the other hand, it would be useful to know the importance ascribed to these skills by those studying college degrees in other fields and to compare the results.

In conclusion, universities must prepare both professors and their students for the new challenges of the 21st century. It is necessary for professors to train in skills to be able to teach them. In addition, it is important to take into account the attitude and perception of all educational agents, and more especially the perception of students as the main educational agent in the university context. The need to identify which skills are demanded by the job market to adjust both the basic and specific skills of students in an academic context to the labor demands must be considered. For this reason, it is also essential to pay attention to the companies that employ graduates, since they provide hints on the skills currently being demanded in a changing society in which employment has to gradually transform and reinvent itself on a daily basis. In this way, the educational quality will increase, and the professional success of the students will be more likely.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

LA designed the study, supervised the data collection, and wrote the manuscript. EM-R carried out the statistical analysis and wrote the manuscript. LR supervised the data collection and assisted with writing the article and edited the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : self-perceptions, basic skills, higher education, college students, attributed importance, teaching method

Citation: Aranda L, Mena-Rodríguez E and Rubio L (2022) Basic Skills in Higher Education: An Analysis of Attributed Importance. Front. Psychol. 13:752248. doi: 10.3389/fpsyg.2022.752248

Received: 02 August 2021; Accepted: 10 January 2022; Published: 08 February 2022.

Reviewed by:

Copyright © 2022 Aranda, Mena-Rodríguez and Rubio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lourdes Aranda, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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University student satisfaction and skill acquisition: evidence from the undergraduate dissertation.

1. Introduction

“The key to success in degree studies may be adapting the study plans to achieving specific competences and meeting the students’ expectations in terms of their insertion in the socio-professional reality of the twenty-first century, thereby achieving a high level of satisfaction while they are studying and once they have left university”.

1.1. Student Satisfaction

1.2. skills perception, 1.3. motivation, 1.4. intellectual curiosity.

“Goals oriented towards developing competences (i.e., towards dominating a specific field of activity or knowledge) place more value on the personal improvement that can be achieved through the activity than the results that can be evaluated by external criteria. This explains their stronger relationship with an intrinsic motivation (by the action in itself), than with an extrinsic motivation (the means to reach another goal)”.

1.5. Potential Moderators: Effort and Relationship with the Tutor

2. materials and methods, 2.1. idenfication of hypotheses and suggested model, 2.2. data collection, 2.3. measurement of latent variables, 3.1. descriptive analysis, 3.2. measurement model, 3.3. structural analysis, 4. discussion and conclusions, author contributions, conflicts of interest.

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Click here to enlarge figure

Measurement	Construct
The complex problems attract me than simple ones (NEED1)
For me, thinking is fun (NEED2)
I enjoy thinking and reflection (NEED3)
I prefer a difficult, important intellectual task over one that does not require much thought, whether it’s important or not (NEED4)
Overall, my motivation when completing the UD was good (MOTGLOB)
Being able to define the objectives of the project (SKILL1)
Being able to organise the project (SKILL2)
Knowing how to look for relevant information (SKILL3)
Using knowledge I acquired during my studies (SKILL4)
Being able to organise the information (SKILL5)
Identifying the limitations of my project (SKILL6)
Developing my research abilities (SKILL7)
Developing my working capacity (SKILL8)
Developing my ability to manage information (SKILL9)
Improving my ability to define problems (SKILL10)
Improving my ability to solve problems and make decisions (SKILL11)
Improving my ability to analyse and summarise data (SKILL12)
Improving my ability to work autonomously (SKILL13)
Improving my ability to properly present the results in writing (SKILL14)
I think that the UD has a real use in the world of business (REALUTIL)
I think that the UD provided me with important training for my professional career (FUTURUTIL)
The learning method reinforced my knowledge about other subjects on the degree course (REINFORCEUTIL)
Overall I am satisfied with the information I received about the UD (SAT1)
Overall I am satisfied with the evaluation system used (SAT2)
Overall I am satisfied with the virtual classroom for the subject (SAT3)
Overall I am satisfied with the teaching-learning method used (SAT4)

	N	Mean	Standard dev.	Skewness	Kurtosis
NEED1	130	3.531	1.0130	−0.400	−0.130
NEED 2	130	3.746	0.8099	−0.212	−0.419
NEED 3	130	3.162	0.9709	0.030	−0.275
NEED 4	130	3.615	0.9756	−0.277	−0.466
MOTIVATION	130	3.415	1.0251	−0.596	−0.131
SKILL1	125	3.680	0.9123	−0.686	0.627
SKILL2	125	3.688	0.9018	−0.755	0.782
SKILL3	124	3.758	0.9574	−0.635	0.377
SKILL4	123	3.382	1.0043	−0.293	−0.093
SKILL5	122	3.746	0.9232	−0.638	0.686
SKILL6	124	3.685	0.9907	−0.563	0.038
SKILL7	130	3.885	0.9033	−0.534	−0.124
SKILL8	130	3.977	0.9019	−0.657	0.034
SKILL9	130	3.731	0.9628	−0.647	0.378
SKILL10	130	3.377	0.9002	−0.559	0.620
SKILL11	130	3.469	0.9416	−0.612	0.729
SKILL12	130	3.815	0.8786	−0.599	0.450
SKILL13	130	3.831	1.0502	−0.871	0.482
SKILL14	130	3.346	1.0617	−0.336	−0.437
REALUTIL	130	2.900	1.1604	−0.074	−0.800
FUTURUTIL	130	2.946	1.1019	−0.208	−0.743
REINFORCEUTIL	130	2.700	1.1657	0.070	−1.003
SAT1	130	3.262	1.0823	−0.093	−0.891
SAT2	130	3.154	0.9762	−0.212	−0.469
SAT3	130	3.285	1.0728	−0.093	−0.891
SAT4	130	3.085	0.9886	−0.316	−0.207

Construct	Indicators	Factor Loadings	Cronbach’s Alpha	Composite Reliability	Variance Extracted
Intellectual curiosity	NEED1	0.59	0.74	0.75	0.44
	NEED2	0.769
	NEED3	0.741
	NEED4	0.513
Skills	SKILL1	0.739	0.94	0.94	0.51
	SKILL2	0.7
	SKILL3	0.629
	SKILL4	0.635
	SKILL5	0.678
	SKILL6	0.662
	SKILL7	0.683
	SKILL8	0.755
	SKILL9	0.743
	SKILL10	0.796
	SKILL11	0.753
	SKILL12	0.756
	SKILL13	0.778
	SKILL14	0.685
Utility	REALUTIL	0.923	0.84	0.85	0.65
	FUTURUTIL	0.851
	REINFORCEUTIL	0.622
Satisfaction	SAT1	0.795	0.81	0.84	0.50
	SAT2	0.724
	SAT3	0.587
	SAT 4	0.513

Constructs	Correlation	Error	(x,	,x)	Correlation
Skills-Utility	0.699	0.089	0.873	0.525	0.488601
Utility-Satisfaction	0.652	0.103	0.854	0.450	0.425104
Skills-Satisfaction	0.711	0.07	0.848	0.574	0.505521
Intellectual curiosity-skills	0.442	0.05	0.540	0.344	0.195364
Intellectual curiosity-Utility	0.377	0.076	0.526	0.228	0.142129
Intellectual curiosity-Satisfaction	0.349	0.057	0.461	0.237	0.121801
Skills-Utility	0.699	0.089	0.873	0.525	0.488601

