Expanded yet restricted: a mini review of the soft skills literature.

\r\nAnna K. Touloumakos,*

  • 1 Department of Education, Centre on Skills, Knowledge and Organisational Performance, University of Oxford, Oxford, United Kingdom
  • 2 Department of Psychology, Panteion University of Social and Political Sciences, Athens, Greece

There has been a progressively heightened preoccupation with soft skills among education stakeholders such as policymakers, educational psychologists, and researchers. Soft skill curricula have been considered these days and developed not only for graduates and as on-the-job training programs but also for students across all levels of education. However, different people mean different things when referring to soft skills. This review presents evidence to suggest that the use of the term “soft skills” has expanded to encompass a variety of qualities, traits, values, and attributes, as well as rather distinct constructs such as emotional labor and lookism. It is argued here that these infinite categories of things can be skills because soft skills research is primarily focused on what are the needs and requirements in the world of work. This approach is problematic because it assigns characteristics to soft skills, which in turn affect the design of the soft skills curricula. For example, soft skills are often construed as decontextualized behaviors, which can be acquired and transferred unproblematically. The paper proposes that an in-depth and embedded approach to studying soft skills should be pursued to reach a consensus on what they are and how to develop them because otherwise they will always be expanded before restricted (as they have become ambiguous) in their meaning and definition.


Suppose you are present in a communication encounter between two men, Joe and Martin. Joe looks upset and literally screams while recounting an incident that has happened to him:

“Can you believe this?,” , Joe starts, “CAN YOU BELIEVE HIM? THE NERVE (.) he actually ended up ordering me “shut up, already, and do as I say!” (sounds infuriated) Joe is breathing heavily.

Martin nods thoughtfully.

(0.7) “As if he was in charge of me (.) as if he owned me … Where does he come off telling me what to do? Who does he think he is?” Joe continues.

Martin nods again, pushing his glasses up the bridge of his nose.

(0.9) Joe seems lost in his thoughts.

“I still can’t believe that this happened to me (.) It still makes me furious … ”

Martin’s nodding continues.

< “Can you understand now why I acted the way I did?” Joe asks. “I was badly provoked = = What would you do if you were me?” >

Martin responds with a nod.

Throughout Joe’s outburst, Martin keeps nodding. Nodding, in this instance, is an expressed form of active listening ( Pasupathi et al., 1999 ; Browning and Waite, 2010 ). The behavior of listening as a unified whole, moreover, features most prevalently in the lists of communication skills encountered in the soft skills literature – educational, medical, management, policy, or other (see for example, Jain and Anjuman, 2013 ). However, is Martin’s behavior a communication skill as these lists inform us? Let us consider two alternative scenarios providing context for this exchange, which, hopefully, can help us decide.

In the first scenario, Martin is a clinical psychologist, and Joe is his client. Martin has been treating Joe for the past 2 years; he is, therefore, aware that Joe suffers from bipolar disorder and that, as part of this, he experiences, periodically, manic episodes, like the one he recounts in the aforementioned exchange taking place in a supermarket between him and a stranger. In this communication encounter, Martin’s nodding and listening are the expressive form of his active processing of the contents of this narrative. It can be argued that it realizes Martin’s relation to Joe (i.e., he is Joe’s therapist) and his intention to encourage him to let it out and that it is enacting Martin’s knowledge of Joe’s condition, the relevant symptoms, and the techniques to deal effectively with it. In line with this, it seems fair to suggest that Martin’s listening behavior is an effective communication strategy and that it can, therefore, be construed as a “communication skill.”

In the second scenario, Joe has just started working as an employee in his uncle’s business. He works along with other seven employees under a team leader (Jacob). The team reports to Martin, the line manager. Joe is difficult to work with and has been constantly reporting problems to Martin with either his team leader or other team members. In the above excerpt, he recounts a recent episode between him and his team leader, Jacob, when the former refuses to follow the agreed strategy during a negotiation meeting. The encounter between Joe and Martin is one of many within the past few weeks. In this instance, and contrary to what one might have expected from a line manager, Martin’s behavior toward Joe fails to articulate the sensible aim of reasoning with Joe and taking actions to ensure such fights come to an end. Martin’s behavior, therefore, seems to be guided by something different; a possible explanation could be that he fears his behavior might displease the boss, so he remains silent instead. If that is the case, could still the behavior of listening be construed as a “communication skill” within the context of this scenario?

These episodes aim to illustrate how meaningless it is to call listening – as a random sample of any of the behaviors commonly featured in the different soft skills lists – a communication skill, before having access to all contextual information that would allow making an informed judgment. However, as the review of the literature that follows highlights this is the norm conceptualization of soft skills: any behavior mobilized in a communication encounter can be taken out of context and find its place to a list of communication skills without any formal and scientific criterion for doing so. The review starts first with the norm approach in the conceptualization and use of the term “skill” – itself.

Sources and Search Strategy

The literature review for this mini-review article was undertaken at two separate points in time: in the first instance looking at the literature up to and including 2011 and later for years 2011–2020. During the first period (up to 2011), a review of the term soft skills formed part of the literature review undertaken as part of a doctorate thesis ( Touloumakos, 2011 ). During this period, (a) keyword searches using the term “soft skills” (but also “soft skills” AND “characteristics,” “soft skills” AND “nature,” “soft skills” AND “development”) were conducted through the scientific databases: Google Scholar, Web of Science, and Scopus; (b) specific journals focusing on education, management, and the labor market were targeted and searched to meet the criteria of the doctoral research that looked at the difference between soft skills conceptualization in practice and in educational policy.

During this second period, the previous steps were reiterated to produce an up-to-date list of papers in which the term was used and defined. The author acknowledges that this article does not follow the methodology of a systematic review and that there is certainly scope for a thorough and systematic review on this topic in the future.

What Do We Mean by Skill?

The first known use of the term “skill” dates back in the 13th century (Merriam-Webster’s, 2019). Skill is considered as the “dexterity or coordination…in the execution of tasks” (typically of physical nature), as the “ability to use one’s knowledge effectively and readily in execution and performance,” and as “learned power of doing something competently.” The practical disposition of skill is acknowledged in these definitions. It is also highlighted in the work of Ryle (1949) and Polanyi (1962) , according to who skill is construed as what knowledge sets in action (know-how and know-that, respectively), and, therefore, the two (knowledge and skill) are seen as “reciprocally constitutive” ( Orlikowski, 2002 ). For the purposes of this paper, I adopt the view of skill as what knowledge sets in action (know-how).

The Expansion of Skills: The Emergence of the Soft Skills Category

Contributing factors in the expansion of the term skill.

Over the years, the term skill has expanded considerably, to the point that its meaning became vague. In recent discourse, especially, it has taken on a range of meanings, and as a result, it refers, frequently, to “what is not skill” ( Hart, 1978 ). Indicatively, the term often refers to attitudes, traits, volitions, and predispositions ( inter alia , Payne, 2004 ; Clarke and Winch, 2006 ) and is sometimes confused, and even interchangeably used, with terms such as expertise and competence ( Payne, 2000 ; Pring, 2004 ; Eraut and Hirsch, 2007 ). Its gradual expansion has meant (and is reflected in) the emergence of new skills categories and subcategories (indicatively: generic, soft, interpersonal, etc.). Key contributing factors toward such gradual expansion of the term skill are identified at three levels. The first is at the rhetorical level; the second is at the definitional level; and the third level is at the dispositional character of term itself within different scientific fields.

Focusing on the rhetorical level, in recent years, there has been a linguistic transition from terms such as “skilled work” and “skilled labor” to “skills.” Payne’s paper highlights this shift:

Whereas the Carr Report of 1958 (HMSO 1958: 10), for example, could still talk of “ skilled craftsmen ” [my emphasis] as being the “backbone of industry,” 40 years on, The Learning Age (Department for Education and Employment 1998: 65) was employing a much wider discourse of “basic skills,” “employability skills,” “technician skills,” “management skills,” and “key skills” ( Payne, 2000 , p. 353).