	Theoretical (M )	M	M	M
Chi-square (CMIN)	471.222	484.978	489.652	503.130
Degrees of freedom (df)	288	289	289	290
CMIN/df	1.636	1.678	1.694	1.735
CFI	0.901	0.896	0.894	0.887
RMSEA	0.070	0.072	0.073	0.075

	Direct Effect	Indirect Effect	Total Effect
Intellectual curiosity→Motivation	0.265	0.000	0.265
Motivation→Skills	0.529	0.000	0.529
Intellectual curiosity→Skills	0.141	0.309	0.450
Skills→Utility	0.707	0.000	0.707
Utility→Satisfaction	0.291	0.000	0.291
Skills→Satisfaction	0.509	0.206	0.715

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Martínez-Roget, F.; Freire Esparís, P.; Vázquez-Rozas, E. University Student Satisfaction and Skill Acquisition: Evidence from the Undergraduate Dissertation. Educ. Sci. 2020 , 10 , 29. https://doi.org/10.3390/educsci10020029

Martínez-Roget F, Freire Esparís P, Vázquez-Rozas E. University Student Satisfaction and Skill Acquisition: Evidence from the Undergraduate Dissertation. Education Sciences . 2020; 10(2):29. https://doi.org/10.3390/educsci10020029

Martínez-Roget, Fidel, Pilar Freire Esparís, and Emilia Vázquez-Rozas. 2020. "University Student Satisfaction and Skill Acquisition: Evidence from the Undergraduate Dissertation" Education Sciences 10, no. 2: 29. https://doi.org/10.3390/educsci10020029

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Skill vs Degree: How to bridge the gap between skill supply and skill demand

We collect our degrees after years of school and college education but panic strikes when we find ourselves jobless why are so many of india's youth population unemployed we are facing a serious skill development crunch in the entire education process as the indian system focuses on an instructor-based approach and rote learning..

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There is an overpowering need for skilled workers in India. Though there are around 20 million youth added to the workforce every year, only a small percentage out of them actually manage to secure a job. This is because even though they possess a graduation degree, they do not possess the necessary skills required in the 21st century job industry to get employed.

India Today spoke to Shubika Bilkha, Business Head, Real Estate Management Institute about the factors what India needs to address right now in terms of creating the right workforce employable across various industries.

Q. Please elaborate on what factors universities should focus on in order to ensure that the gap between demand and supply in various industries can be closed.

Shubika Bilkha: Educational institutes in India train millions of students each year; however, the majority of Indian graduates across disciplines remain unemployed. For example, as per the Aspiring Minds National Employability Report, of the 1.5 lakh engineering graduates in 2015 from over 650 colleges, 80 per cent of them are unemployable. (Read: Only 7 per cent engineering graduates employable: What's wrong with India's engineers? ) There seems to be an inherent disconnect between the curriculum based learning at the school and university level, with the requisite 'job ready' skills needed by Indian corporates. Despite some initiatives taken by the government towards enhancing skill development, there still exists a large gap between supply and demand, with students expressing their frustration by way of limited job opportunities and corporates looking for quality talent.

In the real estate sector alone, there is a current skill shortfall of 4 million core professionals with the total skill requirement of the sector expected to be 75 million by 2022 (KPMG Report 2016). (Read: Property management and real estate: Skill requirement and scope in today's market )

There are a number of key avenues that need to be highlighted to address the issue outlined above:

To bridge the skill gap and create a value for vocational education, there needs to be a greater acceptance of vocational diplomas/certifications by employers.

Q. "Vocational training is a policy orphan because strategy is set by Delhi but delivery systems are in the hand of states." How can this problem be catered to?

Shubika Bilkha: There is an inherent gap between the number of graduates per year and the associated employment metrics. As discussed above, the majority of graduates are said to be unemployable. This is primarily because even though they have a graduation degree, a number of them do not have the required skills needed in today's ever-evolving job industry to get employed.

As vocational training is still in its infancy in India, a number of private institutes, who have the essential resources and expertise in the respective industry, have started training and building skills in-house.

Deen Dayal Upadhyay Grameen Kaushalya Yojana and Pradhan Mantri Kaushalya Vikas Yojana have been important initiatives to persuade the youth to acquire key job ready skills
At the university level, there has been the introduction of the BVoc programme to encourage students to develop employable skills

While these initiatives are a step in the right direction, they need to build a deeper alliance with the recruiting industry. The courses should not end in just mere certificates but should also translate into actual placements.

Need for private and government skilling forces to align

While private institutes have reacted faster to this growing requirement, there needs to be a simpler process by which the government frameworks, the university framework and the private institute align themselves towards sector development. (Read: Scaling skill development: Role of private sector )

We have established REMI- The Real Estate Management Institute with the vision to 'Skill India to Build India' and contribute to industry development of the real estate sector by bridging the skill gap and supplying trained professionals to one of the largest employment sectors in the economy.

Read: Evolution of blackboards: From clay tablets to the digital board

Read: Creating a performance environment: How Google and Apple get the best from employees

Read: Rules for a perfect resume in 2017

Employability and Employment: The Role of Higher Education in a Rapidly Changing World

First Online: 28 June 2022

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Leisa Hassock 9 &
Christopher Hill 10

Part of the book series: Knowledge Studies in Higher Education ((KSHE,volume 10))

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This chapter focuses on the Middle East but draws on case studies from Asia and Europe to examine the evolving role of higher education in supporting, promoting and even hindering employability. Through analysis of existing trends and values, this chapter explores the need for a clearer understanding of the relevance and position of higher education in developing skill-based graduates and the need to reflect on current and past practice in light of tomorrow’s challenges. There is a concern that higher education is approaching a crisis point and that massification of access, increased expectations on returns, and increasing levels of unemployment, are shifting the perspective of the role higher education can and should play. This chapter will also examine and discuss key issues in higher education and explore the importance placed on perspective, activity and results. The chapter provides evidence from a variety of sources in order to establish an understanding of patterns, trends and possible future strategies for interaction and development. The review focuses on the conflict between an outcome-based and a developmental approach in order to explore the extent to which higher education is responding to current issues and the extent to which it is placed to address future concerns.

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Higher Education and the World of Work: The Perennial Controversial Debate

The Future of Education, Employability, and Work in Asia-Pacific

Higher Education and the Employability Agenda

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Hassock, L., Hill, C. (2022). Employability and Employment: The Role of Higher Education in a Rapidly Changing World. In: Ng, B. (eds) Higher Education and Job Employability. Knowledge Studies in Higher Education, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-031-05716-8_8

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Research Article

Connecting higher education to workplace activities and earnings

Roles Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, PA, United States of America

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliations Argyros School of Business and Economics, Chapman University, Orange, CA, United States of America, Digital Economy Lab, Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, United States of America

Roles Data curation, Formal analysis, Methodology

Affiliation Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, United States of America

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, PA, United States of America, Digital Economy Lab, Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, United States of America, Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States of America

Hung Chau,
Sarah H. Bana,
Baptiste Bouvier,
Morgan R. Frank

Published: March 15, 2023
https://doi.org/10.1371/journal.pone.0282323
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Higher education is a source of skill acquisition for many middle- and high-skilled jobs. But what specific skills do universities impart on students to prepare them for desirable careers? In this study, we analyze a large novel corpora of over one million syllabi from over eight hundred bachelors’ granting US educational institutions to connect material taught in higher education to the detailed work activities in the US economy as reported by the US Department of Labor. First, we show how differences in taught skills both within and between college majors correspond to earnings differences of recent graduates. Further, we use the co-occurrence of taught skills across all of academia to predict the skills that will be taught in a major moving forward. Our unified information system connecting workplace skills to the skills taught during higher education can improve the workforce development of high-skilled workers, inform educational programs of future trends, and enable employers to quantify the skills of potential workers.