As is evident, the term “skill” (i.e., a noun) began to be used as an independent concept and replaced the use of the term as a characteristic referring to people and professions for example “skilled craftsmen,” “skilled labor,” and “skilled trades” (i.e., an adjective) in the policy rhetoric. The consistency of the use of “skill” in the literature reflects a tendency to turn the abstract notion of a “skilled craftsman” into something more concrete. In this transition, one can identify a reified conceptualization of skill, according to which “skill” is an entity – often a property of an individual (see Sfard, 1998 ; Clarke and Winch, 2006 ).

At the definitional level, the criteria of what counts as skill expanded considerably, which naturally meant the expansion of the term “skill” as well. Relevant here is the ongoing debate around which jobs should be placed on the high skills end of the spectrum (see Lloyd and Payne, 2008 ). In Marx’s work (1970), for example, distinguishing criteria for skilled job included the high wages and low levels of physical labor at the same time. More recent seminal theoretical work summarizes the criteria distinguishing “unskilled” and “skilled” jobs ( Lloyd and Payne, 2008 ). The thinking behind such distinction is quite different from that of Marx. The authors discuss as an example (p. 1–2) the emergence of categories such as “emotional labor” ( Hochschild, 1979 , 1983 ) as a form of skilled labor “ requiring a range of quite complex and sophisticated abilities (see Bolton, 2004 , 2005 ; Korczynski, 2005 ).” The additional criteria for “what count as skill” in this work suggest a progressively ambiguous use of skill, which destined to term “skill” itself to ambiguity.

Third was the versatility of the term rendering it useful within the context of a range of scientific disciplines. Research on skills is rampant in the international literature, for example in cognitive studies – since many decades now – ( Anderson et al., 1996 , 1997 ), in education ( Clarke and Winch, 2006 ; Eraut and Hirsch, 2007 ; Ritter et al., 2018 ), in policy-making ( Wolf, 2004 , 2011 ; Ewens, 2012 ; World Economic Forum [WEF], 2015 ; OECD, 2016 ; LINCS, 2020 ), in labor market studies ( Meager, 2009 ; Kok, 2014 ), in management ( Kantrowitz, 2005 ; Stevenson and Starkweather, 2010 ), or in medicine ( Maguire and Pitceathly, 2002 ; Kurtz et al., 2005 ), to name a few. This evidence corroborates the multi-currency of “skill”,” which operationalizes cognitive mechanisms , human capital (the worker) , and jobs and tasks , depending on the discipline. It is because of this that we tend to speak of people and work in terms bundles of “skills” ( Darrah, 1994 ). The problem is this seems hard to avoid considering that the “deeper one looks into any activity the more knowledge and skill one is likely to find” ( Lloyd and Payne, 2009 , p. 622 drawing from Attewell, 1990 ).

Taken together, this evidence suggests not only the “ conceptual equivocation ” ( Payne, 2000 ) of the term as it is, but also the potentially perpetual emergence of new skills categories, a “galaxy of “soft,” “generic,” “transferable,” “social,” and “interactional’ skills ” (p. 354).

Soft Skills, Categories of Soft Skills, and Links Between Them

Soft skills were among the skills categories resulting from such expansion. While the emergence and use of the category of “soft skills” signified an important division between those skills that were cognitive and technical in nature – now frequently referred to as hard/technical skills – and those that were not, a unified view of the term in the literature has not been achieved. The genesis and use of the term are traced as far back as 1972 in training documents of the US Army (see Caudron, 1999 ; Moss and Tilly, 2001 ). Since then, the term has been expanded itself to comprise categories (in the various lists of soft skills) that include (but not exhaust to):

(a) Qualities (some of which one can see in the emotional intelligence literature) including adaptability, flexibility, responsibility, courtesy, integrity, professionalism, and effectiveness, and values such as trustworthiness and work ethic (see indicatively Wats and Wats, 2009 ; Touloumakos, 2011 ; Robles, 2012 ; Ballesteros-Sánchez et al., 2017 );

(b) Volitions , predispositions , attitudes like good attitude , willingness to learn , learning to learn other skills , hardworking , working under pressure, or uncertainty (see indicatively Stasz, 2001 ; Stasz et al., 2007 ; Andrews and Higson, 2008 ; Cinque, 2017 );

(c) Problem solving , decision making, analytical thinking/thinking skills , creativity/innovation , manipulation of knowledge , critical judgment (see indicatively Cimatti, 2016 ; Succi, 2019 ; Succi and Canovi, 2019 ; Thompson, 2019 );

(d) Leadership skills and managing skills (see indicatively Crosbie, 2005 ; Lazarus, 2013 ; Ballesteros-Sánchez et al., 2017 ), as well as self -awareness , managing oneself/coping skills (see Cimatti, 2016 ; Cinque, 2017 ; Thompson, 2019 );

(e) Interpersonal savvy/skills , social skills , and team skills , effective, and productive interpersonal interactions (see indicatively Kantrowitz, 2005 ; Bancino and Zevalkink, 2007 ; Succi and Canovi, 2019 ; Thompson, 2019 );

(f) Communication skills (see indicatively Wats and Wats, 2009 ; Mitchell et al., 2010 ; Stevenson and Starkweather, 2010 ; Robles, 2012 ; Cinque, 2017 ) including elements of negotiation , conflict resolution , persuasion skills , and diversity (see, in addition, Bancino and Zevalkink, 2007 ; Majid et al., 2012 ; Cinque, 2017 ; Succi and Canovi, 2019 ) as well as articulation work – that is orchestrating simultaneous interactions with people, information, and technology (see Hampson and Junor, 2005 ; Hampson et al., 2009 ); but also going as far as.

(g) Emotional labor (originally from Hochschild, 1983 ), and even in some cases (in service jobs for example).

(h) Aesthetics , professional appearance , and “ lookism ” (see Nickson et al., 2005 ; Warhurst et al., 2009 ; Robles, 2012 ); finally,

(i) Other areas covered included cognitive ability or processes (see Cimatti, 2016 ; Ballesteros-Sánchez et al., 2017 ; Thompson, 2019 ), ability to plan and achieve goals (see Cimatti, 2016 ).

Next to the expansion of the categories comprising soft skills, the hierarchical relationships between the different categories of soft skills, as featured in the literature, added to its ambiguity. An example is the relationship between communication and interpersonal skills. In some places, the two terms are used as interchangeable; in some other cases, they are seen as two distinct categories forming alongside other categories of the construct of soft skills ( Halfhill and Nielsen, 2007 ; Anju, 2009 ; Selvalakshmi, 2012 ; Jain and Anjuman, 2013 ). Finally, elsewhere, a hierarchical relationship exists between the two, namely the former is seen a part (a subcategory) of the latter ( Rungapadiachy, 1999 ; Hayes, 2002 ; Harrigan et al., 2008 ). The simultaneous overlap, submerging, vicinity, and yet disparity of terms such as communication and interpersonal skills is just one of the many in the skills literature (cf. Kinnick and Parton, 2005 , for discussion about overlap between communication and leadership). It becomes evident, accordingly, that these terms, much like the term soft skills has often become so stretched that their limits have become, in turn, vague. Their expansion meant actually that they became polysemous and, because of that, hard to grasp in a unified and organized way and therefore restricted in meaning and use.

This mini- review unveiled two important aspects in relation to the research and the conceptualization of soft skills. The first is that the rampant categories and lists of soft skills seem to be either the outcome of empirical work focusing on breaking down work activities (paraphrasing Lloyd and Payne, 2009 ) in addressing skills requirements, or recycled lists drawing from this work. This is the approach typically encountered in papers focusing on training graduates, training programes within organizations, and employers skills demands (for example Schulz, 2008 ; Constable and Touloumakos, 2009 ; Chamorro-Premuzic et al., 2010 ; Majid et al., 2012 ; Ballesteros-Sánchez et al., 2017 ; Succi and Canovi, 2019 ). This, however, can only be taken to be a veneer of an evidence-based approach to soft skills conceptualization, which is key for their understanding and development for two reasons:

(a) Because same categories mean different things and different categories mean same things to stakeholders (researchers, participants, policymakers), and

(b) Because the aim of researching skills requirements is very different to the aim of researching soft skills characteristics and their nature (soft skills conceptualization).

It is at the level of the conceptualization, characterization, and definition, therefore, that we need to pursue an evidence-based approach, so as to achieve a common language and avoid getting lost in translation in the use of the various soft skills terms.