Citation: Chau H, Bana SH, Bouvier B, Frank MR (2023) Connecting higher education to workplace activities and earnings. PLoS ONE 18(3): e0282323. https://doi.org/10.1371/journal.pone.0282323

Editor: Simona Lorena Comi, University of Milano–Bicocca: Universita degli Studi di Milano-Bicocca, ITALY

Received: July 26, 2022; Accepted: February 14, 2023; Published: March 15, 2023

Copyright: © 2023 Chau et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: This research is supported in part by the University of Pittsburgh Pitt Momentum Fund and the Center for Research Computing. This work has been supported (in part) by # 2109-33808 from the Russell Sage Foundation. Any opinions expressed are those of the principal investigator(s) alone and should not be construed as representing the opinions of the Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

Education plays a critical role in economic growth and social progress. College degrees are generally associated with higher potential lifetime earnings, larger professional networks, and more adaptable careers [ 1 , 2 ]. Higher education is a major part of US workforce development but information on the skills and expertise taught during higher education remain absent—even as recent research highlights the critical role of skills in shaping labor trends [ 3 – 5 ]. However, most empirical work relies on coarse labor distinctions, such as college major and institutional information (e.g., school brands), to explain these occupational trends [ 6 – 9 ]. While useful, these coarse educational and labor categories may hide further insights into the skills of “high-skilled” workers that contribute to positive career outcomes [ 10 ].

Many workers acquire skills through higher education that shape their careers. Studies have shown that social-cognitive skills and sensory-physical skills are correlated to high- and low-wage occupations, respectively, and that skill polarization divides workers with and without higher education [ 11 ]. Discrepancies between skills demanded, taught, and researched have been identified by applying textual matching techniques to job advertisements, course syllabi, and research publications in Computer Science [ 12 ]. These analyses of skills reveal gaps between the workforce and educational/training systems. Understanding the sources of these gaps, across all fields of study, may improve curriculum design, inform educational policy, and improve student outcomes when they enter the workforce.

In this work, we analyze the recently-available Open Syllabus Project (OSP) dataset, which contains over 1.4 million course syllabi from more than 3,000 US colleges and universities from 2008 to 2017. While relatively new, this data source has proven useful for modeling higher education. For example, one study quantified the skill (mis-)alignment between academic research, industry, and educational offerings in data science and data engineering [ 12 ]. They used Burning Glass (BG) skill taxonomy and applied matching techniques to extract skills appearing in job titles and descriptions, course syllabi, and publication titles and abstracts. Another study proposed a new measure for the “education-innovation gap” using the textual similarity between course syllabi and academic journals to model the dissemination of frontier knowledge into college classrooms while relating these dynamics to students’ graduation rates and incomes [ 13 ].

Our work is the first attempt to connect workplace activities to higher education through course syllabi; here, we use the granular workplace activities designed and produced by the U.S. Department of Labor (i.e., O*NET Detailed Work Activity (DWA) taxonomy described in Section Materials) to explain the underlying knowledge structures across college majors ( i.e ., fields of study (FOS)) and among US universities. We use word embeddings to represent textual documents [ 14 , 15 ], and explore different distance metrics to measure the similarity of two embedded skill vectors. Consequently, we are able to apply agglomerative hierarchical clustering techniques to the DWA-based vector representations of FOS and universities to discover their clusters. Hierarchical clustering [ 16 ] produces a nested sequence of cluster, and the hierarchy of clusters enables us to explore clusters at any level of detail without the need of identifying a specific number of topics as would be the case with K-means clustering techniques. Motivated by the principle of relatedness [ 17 ], we model the relationships between pairs of skills across academia to forecast how skills change over time. Based on our out-of-sample earnings prediction evaluation with 5-fold cross validation , we also discover that differences in acquired skills help to explain the variance of graduates’ earnings. Our results offer an approach that connects college education to future careers. These insights may enable educational policy and academic programs to adapt to the skill dynamics in the labor market. For example, information systems that bridge between higher education and workforce skill data may inform updates to course design that prepare students with the necessary skills for their desired careers.

In summary, this paper attempts to answer these following research questions:

Q1. Can the granular workplace activities used by the Department of Labor to describe the US workforce also distinguish between different college majors and institutions?
Q2. How do the DWAs taught in a curriculum or field of study evolve over time? Can the relationships between pairs of skills across all of academia help to predict the skill evolution?
Q3. Do the differences in taught skills during higher education predict graduates’ earnings? Similarly, do differences in taught skills within college majors correspond to earnings differences of recent graduates?

In the next section, we describe multiple datasets that enable us to answer aforementioned research questions. We then describe our methodology in detail, present our analysis and discuss its implications and potential weaknesses to conclude the paper.

2 Materials

Open Syllabus Project Dataset ( https://opensyllabus.org (OSP)) is one of the largest corpora of syllabi in the world. As of October of 2019, it contains over eight million syllabi, collected from 5,381 colleges and universities, including over three million syllabi taught at 3,186 US institutions. OSP’s fields-of-study classifier draws heavily from the Classification of Instructional Programs (CIP) taxonomy used by the National Center for Education Statistics to determine the academic field of study ( e.g ., Economics, Business, Computer Science ) best associated with each syllabus. It includes 62 fields of study. Each syllabus has a unique identifier and the text assignment data including a description of its content, a list of references and recommended readings, and course requirements (such as assignments and exams). Syllabi can be directly mapped to graduation and enrollment statistics from the US Department of Education’s Integrated Postsecondary Education Data System (IPEDS). Syllabi are annotated with metadata including the institution, department, and academic year associated with the course. We extract and concatenate course titles, course descriptions and learning objectives from syllabi’s textual data to create “course descriptions.” More details can be found in SI Section 1 in S1 File . We limit the data from 2008 and 2017 (the ten most recent years in OSP), resulting in roughly 1.4 million syllabi representing college courses from 1,481 institutions. More about courses statistics per year and/or per field of study (FOS) can be found in S12 and S13 Figs in S1 File .

O*NET Detailed Work Activity (DWA) Taxonomy ( https://www.onetonline.org/help/online/dwa ). O*NET is designed and produced by the U.S. Department of Labor/Employment and Training Administration. The O*NET database allows snapshots of the relationships between occupations and skills. It has 2070 DWAs ( e.g ., “develop methods of social or economic research.” , “design integrated computer systems.” , “design public or employee health programs.” ) representing specific work activities performed across a small to moderate number of occupations within a job family. For example, the occupations with related activities to DWA “design public or employee health programs.” include “Preventive Medicine Physicians”, “Occupational Health and Safety Specialists”, “Occupational Health and Safety Technicians”, “Dietitians and Nutritionists”, and “Dentists, General”.