The second aspect is that, in line with the way the literature features soft skills, they encompass such a wide and diverse range of categories (for example qualities, traits, values, predispositions, etc.) that makes it impossible to think about them as a coherent whole. Arguably, the warehousing approach of soft skills categories development, abstracts behaviors from the context of their enactment and call them skills. This approach, by definition, has ramifications for our understanding of soft skills characteristics, which in turn affects the thinking that underpins their development. For example, given that skills in line with this view are seen as actions toward tasks, it brings to the center the person who acts ( Matteson et al., 2016 ) and, by extension, construes them as personal properties of a generic nature that can be first acquired and transferred uncomplicatedly across contexts ( Touloumakos, 2011 ). Given that this (much like any other) conceptualization of soft skills affects the way we think about their development and their inclusion in education curricula, it is clear that a more inclusive, bottom—up and embedded view would provide a more pragmatic and meaningful alternative in their study.

Author Contributions

This work has been undertaken in its entirety by AT.

Part of the work presented here was undertaken as a Ph.D. research.

Conflict of Interest

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


The Ph.D. was funded by the Economics and Social Research Council and the State Scholarship Foundation. The author would like to thank Dr. Alexia Barrable for her thoughtful comments and insights on this work.

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Keywords : soft skills, skill, soft skills conceptualization, soft skills development, curriculum design

Citation: Touloumakos AK (2020) Expanded Yet Restricted: A Mini Review of the Soft Skills Literature. Front. Psychol. 11:2207. doi: 10.3389/fpsyg.2020.02207

Received: 31 May 2020; Accepted: 06 August 2020; Published: 04 September 2020.

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Copyright © 2020 Touloumakos. 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: Anna K. Touloumakos, [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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The Power of Soft Skills: Our Favorite Reads

soft skills research paper

The the skills we call “soft” are the ones we need the most.

If you’re new to the workforce, you’ve probably read articles about the importance of building “soft skills”—empathy, resilience, compassion, adaptability, and others. The advice isn’t wrong. Research shows  soft  skills are foundational to great leadership and set high performers apart from their peers. They’re also increasingly  sought by employers .

  • EN Evelyn Nam is a graduate of Harvard Kennedy School, Columbia Journalism School, and Harvard Divinity School. She has reported on business and Asian American affairs. Currently, she is an assistant editor at Harvard Business Publishing.

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The future of soft skills development: a systematic review of the literature of the digital training practices for soft skills

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soft skills research paper

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Soft skills are becoming increasingly important in the workplace. Due to their interpersonal nature and experiential face-to-face reality, they are often touted as nearly impossible to develop online; our study finds that an increasing body of literature is offering evidence and solutions to overcome impediments and promote digital technologies use in soft skills training. This review aims to perform a state of the art on the research on digital solutions for soft skills training using a systematic review of literature.

A systematic literature review following the PRISMA statement was conducted on the ISI Web of Science, where from 109 originally collected papers, 37 papers were held into consideration for the in-depth analysis.

This paper aims at bringing clarity for both research and practice to facilitate and promote more effective online training initiatives as well as innovative solutions for training in different areas.

In recent years, the global economy has been facing structural changes, rapidly evolving into the world of digital transformation. The unpredictability of the nature and pace of the changes will make it crucial that individuals in groups, organizations and societies alike develop skills for dealing with all kinds of situations, especially soft skills and in particular emotional and social competencies. In this work we look into the literature in a systematic way in order to understand the types of competences most addressed, most commonly used techniques and positive and negative results of the training...

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Soft skills, do we know what we are talking about?

  • Review Paper
  • Published: 02 June 2021
  • Volume 16 , pages 969–1000, ( 2022 )

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soft skills research paper

  • Sara Isabel Marin-Zapata   ORCID: 1 ,
  • Juan Pablo Román-Calderón   ORCID: 1 ,
  • Cristina Robledo-Ardila   ORCID: 1 &
  • Maria Alejandra Jaramillo-Serna   ORCID: 1  

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During the last decade, individual competencies and soft skills have reached a position of paramount importance among scholars in different fields. Yet, there seems to be a lack of consensus around the meaning of both concepts to the extent that they are sometimes used interchangeably. In response to this, we conducted a systematic review aimed at shedding light on the meaning of competencies and soft skills in business literature. The theoretical perspectives and methodological choices used by scholars were also accounted for as they are closely related to the definitions of these concepts. The systematic review presented in this paper addressed three specific research questions: (a) how are soft skills and competencies conceptualized in the reviewed literature?, (b) what are the main theories used in the study of soft skills and competencies?, and (c) methodologically, what are the main characteristics of those studies? The results indicate that there is still lack of consensus regarding the definitions of both terms. We also found that a large portion of the papers lacked a solid theoretical foundation, while the rest of the papers evidenced that business studies on competencies and soft skills suffer from theoretical dispersion. With regards to the methods used, we conclude that improvements must be made to help develop an understanding of competencies and soft skills. Consequently, a theoretical model explaining the relationships between these concepts was developed taking into account the sounder theoretical perspectives found in the literature review.

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Marin-Zapata, S.I., Román-Calderón, J.P., Robledo-Ardila, C. et al. Soft skills, do we know what we are talking about?. Rev Manag Sci 16 , 969–1000 (2022).

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Reconciling Hard Skills and Soft Skills in a Common Framework: The Generic Skills Component Approach

The distinction between hard and soft skills has long been a topic of debate in the field of psychology, with hard skills referring to technical or practical abilities, and soft skills relating to interpersonal capabilities. This paper explores the generic composition of any skill, proposing a unified framework that consists of five distinct components: knowledge, active cognition, conation, affection, and sensory-motor abilities. Building upon previous research and theories, such as Hilgard’s “Trilogy of Mind”, the generic skill components approach aims to provide a comprehensive understanding of the structure and composition of any skill, whether hard or soft. By examining these components and their interactions, we can gain a more in-depth understanding of the nature of skills and their development. This approach has several potential applications and implications for various fields, including education, training, and workplace productivity. Further research is needed to refine and expand upon the generic skill components theory, exploring the interactions between the different components, as well as the impact of contextual factors on skill development and use.

1. Introduction

In today’s complex, interconnected world, the importance of having a diverse set of skills for success is undeniable. The ability to define, develop and utilise one’s skills is considered a vital part of personal and professional success. This success depends heavily on the acquisition and maintenance of both soft and hard skills. In the modern workforce, employers are searching for the perfect candidate, the one who can bring a combination of skills to the table. Indeed, skills can generally be divided into two main categories—hard skills and soft skills. Hard skills refer to technical or practical abilities, such as programming languages, engineering, accounting, and other occupational skills, whereas soft skills are interpersonal capabilities, such as communication, problem-solving, and emotional intelligence ( Cimatti 2016 ; Laker and Powell 2011 ).

Although these two types of skills are often categorised separately, it is important to understand their interdependence, as well as their contributions to certain areas of expertise. In recent years, there has been increasing recognition of the importance of soft skills in many areas, including education and business ( Andrews and Higson 2008 ; Succi and Canovi 2020 ). The so-called “soft skill revolution” has seen a growing interest in developing and assessing these skills, as organisations have become increasingly aware of their value in the workplace. Yet, there is still some debate about what constitutes a soft skill, and to what extent hard skills remain essential for success. Despite the acknowledged value of soft skills, the lack of a standard definition or systematic approach to measuring and assessing these skills poses a challenge when attempting to review and compare them ( Dede 2010 ; Robles 2012 ; Rasipuram and Jayagopi 2020 ).

Even before challenging the concept of soft skills, there is the question of what a “skill” is, and how to develop certain skills, as it remains an ongoing area of research for psychologists and educators. Whereas the study of skills has traditionally been associated with individual traits such as intelligence and talent, an emerging field of inquiry suggests that the composition of any skill is made up of several core elements. Overall, skills are an important foundation for development, yet much research is needed to understand better the generic components of skills. Although soft skills and hard skills seem very different in the way they are used and observed, what actually makes them inherently different? If both are actually skills, they may have more in common than it seems. In recent years, research into the generic composition of any skill, and the relationship between soft skills and hard skills, has gained increased interest due to its implications for workplace productivity.