Integrated Postsecondary Education Data System ( https://nces.ed.gov/ipeds/ ) ( IPEDS ) is the core postsecondary education data collection program of the U.S. Department of Education’s National Center For Education Statistics (NCES). It annually collects information from all providers of postsecondary education, including public institutions, private nonprofit institutions, and private for-profit institutions, in fundamental areas such as enrollment, program completion and graduation rates. Providing data is required for any institution that applies for or participates in any Federal financial assistance program. IPEDS also includes a wide range of information about institution and institution groups, such as Degree-granting status, Institutional category, and Carnegie classifications. The Carnegie Classification, or more formally, the Carnegie Classification of Institutions of Higher Education ( https://carnegieclassifications.iu.edu/ ), is a framework for categorizing all accredited, degree-granting institutions in the United States. It is designed to group colleges and universities based on their research activities.

College Scorecard ( https://data.ed.gov/ ) is a U.S. Department of Education data initiative providing transparency and consumer information related to individual institutions of higher education and individual fields of study ( e.g ., majors) within those institutions. College Scorecard provides information about post-college earnings including median earnings of graduates working and not enrolled after completing highest credential in their first and second years for the two graduation cohorts of years 2016 and 2017. We only use the first year earnings of graduates. We process the data for Baccalaureate colleges and universities, and create the mapping between College Scorecard CIP code and OSP CIP code (the mapping can be found in this GitHub folder ( https://github.com/HungChau/OSP-connect-higher-education/tree/main/cip_code_mapping )). As a result, we obtain 9007 earnings records for 832 institutions in 54 fields-of-study.

3 Methods and results

3.1 modeling course syllabi with workplace skills.

Are the workplace activities tracked by the US Department of Labor robust and effective to describe the knowledge in higher education? The O*NET database is produced by the US Bureau of Labor Statistics and details the labor market trends of workplace skills and activities by occupation. Specifically, detailed work activities (DWAs) are elements in the O*NET database that provide information about occupations’ labor requirements. This data has been used to analyze several labor market dynamics including job polarization [ 11 , 18 ] and the economic resilience of cities [ 3 , 19 ]. Although O*NET relates occupations to skills in the workforce, similar data is not reported for educational programs even though many high-skilled workers obtain skills in college before entering the workforce.

We bridge this gap by detecting O*NET’s detailed work activities from syllabus course descriptions. Each syllabus in the OSP data contains a description of the course content, a list of references and recommended readings, and course requirements, such as assignments and exams. Given a syllabus, we extract the course’s title, description, and learning objectives from the text and concatenate them to form the course descriptions (details are in SI Section 1A in S1 File ). We apply word embeddings [ 20 ] and document similarity techniques from natural language processing to represent each DWA and syllabus as continuous vectors distributed in the same pre-trained language embedding space. Language embedding models enable us to describe the semantic similarity between two textual documents or sentences; here, we compare syllabus course descriptions to DWAs. We choose pre-trained fastText word embeddings from [ 21 ], which is constructed from all Wikipedia pages in 2017, the UMBC webbase corpus, and the statmt.org news data. We choose these word embeddings because the semantic diversity of Wikipedia and news articles should capture the semantic diversity of topics taught across FOS. This model has been used in several applications [ 22 – 24 ], and achieves better performance than simple bag-of-words and TF-IDF [ 15 ]. We compute the relationship (0 < = r s ( dwa )< = 1) between a syllabus s and a DWA by comparing their word embedding vector representations with soft cosine measure [ 25 ] (details are in SI Section 1B). As a result, syllabi are represented based on their relationships with the DWAs (called the DWA-based syllabus representation). We provide an example of the most and least prevalent DWAs detected for a political science syllabus at Harvard University in 2013 (see Fig 1A ).

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(A) An example political science syllabus from Harvard University and the activities that are most and least strongly associated with its course description. DWA-syllabus similarity scores range from 0 (not detected) to 1 (strongly detected). (B) The DWAs that most significantly distinguish Accounting syllabi from Medicine syllabi. (C) The DWAs that most strongly separate MIT syllabi from Harvard syllabi. (D) The DWAs that most strongly separate Special Focus 4-Year Medical Schools syllabi from Engineering Schools syllabi. More examples can be found in S1-S4 Figs in S1 File .

https://doi.org/10.1371/journal.pone.0282323.g001

In addition to course descriptions, syllabi are annotated with metadata about where and when the course was taught. Metadata includes the institution, department/major/FOS, and academic year. OSP’s field classifier is trained and tested on the IPEDS 2010 CIP taxonomy to determine the academic field ( i.e ., FOS) best associated with each syllabus. This enables us to calculate the relationship between each pair of DWAs based on the co-occurrence of dwa 1 and dwa 2 in any set of course syllabi S ; for example, the set of all syllabi within a given FOS, sim f ( dwa 1 , dwa 2 ) for f ∈ FOS , or across all of academia, sim ( dwa 1 , dwa 2 ). We experiment with various semantic distance metrics to compute DWA relationships through syllabi including Jaccard similarity, Cosine similarity, Euclidean distance, and Manhattan distance (see SI Section 2 in S1 File ). We find Jaccard similarity to be the most predictive and we present those results in the main text. It is worth noting that relationships between two DWAs can be directly computed by measuring the cosine similarity of their embedding vectors. However, this approach measuring a static relationship between DWAs fails to distinguish the dynamics of how one DWA relates to another locally (i.e., within a FOS or a university) and globally (i.e., across all of academia) overtime, which will be discussed in Section Predicting the change in taught skills. For example, social skills and computer programming skills may be semantically different but co-taught as complementary skills across syllabi (e.g., computational social science, social network analysis, or econometrics).

These tools enable us to compare pairs of syllabi, FOS, or universities based on their most common DWAs. We publish the DWA similarities by different metrics, DWA scores for each FOS and for each university by year from 2008 to 2017 in a Github repository ( https://github.com/HungChau/OSP-connect-higher-education ). Specifically, we compare entities of the same type ( e.g ., one FOS to another) by subtracting its DWA vector representation from the other’s and rank the resulting vector in descending order. We visualize the top 15 DWAs of each entity that contribute most to the difference of the pair in Fig 1B–1D . For example, the DWAs “refer patients to other healthcare practitioners or health resources” and “administer basic health care or medical treatments” most strongly distinguish Medicine from Accounting, while “analyze budgetary or accounting data” and “analyze business or financial data” identify Accounting from Medicine (see Fig 1B ). Similarly, we compare pairs of universities based on their taught DWAs. As an example, “design integrated computer systems” and “design alternative energy systems” most strongly distinguish Massachusetts Institute of Technology (MIT) from Harvard University, while “forecast economic, political, or social trends” and “develop financial or business plans” more strongly identify Harvard from MIT (see Fig 1C ). These results match our intuition as MIT is the world-leading engineering university and Harvard is in the top ten universities in each social science area according to U.S. News rankings. Building on this, we can group universities based on their Carnegie classification to identify the major differences in taught DWAs. We compare Medical Schools to Engineering Schools in Fig 1D . More examples can be found in S1-S4 Figs in S1 File .