Researchers have identified that any workplace skill requires a combination of hard and soft skills ( van der Vleuten et al. 2019 ; Lyu and Liu 2021 ). They have also elucidated that there are shared components between hard and soft skills which could be seen as the bridge between them ( Pieterse and Van Eekelen 2016 ; Kuzminov et al. 2019 ). This presents an interesting opportunity for educators and trainers to develop individuals in an integrated manner, allowing for an understanding of both technical and non-technical components of skills.

This paper explores the generic composition of any skill and the common ground between soft skills and hard skills. Hilgard’s “Trilogy of Mind” (1980) provides useful insights into the debate, by suggesting that all skills—whether hard or soft—can be understood in terms of three distinct components: cognition, conation, and affection. In this article, we will discuss how Hilgard’s theory can be applied in order to describe the composition of any skill, and argue that, theoretically, there is no difference between soft and hard skills, opening the way to a generic skills framework.

2. Critical Literature Review

2.1. definition of skill.

As the distinction between soft and hard skills is not standardised, it is important to consider different definitions of “skill” for the purposes of this article. Skill is a multifaceted concept that has been studied extensively in the scientific literature ( Vallas 1990 ; Clarke and Winch 2006 ; Green 2011 ). According to the definition of the 2023 Merriam-Webster dictionary, a skill is “the ability to use one’s knowledge effectively and readily in execution or performance” ( Merriam-Webster n.d. ). It describes the ability that develops from practice, training, and experience to perform a specific task to a certain standard. It has been subject to considerable examination by researchers across different disciplines, including psychology, neuroscience, education and sports science ( Gagné and Fleishman 1959 ; Frese and Stewart 1984 ; Bo et al. 2008 ).

Boyatzis ( 1982 ) defined “skill” as “an underlying characteristic of a person that has a causal relationship with their average or superior performance in a given function”. In more concrete terms, “skill” refers to an individual’s ability to accomplish tasks by utilising appropriate resources, including those acquired through training or previous experience ( Le Boterf 2000 ). A skill can be conceptualised as specific know-how that is pertinent to a given situation, resulting in the combination of knowledge, other mental abilities and physical strength, agility, coordination, and motor abilities ( Green 2011 ). This definition provides a clear understanding of the underlying competencies and knowledge necessary to successfully carry out any task, regardless of whether it concerns soft or hard skills. In addition, the success of skills is partially dependent on the direct content of the tasks, abilities, values, interests, and the environment of the individual ( Le Boterf 2000 ).

As noted by DeKeyser ( 2020 ), the term “skill” encompasses the ability to process and understand information, interpret, and use it in order to complete a task. It involves both cognitive and motor abilities, which together form a basis for mastery ( Roebers et al. 2014 ; Van der Fels et al. 2015 ). Both require knowledge and the ability to store and recall information, as well as the ability to interpret and apply it correctly. Through practice and repetition, skills become increasingly automatic and rapid, and proficiency is observed.

As such, “skill” can be seen as the ability to retrieve knowledge and apply it to a task in a proficient manner. Cognitive factors include working memory, various forms of reasoning, and problem-solving ( Carroll 2003 ). Motor abilities include factors such as coordination, muscle and joint strength, and speed ( Zajac 1993 ). In more psychological terms, they can be seen as a component of behavioural abilities. When including motor abilities, the dyad created by cognitive and behavioural components plays an important role in the development and refinement of skills. This is an important concept to recognise when considering the notion of skill, as both the ability to understand and interpret knowledge, as well as the application of what has been learnt are essential for skill development. In conclusion, a skill is an ability that is refined with training, technique, and experience. It is noted to involve a combination of cognitive and behavioural components which interact to allow the effective completion of a given task.

A wide range of skills have been studied, such as motor skills, sensory and perceptual skills, cognitive skills, and social skills ( Fischer 1980 ). Motor skills are defined as the ability to control and coordinate the movements and actions of the body ( Newell 1991 ). Sensory and perceptual skills involve the ability to receive, interpret, and act upon sensory information, such as visual, auditory, and tactile data ( Karni and Bertini 1997 ). Cognitive skills encompass the ability to think logically, problem-solve, and make decisions, whereas social skills involve the ability to interact and communicate effectively with others ( Patterson 2008 ). Overall, skills are multifaceted constructs that enable humans to continue to grow and learn in a variety of contexts, through general practice and experience, as well as through the development of specific tasks and strategies.

2.2. Definitions and Characteristics of Hard Skills

Hard skills refer to technical, tangible, and quantifiable abilities related to the use of equipment for a specific job, such as driving a car, computer programming, or welding ( Lyu and Liu 2021 ). Hard skills are typically acquired through training and education and are a requisite for performing job duties. They are necessary for specific tasks within an industry that requires specific expertise and proficiency, such as welding, accounting, and using a 3-D printer. As researchers note, hard skills are also differently defined along the lines of work and education. A person with a background in computer science may define hard skills as the technical abilities required for software development, whereas someone with a background in design may define hard skills as the artistic abilities needed for graphic design. The importance of hard skills has long been acknowledged in the workplace, especially because the manipulation of these skills often leads to measurable performance outcomes ( Rainsbury et al. 2002 ; Hendarman and Cantner 2018 ). Consequently, they are usually emphasised during recruitment processes and have been found to play a determining role in the hiring decisions of employers ( Bishop 2017 ; Huber 2018 ). Actually, both motivation and hard skills play an important role in positive job performance ( Hendarman and Cantner 2018 ).

2.3. Definitions and Characteristics of Soft Skills

In 1972, the term “soft skills” was first used by the researcher Paul G. Whitmore, during a training conference in Texas for the US Army Continental Army Command (CONARC). Whitmore used the term “soft skills” to refer to crucial job-related skills that involve little or no interaction with machines (CONARC 1972, cited in Parlamis and Monnot 2019 ). They may as well be considered behaviours that a person must mobilise in order to reach a given objective competently ( Tate 1995 ). Considering the context of hard skills, soft skills are non-technical abilities that are harder to measure and quantify ( Kantrowitz 2005 ; Byrne et al. 2020 ). Soft skills involve personal, interpersonal, and intrapersonal abilities that are essential in the workplace ( Dell’Aquila et al. 2017 ). Examples of soft skills include emotional intelligence, communication, creativity, problem-solving, team building, and stress management ( Martins et al. 2020 ).

Unlike hard skills, soft skills tend not to be acquired through formal education and training and often require dedication, self-reflection, and self-improvement ( Chell and Athayde 2011 ; Wisshak and Hochholdinger 2020 ). This does not mean that hard skills do not require these same qualities, however, the probability of systematic acquisition seems less predictable for soft skills, and more related to personal qualities, as their use will be specific to every person. Furthermore, soft skills are typically more developed through social experience, which is why they are often referred to as “people skills” ( Levasseur 2013 ).

There are many different terminologies when referring to soft skills, such as social competencies, interpersonal skills, or even emotional intelligence ( Matteson et al. 2016 ). Social competencies encompass a broader range of abilities that enable individuals to navigate effectively interpersonal situations, build and maintain relationships, and work well with others. These competencies include communication, teamwork, adaptability, and cultural awareness ( Rychen and Salganik 2003 ). Interpersonal skills refer to the abilities needed to effectively interact, communicate, and collaborate with others. These skills include active listening, empathy, conflict resolution, and negotiation ( Spencer and Spencer 1993 ). Emotional intelligence encompasses the ability to recognise, understand, and manage one’s own emotions and the emotions of others. It is closely related to interpersonal skills and includes self-awareness, self-regulation, motivation, empathy, and social skills ( Goleman 1995 ; Mayer et al. 2008 ).

With over 119 labels identified in the literature in 600 publications about soft skills over the past 50 years ( Joie-La Marle et al. 2022 ), numerous frameworks have been created to categorise and understand them. Depending on the approach, these frameworks deal with social skills, emotional skills, cognitive skills, or all of them. Their main interest is generally to delineate critical skills needed for the future of work, which is the reason why the field of education is where most frameworks are created. Researchers, schools, and even international organisations have created their own soft skills frameworks. Lamri ( 2018 ) reviewed various soft skills frameworks. In 2016, OECD released an overview of the key findings from the OECD Survey of Adult Skills ( Kankaraš et al. 2016 ), which highlights the importance of soft skills in the labour market and discusses policy implications for developing these skills.