3.2 Identifying Field-of-Study and university clusters

Do DWAs capture the focal knowledge offered by an academic field or a university? To further compare education among FOS, we use agglomerative hierarchical clustering on DWA-based vector representations of each FOS. Hierarchical clustering [ 16 ] produces a nested sequence of clusters like a tree (also called a dendrogram). Agglomerative clustering builds the dendrogram from the bottom level, and merges the most similar (or nearest) pair of clusters at each level to go one level up. Hierarchical clustering can take any form of distance or similarity function, and the hierarchy of clusters enables us to explore clusters at any level of detail without the need of picking a number of topics k as would be the case with K-means clustering. Pairs of FOS are similar if they are associated with similar types of work activities. For instance, Accounting is clustered together with Business and Marketing ; Medicine is clustered together with Nursing , Nutrition , Health Technician , Dentistry and Veterinary Medicine ; the STEM cluster includes Mathematics , Physics , Astronomy , Biology , Earth Sciences , Atmospheric Sciences and Chemistry ; and the Social Science cluster includes Social Work , Political Science , History , Sociology , Women Studies , Anthropology and Religion (see Fig 2 ).

The dendrogram and heatmap show similar FOS clustered together based on their DWA-vector representations.

https://doi.org/10.1371/journal.pone.0282323.g002

Similarly, we compare all US universities in our data set using agglomerative hierarchical clustering performed on the weighted DWA-based vector representation of each institution in Fig 3 . We see that similar universities are clustered together. For example, The University of Texas Medical Branch , The University of Texas Health Science Center , and Oregon Health and Science University are clustered together. Although our dataset contains a large number of universities, we select a subset of Ivy Plus universities and universities from various IPEDS Carnegie Classifications to visualize in Fig 3 . We filter out universities that have less than 100 syllabi or were missing syllabi in any year from 2008 to 2017. Carnegie classifications are mostly recovered by the clusters (see colors in Fig 3 ). Additionally, engineering schools like California Institute of Technology , Massachusetts Institute of Technology , and Carnegie Mellon University , are clustered together. Similarly, liberal arts schools including Cornell University , Harvard University , and University of Pennsylvania are clustered together.

The dendrogram and heatmap reveals the hierarchical clustering of the Ivy Plus group and Special Focus Four-Year groups from the Carnegie Classification 2018 based on DWA vector representations.

https://doi.org/10.1371/journal.pone.0282323.g003

3.3 Predicting the change in taught skills

How do the DWAs taught in a field of study evolve over time? In particular, which new skills or topics will emerge in a field’s syllabi? Forecasting these educational trends enables proactive course design by educators and could inform educational incentives from policy makers. Here, we use the principle of relatedness [ 17 ] to hypothesize that DWAs that occur together across all of higher education are more likely to be co-taught within a given FOS in the future. If correct, then modeling the relationships between pairs of DWAs across all of academia should forecast the introduction of new topics within a FOS even if that topic has not been part of that FOS historically. As an illustrative example, although largely absent from Economics syllabi today, machine learning may become more common in Economics because Economics already teaches linear regression which is commonly taught as an example of machine learning in Computer Science courses. As a more specific example from our data, DWAs that relate to machine learning, such as “analyze website or related online data to track trends or usage” may become more prevalent in Economics syllabi moving forward (e.g., in studies of online job postings [ 12 , 26 ]).

As robustness checks, we run Models 2, 3, 4 & 5 with the two different methods and four distance metrics aforementioned in Section Modeling course syllabi with workplace skills for computing the DWA relationships. Although we could compare DWA pairs based solely on their semantic similarity using their word embedding vectors, this approach would miss DWA pairs that capture complementary topics. For example, Models 2 and 3 would be identical to Models 4 and 5, respectively. The results (see SI Section 3A in S1 File ) show that modeling DWA relationships based on their co-occurrence in syllabi with Jaccard similarity yields the best performances across all the models involving inter-DWA relationships. We discuss these results in the main text.

We compare model performance using root mean squared error (RMSE) with 5-fold cross validation in Fig 4 (R-squared metric is reported in S11A Fig in S1 File ). First, including variables representing DWA relationships decreases RMSE ( i.e ., Model 2 ( R 2 = 0.231) & Model 3 ( R 2 = 0.239) are statistically significantly better than Model 1 ( R 2 = 0.191)). Second, measuring DWA co-occurrences across all of academia (i.e., using R ) instead of only within a single FOS (i.e., using R f ) improves model predictions. Specifically, Model 3 ( R 2 = 0.239) outperforms Model 2 ( R 2 = 0.231) and Model 5 ( R 2 = 0.244) outperforms Model 4 ( R 2 = 0.231).

We perform 5-fold cross validation and repeat 40 times (i.e., 200 trials in total) for each model and measure RMSE by the resulting model applied to the test set. Asterisks indicate the statistically significant difference between two models’ performances with Bonferroni correction. Predicting the importance of DWAs changing in nine years (2008 vs. 2017). As a baseline, model 1 only considers the current DWA score and FOS fixed effects. The other models consider the relationships between DWAs, how they interact with each other to predict how they may change in future.

https://doi.org/10.1371/journal.pone.0282323.g004

These results suggest that FOS educational trends within a FOS correspond to global educational trends across all of academia. In particular, this evidence supports our hypothesis that DWAs tend to be co-taught more within a given FOS if they are bundled together across all of higher education. ( e.g ., Computer Science may increasingly teach “analyze green technology design requirements” since it is commonly taught with “identify information technology project resource requirements” in other FOS including Engineering). Although Model 4 does not outperform Model 2, including the interactions between current DWA relevance scores and the average of the proximity of global DWA relationships does yield a significant improvement ( i.e. , Model 5 outperforms Model 3). In conclusion, the best performing model is Model 5 which leverages the information about the current score of the DWA, their relationships with other DWAs across academia, and the interaction of these two variables. Model 5 improves 3.3 percent (27.5 percent) in terms of RMSE (R-squared) over Model 1, which only uses the 2008 DWA relevance scores. Therefore, we train Model 5 using the entire data, and use it to predict the relevance scores of DWAs in a FOS nine years later. Table 1 shows some examples of DWAs that became important within a FOS —in terms of ranking DWAs—in nine years. The full list of DWAs that are predicted to increase their ranks by at least five units and ranked in the top 50 in 9 years can be found in the aforementioned Github repository.

We only select DWAs that are ranked in top 50 in future. The full list of predicted DWAs can be found in the same Github folder.

https://doi.org/10.1371/journal.pone.0282323.t001

3.4 Predicting graduate earnings

Do detected DWAs predict the variation in graduates’ earnings? Most—if not all—educational programs aim to provide students with the skills and abilities to successfully enter the workforce ( e.g. , to gain employment and maximize earnings). Most empirical work relies on coarse labor distinctions such as college major and institutional information (e.g., school brands) to correlate to graduate earnings [ 7 , 9 , 27 , 28 ], but none have provided insights into the skills students learn that could contribute to their future earnings. Our analysis of DWAs in university course syllabi provides the first data set connecting taught skills to students’ earnings after graduation. We collect earnings of graduates from the College Scorecard earnings data from the U.S. Department of Education. Though large, the OSP course syllabus data is not distributed evenly across fields-of-study and institutions. Some fields and institutions have much less course syllabi. Thus, to sufficiently estimate work activities taught in a FOS at a university, we limit earnings records for FOS (in an institute) that have at least 10 course syllabi; and perform Kolmogorov-Smirnov statistical test to make sure the remaining earnings records representative for the entire population of the field at the institute (more details on the selection process and criteria are in SI Section 4 in S1 File ). We build several OLS regression models to predict average graduate earnings across FOS ( f ) at a university ( u ) based on the relevance scores of the DWAs across fields ( DWA ) and within field ( FOS*DWA ), FOS fixed effects ( FOS ), school brands (i.e., school ranks (Historical U.S. News and World report rankings are compiled by Andy Reiter and available at https://andyreiter.com/datasets/ ) if available) fixed effects (RANK), and geography fix effects ( GEO ). Due to the limited availability of earnings data, we use groups of 10 ranks (i.e., 1–10, 10–20) for national universities and 15 ranks (i.e., 1–15, 15–30) for liberal arts colleges. For geographical features, we group universities together based on their divisions (U.S. Geographic Levels are available at https://www.census.gov/programs-surveys/economic-census/guidance-geographies/levels.html ) (e.g., New England Division, West North Central Division). These groups are represented using indicator variables in the regression analyses.

To avoid model over-fitting, we perform 5-fold cross validation and LASSO feature selection on the models that include DWA features. LASSO [ 29 ] is one of the most popular methods for feature selection; it minimizes the residual sum of squares subject to the sum of the absolute value of coefficients being less than a constant. This constraint tends to “regularize” large models by producing some 0 coefficients when variables are co-linear. In other words, the penalty factor determines how many features are retained; using cross-validation to choose the penalty factor helps assure that the model will generalize well to future data samples. As a result, we find that DWAs improve predictions of graduate incomes (see Fig 5 for RMSE metric and S11B Fig in S1 File for R-squared metric according to 5-fold cross validation). Including DWAs improves predictions of earnings compared to FOS fixed effects ( i.e. , smaller RMSE). Also, R 2 = 0.684 of the DWA model is significantly better than that of FOS model R 2 = 0.677). Controlling for university rankings and geography further improves the FOS model (i.e., FOS+RANK+GEO ( R 2 = 0.757) model is significantly better than FOS ( R 2 = 0.677) model). But combining DWA variables with RANK and GEO variables and FOS fixed effects yields even further improvement ( FOS+RANK+GEO+DWA model ( R 2 = 0.761) is statistically significantly better than that of FOS+RANK+GEO model). This evidence suggests that some of the information about graduate earnings represented in university rankings is also encoded the DWA variables (e.g., a LASSO regression model containing DWA variables accounts for 48% of the variation in college rankings; year and FOS fixed effects account for 7.9%). Finally, the best model ( FOS+RANK+FOS*DWA ) is found when we allow DWA variables to interact with FOS fixed effects which suggests that different DWAs correspond to earnings variation in different FOS ( R 2 = 0.779). The geographic variables also help to improve the best model’s performance but not significant ( R 2 = 0.782).

https://doi.org/10.1371/journal.pone.0282323.g005

3.5 Within Field-of-Study skill variation and the earnings of recent college graduates

Do differences in taught skills within college majors correspond to earnings differences of recent graduates? To study how DWAs relate to earnings of graduates of a specific field of study, we perform separate regression analyses for each FOS with at least 100 institution-year observations. We employ LASSO feature selection for DWAs and report model performance using 40 independent trials of 5-fold cross-validation to mitigate over-fitting. The remaining DWAs are used to predict earnings. As can be seen from Fig 6 , the DWA+GEO models perform significantly better than the baseline GEO models in terms of RMSE. Due to the limited earnings data within FOS to perform cross validation, the school ranking is omitted; the baseline models only include geographic variables ( GEO ). We obtain similar performance when alternatively using the model variance explained ( R 2 ) (see S11C Fig in S1 File ). This result again shows that the DWAs complement the FOS information by increasing the share of the earnings explained by the model and improving the model’s predictions. However, DWA+GEO model performance varies across FOS. For example, the DWA+GEO model improves 27.2% RMSE over the GEO model for Business compared to a more modest improvement of 4.2% for Psychology . Although O*NET DWAs improve predictions in general, this varied performance across FOS could be because DWAs represent key skills and activities better in some FOS than in others. Nevertheless, our methodology shows that using granular workplace skills helps to identify important features contributing to earnings of graduates beyond course educational and labor categories.

We perform 5-fold cross validation and repeat 40 times (i.e., 200 trials in total) for each model and measure RMSE by the resulting model applied to the test set. The baseline GEO model only includes geographic variables. The performances of the DWA+GEO models are statistically significantly better than the GEO models with the p-values < 0.05 for all of the reported FOS (the school ranking is omitted due to the limited earnings data).

https://doi.org/10.1371/journal.pone.0282323.g006

Identifying DWAs that correspond to increased earnings after graduation could inform students’ course selection based on the demand for skills in the labor market. To demonstrate this, we analyze the regression of FOS Business as an example. After performing 5-fold cross validation on the model determined by LASSO feature selection, there are 57 DWAs remaining. Based on our statistical regression analysis, the 57 DWA features are able to explain 69.2% of the variance of the earnings in Business . Among those, 10 DWAs have significant coefficients with the p-values below 0.05. DWAs “ complete documentation required by programs or regulations ,” “ evalutate program effectiveness ,” and “ advise others on career or personal development ” are positively associated with earnings while “ conduct health or safety training programs ” is negatively associated with earnings (regression coefficients estimated with p value < 0.01 in each case). The list of DWAs have significant coefficients for all the 10 FOS can be found in S2 Table in S1 File . The full list of all the selected DWAs including the coefficients and statistics can be found in this GitHub folder ( https://github.com/HungChau/OSP-connect-higher-education/tree/main/selected_DWAs ).

4 Discussion

Knowledge, skills, and abilities shape workers’ careers, and so, quantifying their sources may impact workforce development and our understanding of the labor market. Largely, higher education is a source of skill acquisition for many middle and high-skilled jobs in America. However, there is a disconnect between work and learning in the US; higher education can fail to meet the skill demands of the labor market thus creating “skill gaps” across the country. A labor market information system where work skills are shared across entities, connecting education to work, could help students know what skills they need, educators know what skills to instruct for, employers know what skills workers have, and policy makers more effectively impact workforce development. This study demonstrates a methodology to bridge material taught in U.S. colleges and universities with the detailed work activities (DWAs) used by the Department of Labor to describe the US workforce. This creates new opportunities to track changes in the evolution of higher education and workforce development; for example, the emergence of DWAs within the syllabi of a field of study (FOS), or major, corresponds to the co-occurrence of DWA pairs across all of academia (see Fig 4 ). As an illustrative example, discussions of green technology design requirements may become more prominent in Computer Science programs because they go hand-in-hand with information technology project resource requirements, commonly taught in courses across academia. Educators, educational policy, and course recommendation systems could use these insights to design educational programs and to advise students towards the classes offering the experience that will be most valuable for their career goals. Following our example, proactive curriculum design might include green technology topics to prepare students for jobs in Computer Science.

However, it is likely not the case that every FOS will teach every skill or ability, in part, because labor market incentives for specific DWAs vary by industry, region, and employer. Thus, insights into the course topics that correspond to increased, or decreased, earnings after graduation (see Fig 6 for example) may increase the relevance of an educational program or policy and increase students’ success when they enter the workforce. For example, academic programs might grow to include new high-demand skills while decreasing emphasis on outdated topics. Such insights could inform goal -based learning [ 30 ] in course recommendation systems while improving explanations of recommendations. Increasingly-personalized course recommendations can identify relevant topics based on students’ predefined goals ( e.g. , maximizing job earnings). For example, recommending Business courses that include “ complete documentation required by programs or regulations ” work activities might proactively prepare today’s students to meet the growing demand for Business Analytics in the labor market.