Overall, despite the difficulty to agree on frameworks and terminologies, the relevance of soft skills for individual success in the workplace has been widely discussed in the literature. Numerous authors have called attention to the interplay between soft skills and other personal qualities to facilitate individual performance in the workplace or in general ( Rychen and Salganik 2003 ; Kantrowitz 2005 ; Cimatti 2016 ; Ibrahim et al. 2017 ). Further, soft skills can be instrumental in improving work satisfaction and are associated with higher levels of engagement, productivity, and creativity in the workplace ( Palumbo 2013 ; Feraco et al. 2023 ; the role of particular individual qualities or activities has been shown in numerous studies ( Reysen et al. 2019 ; Feraco et al. 2023 ).

In terms of educability, Durlak et al. ( 2011 ) published a meta-analysis related to categories of self-emotional learning (SEL). This meta-analysis examined the effectiveness of school-based social and SEL programs in enhancing students’ skills, attitudes, prosocial behaviour, and academic performance. The researchers analysed data from 213 studies involving more than 270,000 students from kindergarten to high school. The results showed that students who participated in SEL programs had significantly better social and emotional skills, attitudes, and behaviour compared to their peers who did not participate in these programs. Additionally, the study found that students involved in SEL programs also had an 11 percentile-point gain in academic achievement. Another study considers soft skills through the prism of social, emotional, and behavioural skills ( Soto et al. 2022 ).

2.4. Differences and Commonalities between Hard and Soft Skills

It is important to have both hard and soft skills in order to be successful in the workplace. Research has shown that both types of skills are necessary and having a combination of the two leads to greater success ( Rainsbury et al. 2002 ; Vasanthakumari 2019 ; Lyu and Liu 2021 ). For example, software development requires typically a variety of technical know-how and problem-solving capabilities ( Groeneveld et al. 2021 ). For an individual to successfully complete such a task, he or she must often combine soft skills such as creativity and knowledge of various programming methods to come up with a successful solution. Designers must master computer software and physical tools to create prototypes as well as people skills to interact with clients or team members in collective design projects.

Hard skills are necessary for specific knowledge-based tasks and are often taught in universities and technical schools. On the other hand, soft skills are often a better predictor of workplace success than hard skills, as they are essential for personal and interpersonal functioning ( Hargood and Peckham 2017 ). Soft skills can help to identify candidates who have the necessary qualities to lead, manage, and collaborate, which are essential for a successful and productive workplace ( Rainsbury et al. 2002 ). Additionally, soft skills are also important for customer service, which is a required and necessary component of most work environments.

Whereas the different terminologies highlight the various aspects of hard and soft skills, it is important to recognise that these skills often intersect and support one another in various contexts. As the literature continues to evolve, researchers are increasingly examining the interrelationships between hard and soft skills and their combined contribution to individual and organisational success. On many occasions, the differences between soft skills and hard skills are often difficult to discern.

It is possible for an individual to have both strong soft and hard skills, and studies tend to show that it is the combination of both that increases an individual’s chances for success in the workforce by providing a well-rounded and competitive toolkit for employers ( Rainsbury et al. 2002 ; Succi and Canovi 2020 ). Having a mixture of both types of skills is seen as a requirement for many positions.

When seeking to hire candidates, employers should consider the importance of both soft and hard skills. Although employers want typically to find someone who has technical expertise and qualifications, they should consider attributes such as creativity, communication, interpersonal skills, and problem-solving, as well ( Lyu and Liu 2021 ). Research has shown that hard skills become obsolete more quickly than soft skills ( Dominici 2019 ; Schultheiss and Backes-Gellner 2022 ), so employers should take into account the importance of both types of abilities when hiring. Furthermore, employers should also provide the necessary training and mentorship to ensure that their employees have the correct skillsets for the job ( Succi and Canovi 2020 ).

Generally speaking, the criteria for determining whether a skill is soft or hard depend on the context in which the skill is used. Some researchers argued that soft skills are often seen as being more “Person-Centred” whereas hard skills are classified as “Task-Centred”, emphasising the need for individuals to be able to both interact with and help others ( Rodríguez-Jiménez et al. 2021 ). As a result, soft skills are typically viewed as more important when it comes to interpersonal aspects of professional life such as communication, problem-solving, customer service, and teamwork, among others. Hard skills are generally evaluated and valued based on their effectiveness with regard to the completion of a specific task.

Although hard and soft skills have different definitions and uses, they also overlap to some degree ( Green 2011 ; Cinque 2016 ). For example, communication, although traditionally categorised as a soft skill, also involves technical aspects like data analysis and writing, using software to produce presentations. Similarly, interpersonal skills include specific knowledge about group behaviour and social codes, which could be seen as a hard skill ( Bishop 2017 ). There exists an interdependent relationship between the two, with each trait enabling the other to succeed ( Lyu and Liu 2021 ). As an example, hard skills such as accounting or designing require the support of certain soft skills, like communication and problem-solving, to truly display the potential of the hard skill. Additionally, numerous studies show a positive relationship between soft skills and hard skills performance ( Kuzminov et al. 2019 ; Lyu and Liu 2021 ), suggesting the need for a synergistic combination of the two that can lead to successful job outcomes.

3. From Skills Theories to the Generic Skills Component Approach

3.1. foundations for the generic skill components approach.

Is the distinction between hard/soft useful? Is there, metaphorically, a scale of “hardness” of skills, like Mohs’ scale for the hardness of minerals, ranging from talc (very soft) to diamonds (very hard)? Numerous authors have raised the idea of a continuum from hard to soft skills passing by a vast mid-scale with semi-hard and semi-soft skills (see Andrews and Higson 2008 ; Clarke and Winch 2006 ; Dell’Aquila et al. 2017 ; Hendarman and Cantner 2018 ; Lyu and Liu 2021 ; Spencer and Spencer 1993 ; Rychen and Salganik 2003 ). Le Boterf ( 2000 ) suggests that skills are better understood as a continuum, with some skills containing both hard and soft components.

The generic skill components approach builds upon these recent findings, suggesting that all skills can be understood through a shared framework of five distinct components: knowledge, active cognition, conation, affection, and sensory-motor abilities. This integrated approach has the potential to reconcile the traditional distinction between hard and soft skills, providing a more comprehensive understanding of the complex nature of skills and their development.

3.2. Discrediting Skills as Discrete Entities

Working on a generic structure for all skills implies that skills are not discrete entities as such. We believe there is a necessity to clarify that aspect, before moving towards the construction of a generic skills approach. Consider the following arguments:

1. Overlapping and interrelated nature of skills: Skills are often interconnected and interdependent, making it difficult to clearly separate them into distinct categories. For example, the successful application of technical skills often depends on the presence of effective interpersonal skills, and vice versa ( Kavé and Yafé 2014 ; Gardiner 2017 ). This overlap and interrelatedness challenges the idea that skills exist as discrete entities ( Greenwood et al. 2013 ; Bean et al. 2018 ).

2. Contextual factors: The relevance and importance of specific skills can vary depending on the context in which they are applied. This contextual variability can lead to differing interpretations and classifications of skills, further challenging the idea of skills as discrete and stable entities ( Perkins and Salomon 1989 ; Hall and Magill 1995 ; Widdowson 1998 ).

3. Evolving skill requirements: The rapidly changing nature of work and technological advancements requires individuals to adapt continuously and develop new skills. As a result, the boundaries between different skill categories may become increasingly blurred as individuals are expected to possess a diverse and dynamic skillset ( Dede 2010 ; Hargood and Peckham 2017 ; Dominici 2019 ).

4. Limitations of terminologies: The use of specific terminologies for hard and soft skills can sometimes oversimplify or constrain our understanding of the multidimensional nature of skills. By focusing on specific aspects or dimensions of skills, these terminologies may inadvertently perpetuate the idea that skills are discrete entities, rather than acknowledging the complex, interconnected permeable nature of skill development and application ( Matteson et al. 2016 ; Lyu and Liu 2021 ).