4.1 This study has a few limitations

This study demonstrates how novel syllabus data and natural language processing (NLP) techniques can connect labor market data to higher education by predicting the change in taught skills within a FOS and linking DWAs to graduate earnings. Future work might build on our study by analyzing the causal implications of skill-level adjustments to course content. In particular, our study’s approach is unable to address selection bias when students choose a university in which to enroll. But future work may study natural experiments that overcome this barrier. Potential examples include the hiring, firing, or retirement of new faculty, the creation of a new school or department, the emergence of a large employer ( e.g. , resulting from new tax credit), or large donations focused on specific learning outcomes. For example, future work might augment our analysis of graduate’s recent earnings with other career outcome measures. Our analysis of the College Scorecard earnings data is limited to only two graduation cohorts and similar Post-Secondary Employment Outcomes data is limited to only a few institutions. Furthermore, we only consider earnings one year after graduation, which may not capture the full career trajectory [ 31 ]. However, future analysis involving workers’ resumes will enable direct connections between workers’ educational foundations during college and their career dynamics ( e.g. , worker adaptability, tenure, and mobility) in addition to earnings. Similarly, job postings analysis might compare employer demands to the DWAs detected in our study thus identifying the most or least adaptive educational programs ( e.g. , [ 12 ]). Future research along this dimension will offer new insights into the sources and sinks of the high-skilled workers that shape job polarization [ 11 ] and urbanization today [ 4 , 19 ].

We have demonstrated, using mean cohort level graduate earnings, that there is already detectable variation in earnings based on skills taught in courses offered. Our approach has focused on outcomes for groups of graduates (e.g., by major or university). Future work with alternative data might investigate variations in labor market outcomes for individuals. For example, students studying the same major could take different courses offered, thus learning different skills. Whether the course selection by individual students leads to different occupations and different earnings, and how much learned skills could explain individual career variation are interesting questions left to be discovered. One challenge in undertaking such research is the availability and accessibility of this type of datasets at scale due to privacy concerns. Further, our analyses focused on students with bachelor’s degrees, but future work might study the skills of graduate education or the undergraduate education that lead to graduate school admission.

Our study relied on simple off-the-shelf techniques in combination with novel data sources, but future work might expand our methods with more sophisticated approaches. For example, this study used pre-trained static word embeddings and standard document similarity techniques to detect work activities from syllabi, but more complex NLP techniques could yield further insights. Static word embeddings are a powerful tool for capturing syntactic and semantic regularities in language, but each word is represented by a single vector regardless of context. That is, all senses of a polysemous word have to share the same representation. Contextualized word representations, such as Transformer-based embeddings, overcome those issues and have yielded significant improvements on many NLP tasks. Additionally, our study relies on the O*NET taxonomy used by US Department of Labor to describe labor market trends. These granular DWAs reveal core differences between courses, fields and universities. For example, DWA relevance scores improved predictions of graduate earnings within many fields of study, but not all. This suggests that “skill” differences may impact the effectiveness of college education (in terms of earnings) but O*NET DWAs may not be the most precise taxonomy to describe the granular level of knowledge expressed in courses. This is in part because O*NET data is not designed to describe higher education, but to describe workers. There is no standard knowledge base describing more granular concepts and skills in higher education and the labor market. This highlights an urgent need for future educational research that builds a knowledge base that could standardize and advance insights into how educational foundations shape workforce development and the skills of workers. With the advances of text mining methods, one could extract skills described in course syllabi and job postings, and align those skills to connect educational contents with the demands of the labor market. There are some existing job skill taxonomies to describe job postings’ requirements such as BG’s or LinkedIn’s proprietary skill taxonomies. Börner et al. (2018) analyze course syllabi and BG’s job postings focusing on areas of Data Science and Data Engineering. They use BG’s skill taxonomy instead of the one used by the U.S. Bureau of Labor Statistics to analyze skill discrepancies between research, education and jobs. Modeling job postings with NLP techniques has also been shown to be useful in understanding wage premia [ 32 ]. Although our study focuses on the work side of job seeking, we acknowledge that the demand from the employer side is also important to understand the holistic picture from skill offerings in higher education to skill demands in the labor market; which could benefit many applications such as identifying potential curricular gaps or recommending courses to meet jobs’ requirements.

Increasingly, researchers and policy makers use workers’ skills and abilities to describe labor market outcomes in addition to workers’ educational attainment based on their occupation [ 5 ]. But, similar data and methods are only just being developed and applied to workforce development and, in particular, to higher education. This study offers an approach and a methodology to connect higher education to workplace skills thus enabling new strategies for course recommendation, curriculum design, and education policy that prepare students to meet their career goals.

Supporting information

https://doi.org/10.1371/journal.pone.0282323.s001

Acknowledgments

We thank Erik Brynjolfsson, Seth Benzell, Daniel Rock, Nabeel Gillani, and Peter Brusilovsky for their feedback throughout this project.

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Front Psychol

Basic Skills in Higher Education: An Analysis of Attributed Importance

Lourdes aranda.

1 Department of Research Methods and Diagnosis in Education, University of Málaga, Málaga, Spain

Esther Mena-Rodríguez

Laura rubio.

2 Department of Developmental and Educational Psychology, University of Granada, Granada, Spain

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Introduction

Materials and Methods

Participants.

Distribution of students by bachelor degree.

Degree		Percentage
Pedagogy	133	19.2%
Early childhood education	183	26.3%
Primary education	279	40.2%
Psychology	99	14.3%
Total	694	100%

Instruments

Distribution of students by universities and degrees.

University	Degree
University of Málaga	Pedagogy	133
	Early childhood education	183
	Primary education	54
	Psychology	55
University of Granada	Primary education	117
	Psychology	44
University of Sevilla	Primary education	108
Total		694

Data Analysis

An external file that holds a picture, illustration, etc.
Object name is fpsyg-13-752248-g001.jpg

Mean scores of basics skills.

One-way Analysis of Variance (ANOVA).

Basic skill	Degree	(SD)			η
OP	Pedagogy	3.59 (0.45)	17.186	0.000	0.070
	Early childhood education	3.84 (0.21)
	Primary education	3.61 (0.40)
	Psychology	3.65 (0.37)
AF	Pedagogy	3.28 (0.46)	12.650	0.000	0.052
	Early childhood education	3.32 (0.42)
	Primary education	3.07 (0.50)
	Psychology	3.25 (0.51)
AT	Pedagogy	3.49 (0.41)	10.105	0.000	0.042
	Early childhood education	3.58 (0.32)
	Primary education	3.37 (0.40)
	Psychology	3.44 (0.45)
TE	Pedagogy	3.54 (0.38)	9.334	0.000	0.039
	Early childhood education	3.64 (0.28)
	Primary education	3.47 (0.35)
	Psychology	3.49 (0.41)
RP	Pedagogy	3.59 (0.40)	16.251	0.000	0.066
	Early childhood education	3.77 (0.24)
	Primary education	3.56 (0.35)
	Psychology	3.54 (0.39)

OP: capacity for organization and planning; AF: access to information sources; AT: analysis and synthesis of texts, situations, and people; TE: teamwork; RP: problem solving.