The overlapping and interrelated nature of skills, the continuum perspective, contextual factors, evolving skill requirements, and the limitations of terminologies contribute to the difficulty of treating skills as discrete entities. Recognising these challenges can help researchers and practitioners develop more nuanced and integrative approaches to skill development and assessment. Building on this analysis, we believe there is a need for a unified approach to the structure of skills.

3.3. Using Goldstein and Hilgard’s Work as a Core Basis

The ambition to find a generic structure for skills is not new. Goldstein ( 1989 ) proposed a framework, with four components structuring any skill: cognitive, affective, motivational, and behavioural. In Goldstein’s, cognitive components involve the understanding and knowledge associated with a skill, such as problem-solving and analytical skills. Affective components involve emotions and attitudes, such as self-awareness and empathy. Motivational components involve the drive and determination to succeed, such as perseverance and ambition. Last, behavioural components involve the actual physical performance of a skill, such as hand-eye coordination and agility.

Although the literature is filled with definitions and discussions about skills, we choose in this article to use the work of Goldstein ( 1989 ) as a primary basis. His work, both theoretical and empirical, provides a comprehensive framework for understanding, designing, implementing, and evaluating skills development in organisations.

Applying these four components to hard and soft skills, we can see that all skills are composed of the same elements, but with different weights depending on the context in which they are used. For example, a hard skill such as programming would require a higher level of cognitive ability but lower levels of affection. In contrast, a soft skill such as active listening would require a higher level of affection but lower levels of cognition. In that way, Goldstein’s framework seems a relevant basis to reconcile soft skills and hard skills. However, it is necessary to take a step back and take a closer look at Goldstein’s components.

Goldstein’s work relates to Hilgard ’s ( 1980a ) ‘Trilogy of Mind’, which describes human consciousness in terms of three main dimensions: cognition, conation, and affection. Hilgard ( 1975 , 1980b , 1986 ) examines learning, personality, and hypnosis, and how they interact with one another to shape our understanding of the mind. Hilgard’s trilogy is itself based on the ‘Trilogy of Mind’ that Emmanuel Kant espoused.

Hilgard’s conception of these concepts differs from Goldstein’s:

  • Cognition is the ability to think and solve problems, acquire information, and understand the world around us. It entails the processing of ideas and facts which allows the user to make better-informed decisions.
  • Conation is the preferred pattern of actions and choices, integrating the results of cognitive processes to take action in order to achieve our objectives. It relies on the capacity to plan, as well as to monitor and evaluate our goal-driven performance.
  • Affection is the ability to build and maintain relationships with others, stimulating social interaction and facilitating collaborative work. It involves the capacity to understand and empathise with others’ needs, as well as the ability to develop positive social networks.

In this approach, conation has a clear link with cognition and action, and we believe that, with some adaptations, it can be a promising way to apprehend motivational aspects, known as “volition” in some frameworks. Cognition should be treated as an active dynamic process. In this process, knowledge is acquired, used, transformed, and produced. It is however useful to distinguish the knowledge itself and the information-processing actions in which this knowledge is used.

Affection as seen by Hilgard seems richer than what is envisioned by Goldstein and relates better to the concept of emotional intelligence ( Goleman 1995 ). Goldstein underlines the importance of the body actually taking action. However, calling it behaviour might be confusing, regarding the extensive literature about behaviour, and the way behavioural psychology apprehends it. Following Goldstein’s definition, we believe sensory-motor abilities to be more appropriate as a component name.

Considering these adjustments, we propose the following revised framework for any skill, composed of five distinct components:

  • Knowledge includes both external knowledge or facts, such as technical job-related knowledge, as well as internal knowledge, such as memory ( Bloch 2016 ; Zagzebski 2017 ).
  • Active cognition involves perceiving and processing information to form decisions and opinions, such as perception, attention, and judgement ( Bickhard 1997 ). The analysis of the environment and the context falls under active cognition.
  • Conation is the component that describes preferences, motivations, and volitional components of behaviour. It is the drive or impulse to act and is often referred to as the “will” or “willingness” to act ( Csikszentmihalyi 1990 ). We believe it goes beyond motivation as referred to by Goldstein.
  • Affection: Affection is the ability to empathise with and manage feelings in order to build and maintain relationships with others.
  • Sensory motor abilities: Sensory motor abilities refer to the ability to control and coordinate movements. This includes the ability to perceive, interpret, and respond to sensory input, as well as the ability to plan and execute movements. Examples of sensory-motor abilities include balance, coordination, and fine motor skills.

Using this framework, it becomes possible to describe both soft skills and hard skills in the same way. With time, we believe the distinction between both types of skills may become either obsolete or insufficient. Only the specific content and weight of each component would matter in order to describe a skill, to determine the overlap between two skills, or the transferability from one skill to another.

3.4. Developing the Generic Skill Components Approach

The generic skill components approach aims to provide a comprehensive understanding of the structure and composition of any skill. This approach posits that all skills, whether hard or soft, can be understood in terms of five distinct components: knowledge, active cognition, conation, affection, and sensory-motor abilities. By examining these components and their interactions, we can gain a more in-depth understanding of the nature of skills and their development.

This approach is supported by previous research that has identified common elements across various types of skills. For example, Rychen and Salganik ( 2003 ) propose a model of key competencies that includes cognitive, intrapersonal, and interpersonal dimensions, which align with the active cognition, conation, and affection components of the generic skill components approach. Similarly, other studies highlight the importance of cognitive, affective, and behavioural processes in the development and application of both hard and soft skills ( Parlamis and Monnot 2019 ; Soto et al. 2022 ). Our approach extends beyond existing models by incorporating sensory-motor abilities, which are often overlooked in discussions of skill development. This inclusion acknowledges the importance of physical and perceptual abilities in the successful application of many skills, particularly in fields such as sports, manufacturing, and healthcare.

This approach has several potential applications and implications for various fields, including education, training, and management. By understanding the generic components of skills, educators and trainers can develop more effective and holistic approaches to skill development, integrating both technical and non-technical components. In the workplace, a greater understanding of the generic composition of skills can help inform hiring decisions, performance evaluations, and employee development programs. If a skill has a major active cognition component, the resulting pedagogic engineering will be very different compared to a skill with a major knowledge component.

Further research is needed to refine and expand upon the generic skill components approach. Future studies could explore the interactions between the different components, as well as the impact of contextual factors on skill development and use. Indeed, the generic skill components approach highlights the importance of context in the development and application of skills, suggesting that educators and trainers should consider the specific environments in which their students or employees will be applying their skills. This may require the development of more context-specific training programs that focus on the unique challenges and opportunities presented by different work environments. Additionally, researchers could investigate the potential for more distinct skill categories and their implications for various domains.

3.5. Tentative Representation of the Generic Skills’ Components Framework

Although the approach needs to be further developed and tested empirically, we propose in this article an attempt at visual representation, displaying the five generic components in a diagram (see Figure 1 ). This diagram may be seen as a template to be used for skills description, as proposed later.

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Visual representation of the generic skills’ components framework.

Our understanding of generic skills components would be that all components exist independently and need to be associated to create the necessary skill. This implies that they are not relative to each other, meaning that for a given skill, it is possible that all components are required at a very high level of mastery or development. Furthermore, conversely, for another skill, it is possible that all components are required at a very low level. In this manner, all types of combinations are possible, the point being that the necessity of one component at a high level does not determine the level of other components.

3.6. Tentative Representation of Skills Composition Using the Framework

Below, we propose three examples of using the framework to represent skills: oral communication, Python programming, and logical analysis. At this stage, the assessment is very basic, as it results in a consensus among the authors, having both theoretical and empirical experience in skills expertise. These specific cases of skill descriptions will need to be challenged in order to be considered consensual, but the purpose of this section is rather to show the possibilities offered by the generic skills’ components approach. For each skill, we propose:

  • A visual representation based on the generic skills’ components framework (see Figure 1 );
  • A rating from 1 (low) to 5 (high) for each component;
  • An explanation of the importance given to each component in the context of the skill;
  • A suggestion of a training program detailed for each component.
  • (A) Example 1: Oral communication

For the skill “oral communication”, which is usually referred to as a soft skill, we describe below on a scale of importance of 1 to 5 for each component, the composition for each component (see Figure 2 ):

  • Knowledge: 4/5—Knowledge is essential for effective oral communication, as it involves understanding the topic being discussed, the context, and the audience. Having a solid grasp of the subject matter, as well as cultural and social norms, allows the speaker to convey messages accurately and effectively. Additionally, internal knowledge helps the speaker to convey relevant information and experiences to support their points.
  • Active cognition: 5/5—Active cognition is crucial for oral communication, as it involves perceiving and processing information in real-time. Effective oral communication requires the speaker to pay attention to the audience, adapt the message based on audience reactions, and make judgments about what information to share and how to present it. It also involves critical thinking and problem-solving skills, as the speaker may need to respond to questions or objections from the audience.
  • Conation: 4/5—Trait extraversion can support oral communication because it motivates the speaker to engage with the audience and present the message confidently and persuasively. A strong willingness to act can also help the speaker overcome any anxiety related to speaking in front of others.
  • Affection: 4/5—The ability to empathise with and manage emotions is important for connecting with the audience and creating a positive atmosphere during oral communication. Understanding the emotional state of the audience can help the speaker adjust their/his/her tone and approach while managing their/his/her own emotions can ensure a calm and composed delivery. Additionally, being able to express warmth and enthusiasm can make the message more engaging and persuasive.
  • Sensory motor abilities: 3/5—Although not as critical as other components, sensory-motor abilities still play a role in oral communication. The ability to control and coordinate movements, such as gestures and facial expressions, can help the speaker convey a message more effectively and make a stronger impression on the audience. Proper posture, eye contact, and voice modulation are also important aspects of oral communication that rely on sensory-motor abilities.

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Visual representation of the generic skills components’ framework for the skill ‘Oral communication’.

It is interesting to observe that using the framework, it appears that all components are relevant to the skill of oral communication. This example shows the value of such skills that can be underestimated in their complexity.

To develop the skill of oral communication using this framework, a pedagogical program could be designed as follows:

  • Provide learners with the necessary knowledge related to the subject matter they will be communicating, whether it is through lectures, research, or reading.
  • Encourage learners to integrate this knowledge into their communication to increase their credibility and effectiveness.
  • Provide learners with opportunities to practise active listening and critical thinking to understand better the needs of their audience and adapt their communication accordingly.
  • Encourage learners to use visual aids or other communication tools to increase their impact and effectiveness.
  • Provide learners with opportunities to practise oral communication in a safe and supportive environment, such as through role-playing or group discussions.
  • Encourage learners to take risks and learn from their mistakes, building their confidence and willingness to communicate effectively.
  • Integrate exercises and activities that promote empathy and emotional intelligence, such as reflecting on the emotional impact of communication or practising active listening.
  • Encourage learners to build positive relationships with their audience, as this can enhance their effectiveness as communicators.
  • Provide learners with opportunities to practise their oral communication skills, such as pronunciation, articulation and voice projection exercises.
  • Encourage learners to practise clear and effective body language to enhance their overall communication skills.

Overall, a training program created according to the skills generic components approach should emphasise the importance of all five components of the framework and provide learners with the opportunity to develop each one in a holistic and integrated manner. By focusing on all the aspects of oral communication, learners can develop the skills they need to communicate effectively and build positive, meaningful relationships with those around them.

  • (B) Example 2: Python programming

For the skill “Python programming”, which is usually referred to as a hard skill, we indicate the importance of each component on a 5-point scale, and describe, the composition for each component (see Figure 3 ):

  • Knowledge: 5/5—Knowledge is crucial for Python programming, as it involves understanding the syntax, functions, libraries, and best practices in the language. A programmer must be knowledgeable about programming concepts, algorithms, and data structures to effectively use Python in various applications. This includes both external knowledge, such as learning from resources and documentation, and internal knowledge, such as remembering previously learned concepts and experiences.
  • Active Cognition: 4/5—Active cognition plays an important role in Python programming, as it involves perceiving and processing information to form decisions and opinions. This includes understanding the problem being solved, designing an appropriate solution, and troubleshooting any issues that arise during coding. Active cognition also involves adapting to new programming paradigms, tools, and techniques.
  • Conation: 3/5—Conation is moderately important in Python programming. Although having the motivation and willingness to learn and improve one’s programming skills is important, it may not be the primary driver for success in this field. However, showing perseverance, and having a strong drive to problem-solve, debug, and optimise code can contribute to better overall performance and growth as a programmer.
  • Affection: 2/5—Affection has a lower importance in Python programming compared to other components. While empathy and emotional intelligence may not directly contribute to programming skills, they can still play a role in building positive relationships with teammates or clients, understanding user needs, and contributing to a healthy work environment. Good communication and collaboration skills can also help when working on projects with others.
  • Sensory Motor Abilities: 1/5—Sensory motor abilities have minimal importance in Python programming. While basic motor skills are needed for typing and using a computer, the primary focus in programming is on cognitive and knowledge-based skills. However, maintaining proper ergonomics and posture while working at a computer can help prevent physical strain and promote overall well-being.

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Visual representation of the generic skills’ components framework for the skill “Python programming”.

It is interesting to observe that using the framework, it appears that active cognition and knowledge seem to be the most important components for the skill of Python programming. However, conation is not to be underestimated. Knowledge is commonly associated with hard skills, whereas active cognition and conation are commonly associated with soft skills. Although knowledge seems more important than the other components, we believe the importance of other components is generally underestimated when considering Python programming as a hard skill, as context matters. This example shows value for such skills that are unfairly considered hard skills with little to no consideration for the potential complexity of the context, or the motivation of the programmer.

To develop the skill of Python programming using the framework of the five components, a pedagogical approach can be designed as follows:

  • Begin with teaching the fundamentals of Python, such as data types, variables, control structures, and functions, through a combination of lectures, reading materials, and online resources.
  • Introduce more advanced concepts, such as object-oriented programming, error handling, and file I/O, as students progress.
  • Teach students about commonly used Python libraries and their applications in various domains.
  • Assign small projects or exercises at the end of each topic to reinforce learning.
  • Encourage students to practise problem-solving using Python by assigning coding challenges and puzzles that require critical thinking and decision-making.
  • Provide opportunities for peer programming, where students collaborate and exchange ideas to solve problems.
  • Organise regular code review sessions to help students learn from each other’s solutions and improve their problem-solving strategies.
  • Set clear expectations and learning goals for students to motivate them to learn and practice Python programming.
  • Offer regular feedback and support throughout the learning process to help students stay engaged and committed.
  • Encourage students to participate in coding competitions, hackathons, or open-source projects to build their confidence in Python programming.
  • Foster a supportive learning environment in which students can openly discuss their challenges and successes in Python programming.
  • Encourage students to work in teams for some projects, which will help them develop shared (and hopefully positive) emotional experiences.
  • Provide opportunities for mentorship or tutoring, where more experienced students can assist their peers in learning Python programming.

Although sensory-motor abilities are not directly relevant to Python programming, promoting healthy computer use habits can indirectly support skill use.

  • Teach students about ergonomics and the importance of regular breaks to prevent strain and fatigue while working on a computer.
  • Encourage students to engage in physical activities or exercises to maintain overall well-being, which can have a positive impact on their cognitive abilities.

By incorporating these strategies in a Python programming course or training program, learners can develop the required skills while addressing all components of the pedagogical framework.

  • (C) Example 3: Logical analysis

For the skill “logical analysis”, which is ambiguously considered as a soft skill or a hard skill depending on the situation, we describe below on a scale of importance of 1 to 5 for each component, the composition for each component (see Figure 4 ):

  • Knowledge: 4/5—Logical analysis requires a solid foundation of knowledge about the subject matter being analysed. This includes understanding key concepts, principles, and relationships within the domain. For example, analysing a scientific argument requires knowledge of the relevant scientific facts and theories. However, the ability to apply logic and reasoning is also essential, so knowledge alone is not enough for logical analysis.
  • Active cognition: 5/5—Active cognition is crucial in logical analysis, as it involves the ability to perceive and process information, identify patterns and relationships, and evaluate the validity of arguments. This includes skills such as critical thinking, problem-solving, and decision-making. Active cognition allows individuals to analyse situations, evaluate evidence, and form sound judgments based on logical reasoning.
  • Conation: 2/5—Whereas motivation and the willingness to engage in logical analysis are necessary, conation also plays a supporting role through perseverance and perfectionism, which ensures that individuals are committed to the process of logical analysis and persist in their efforts to reach accurate conclusions.
  • Affection: 1/5—Affection, as defined by empathy and emotional management, is not a central component of logical analysis. Logical analysis focuses primarily on rational thinking and objective evaluation of evidence, rather than emotional connections and relationships. However, having a certain level of emotional intelligence can help individuals avoid potential biases and maintain objectivity in the analysis.
  • Sensory motor abilities: 1/5—Sensory motor abilities are not directly relevant to the skill of logical analysis, as logical analysis is a cognitive process that does not rely on physical movement or sensory input. Although sensory-motor abilities may be necessary for other skills, they do not play a significant role in logical analysis.