To determine the differences between groups, the Tukey post-hoc contrast test was performed. The mean scores for each dimension by bachelor degree are shown in Table 3 .

Data Availability Statement

Author contributions.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

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COMMENTS

Skill Acquisition vs. Higher Education? Why This Is A False ...
Skills-Based Technical Education. Benefits. Drawbacks. Lower cost of tuition. Focuses on professional and vocational skills that today's employers value. Apprenticeships and certificates often lead directly to employment in a chosen field. Lacks opportunities for student development outside of specific skill-sets and programs.
Higher Education Vs Skill Acquisition [1 min read]
Education News | Jan-22-2022. facebook. This debate on between higher education Vs. skills acquisition has become more relevant today given the emerging and dynamic employment landscape. Following the rising concern in the acquisition of specialized knowledge and skills in the job market, students are faced with a decision hingeing the choice ...
The Evolutionary Dilemma: Higher Education vs. Skill Acquisition
While higher education emphasizes academic knowledge and critical thinking, skill acquisition prioritizes practical proficiency and vocational expertise. This essay explores the nuances of this dilemma, examining their impacts on individuals, economies, and the future of education. Higher education, often synonymous with universities and ...
Why Skills Training Can't Replace Higher Education
Why Skills Training Can't Replace Higher Education. Summary. 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 ...
Higher Ed vs. Skill Acquisition
Firstly, higher education typically involves attending a college or university to earn a degree. This formal process of education is structured and often takes several years to complete. On the other hand, skill acquisition can be acquired through informal means such as on-the-job training or self-study.
Higher Education vs. Skill Acquisition: Navigating the Crossroads of
The traditional path of higher education, while still holding significant value, now faces competition from a burgeoning ecosystem of skill acquisition programs. Both approaches have their merits and drawbacks, and the optimal choice hinges on a nuanced understanding of personal aspirations, industry demands, and financial considerations.
CGPSC 2024 Mains, Paper II, Essay: Higher Education Vs Skill
CGPSC 2024 Mains, Paper II, Essay: Higher Education Vs Skill Acquisition. Higher Education Vs Skill Acquisition. In an era where the landscape of the professional world is rapidly evolving, the debate between the pursuit of higher education and skill acquisition has become increasingly relevant. This essay aims to explore the nuances of both ...
PDF Skill-based Education Shifting the Focus of Higher Education
Higher education Institutions can tap into the current context to better serve workers'. desire to be challenged to learn new skills and employers' need to hire more skillful workers. Shifting to a skill-based curriculum can enhance the usefulness of the degrees awarded by higher. education institutions.
PDF Understanding the Purpose of Higher Education: an Analysis of The
The ultimate goal is to develop renovation or repurposing strategy across competing imperatives and to outline success measures to critically define, measure, and evaluate the achievement of specific goals and outcomes in hopes of resolving potential skills mismatch in a world of massive cataclysmic change.
PDF Contributors to Undergraduates Perception of Skill Acquisition ...
in perceived skill acquisition was observed from first to fifth semesters. This result is in accordance with studies indicating that skill acqu. sition improves with years spent at the university (McInnis et al., 2001). However, in previous studies (see McInnis et al., 2001) the assessment of perceived sk.
Skills vs College Degrees: Key element reinventing the future of work
According to the facts, around 3.7 Cr students are enrolled in higher education (Source: 2019 Aishe.nic.in report) across multiple degrees and colleges. Although the number of jobs rolled out and ...
Beyond educational attainment: The importance of skills and lifelong
Similarly, the evidence relating trust and skills supports the fact that higher levels of skills are correlated with greater trust, which is conditional on education. Volunteering, usually defined as any planned and non-obligatory activity in which time is given freely to benefit private individuals or the general public (Wilson, 2000 ), is ...
Learning in higher education: towards knowledge, skills and competency
Nonetheless, the discussion and results obtained make insights to any future-related studies.,As pointed out in the previous sections, learning will be conceptualized in the form of knowledge, skills and competency acquisition. In a school setting, knowledge, skills and competencies are better captured by the grade attained in each subject.
Basic Skills in Higher Education: An Analysis of Attributed Importance
Basic Skills in Higher Education: An Analysis of Attributed Importance. Today, the skills-based approach is increasingly in demand by companies due, in large part, to the fact that it favors the management of human resources by focusing on individual capabilities; which, finally, improves the job profile of a company.
PDF Skill Development in Higher Education: Challenges and Opportunities
In the coming two decades, labor force of industrialized nations is forecast to decline by four percent. In sharp. Retrieval Number: D0184063418. contrast, India will witness a boom of some 32 percent during this time span. Skill India aims at tapping this vast potential of indigenous manpower.
University Student Satisfaction and Skill Acquisition: Evidence from
One of the main objectives of the Undergraduate Dissertation is to evaluate the skills associated with a degree. Student satisfaction with the training and skills acquired can be an indicator of the quality of higher education. This paper aims to analyse student satisfaction with Undergraduate Dissertation at the Faculty of Economics of the University of Santiago de Compostela (Spain). Based ...
Skill vs Degree: How to bridge the gap between skill supply and skill
In India today, vocational skilling exists outside of the realm of the university framework, with a number of corporates outlining graduate degrees as a key requirement. While there are university initiatives such as the BVoc scheme, most of these again exist within the degree framework as opposed to the vocational framework.
Employability and Employment: The Role of Higher Education ...
Whereas Knight and Yorke in their USEM model (Understanding, Skills, Efficacy and Metacognition) of employability focused on the graduate displaying subject understanding, as well as workplace skills and personal skills.In contrast, Guilbert et al. concentrated on employability from the perspective of accessing a suitable job, remaining employed in a social, economic, cultural and ...
Connecting higher education to workplace activities and earnings
Higher education is a source of skill acquisition for many middle- and high-skilled jobs. But what specific skills do universities impart on students to prepare them for desirable careers? In this study, we analyze a large novel corpora of over one million syllabi from over eight hundred bachelors' granting US educational institutions to connect material taught in higher education to the ...
Skill Development Through Higher Education
Several case studies have thus been conducted to link higher education provision, skills development, and graduate employability in both developed and developing nations (Jackson, 2015;Chan & Lin ...
Higher education versus skill acquisition essay
Unformatted Attachment Preview. Higher Education versus skill acquisition Reed 1mints Only. Competitiveness skills against qualifications (higher education) occur anywhere in the world. Most people in our country have a college education but that does not benefit them due to lack of skills. In that capacity, they work in a number of different ...
PDF European Higher Education Graduates Formation, Acquisition, and
Call for papers: Special Issue on 'European Higher Education Graduates - Formation, Acquisition, and Suitability of Skills' in Research in Comparative and International Education Guest editor: Katarina Wessling Digitisation and technological change is fundamentally transforming the world of work.
Basic Skills in Higher Education: An Analysis of Attributed Importance
Mean scores of basics skills. Regarding gender, significant differences were observed between men and women in the importance given to Capacity for organization and planning ( t(687) = −3.675, p < 0.001, d = 0.374) and Problem solving ( t(687) = −3.476, p = 0.001, d = 0.354). In both cases, women scored higher than men in the importance ...

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