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Visual representation of the generic skills’ components framework for the skill “Logical analysis”.

It is interesting to observe that using the framework, it appears that active cognition and knowledge seem to be the most important components for the skill of logical analysis. Knowledge is commonly associated with hard skills, whereas active cognition is commonly associated with soft skills. The dominance of these two components could explain why it seems complicated to categorise logical analysis as a soft or hard skill. This example shows the value of such skills that cannot be consensually categorised.

To develop the skill of logical analysis using the framework based on the five components, a pedagogical approach can be designed as follows:

  • Begin by teaching the basic logical concepts, such as premises, conclusions, and logical fallacies.
  • Teach various types of logical arguments and structures (e.g., deductive, inductive, and abductive reasoning).
  • Provide examples and case studies to illustrate different logical principles and argumentation styles.
  • Engage students in debates or discussions to practise identifying and evaluating arguments.
  • Provide exercises that require students to identify logical fallacies or errors in reasoning.
  • Engage reflection and self-assessment to help students recognise their own biases and assumptions.
  • Set clear goals and expectations for students’ progress in developing logical analysis skills.
  • Provide regular feedback and encouragement to help students stay committed and motivated.
  • Create opportunities for students to collaborate and share their learning experiences with peers.
  • Teach students how to present their logical analyses effectively and persuasively, while considering the perspectives and emotions of their audience.
  • Encourage empathy and active listening during debates and discussions to foster a more open and collaborative learning environment.
  • Present information and materials in a clear, visually appealing manner to facilitate understanding.
  • Encourage students to take notes or create visual representations (such as diagrams or flowcharts) to help organise and process information.

By addressing each component of the generic framework, this pedagogical approach provides a comprehensive and structured method for developing logical analysis skills in students.

4. Limitations and Opportunities

Skills have traditionally been defined as a set of competencies or abilities that an individual has, such as problem-solving, analytical thinking, and communication. However, this definition is problematic because it treats skills as discrete entities; this fails to account for the influence of contextual factors on how skills are used in practice. For example, a skill such as communication may be used differently in diverse contexts, with different levels of success. Further, there may be no such thing as a completely “generic” skill—one that functions equally well in all contexts. In short, the idea of skills as abstract entities is a misleading oversimplification.

The definition of skills as abstract entities has a wide range of implications. It ignores the role of context in how skills are applied, which in turn can lead to an over-emphasis on the individual’s capabilities and an under-emphasis on environmental conditions ( Widdowson 1998 ). This can lead to a focus on individual differences instead of a collective approach; this in turn can lead to a narrow focus on the individual and an inability to identify external influences on skill use. Further, it can lead to a teleological approach ( González Galli et al. 2020 ), whereby skills are thought to be automatically “transmitted” to the context in which they will be used, without regard to the idiosyncrasies of that context. Finally, it can lead to a focus on skills as an end in themselves, instead of collectively as part of a much larger system.

A systems-based perspective goes beyond the traditional concept of skills as abstract entities and instead focuses on the way in which skills develop within specific contexts, thus treating them not as static entities, but as part of an interactive, evolving system. Through this perspective, the influence of context on skill use is fully acknowledged, with multiple factors—such as culture, power dynamics, and social norms—being taken into account. Therefore, this approach enables the concept of skills to be seen as part of a larger system of behaviour and learning, which is essential to understanding how skills can be effectively developed, practised, and utilised.

Indeed, the scientific literature has challenged the definition of skills as abstract entities and instead advocated for a systems-based approach that acknowledges the role of context in how skills are applied ( Tracey et al. 1995 ; Le Boterf 2000 ; Sih et al. 2019 ). However, if skills did not exist, then only knowledge would matter a priori.

Knowledge alone does not lead to successful interactions with others; skill plays an integral role in the development of successful social behaviours ( Boyle et al. 2017 ; Rios et al. 2020 ). Further, this research indicates that even if a person has a great deal of knowledge, it is not enough to produce the desired results unless they can put the knowledge into practice. Skills need to exist in order to allow professionals, educators, and clinicians to work on isolated and specific constructs, even if variable and not perfect as such. In our contribution, we see the generic components approach as a way to redefine the concept of skill, by embedding environmental factors in cognitive, conative, and affective dimensions.

Although our generic skill framework provides the basis for further developments, it is important to note that other approaches may need to be considered to provide a more comprehensive understanding of the concept of skill in various contexts.

5. Conclusions

This article has explored the definitions, categories, and impact of both hard and soft skills in order to gain an understanding of the generic composition of any skill. It found that both must be viewed as complementary elements comprising a successful performance and that hard skills are objective and quantifiable capabilities that are easily measured, whereas soft skills are non-technical, interpersonal, and visual qualities that are often learned through experience. Although the two types of skills are often classified separately, understanding their interdependence can help create a more comprehensive skill set. Strategic thinking and action, skills that cut across both soft and hard skills, are essential for making effective decisions.

Research on skills reveals that hard and soft skills often overlap, with various components being shared between them. As such, there is a need to recognise the different components of any skill to develop individuals efficiently and effectively. The generic components proposed in this article open the way to discuss the common ground between hard skills and soft skills, and more broadly the generic composition of any skill. More research is needed to refine the approach on this topic, but it seems a greater understanding of the generic composition of skills can help inform professional, educational, and clinical practices.

Funding Statement

This research received no external funding.

Author Contributions

The authors were responsible for all aspects of the study, including research, writing and editorial work. Both authors contributed to the conceptualization. The first author drafted the paper. Both authors contributed to the revisions of text. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest or any other ethical considerations with respect to this study.

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National Soft Skills Association

To promote and enhance programs that increase soft skills

Study: Boosting Soft Skills Is Better Than Raising Test Scores

By National Soft Skills Association 149 Comments

soft skills research paper

A recent study was just released by Northwestern University’s Kirabo Jackson on the effect of soft skills vs test scores. This study demonstrates that schools that build social-emotional qualities are getting better short-term and long-term results for students than schools that only focus on improving test scores.

This study included 150,000 high school students in all 133 Chicago Public Schools from 2008 onward, and reported that schools putting soft skills ahead of test scores produced students with higher grades, fewer absences and fewer disciplinary problems and arrests in high school. The students who attended these high schools also graduated and went to college at higher rates .

Another focus of the study was on two problematic behaviors—attendance and disciplinary incidents with ninth graders from 2011-2017. The results showed that schools emphasizing soft skills over test scores had fewer absences as well as disciplinary incidents. For students who entered ninth grade between 2011-2014, researchers found that students who attended schools focusing on soft skills had fewer arrests during their high school years and graduated in higher numbers.

Jackson says, “You could actually do a lot more good by focusing on schools that promote social-emotional development as opposed to focusing on schools that focus on test scores.”

In February of 2020, Jackson presented the findings at a conference for the National Center for the Analysis of Longitudinal Data in Educational Research (CALDER). There are four co-authors from The University of Chicago Consortium on School Research, Northwestern University and Mindset Scholars Network.

The Value of Soft Skills in the Labor Market

By National Soft Skills Association 29 Comments

soft skills research paper

Economists are increasingly focused on the importance of so-called “soft skills” for labor market success. The evidence is overwhelming that these skills — also called “non-cognitive skills” — are important drivers of success in school and in adult life. Yet the very term soft skills reveals our lack of understanding of what these skills are, how to measure them, and whether and how they can be developed. And the term “non-cognitive” is simply used to mean “not predicted by IQ or achievement tests.”

Read the full article:

Why Soft Skills Are so Difficult to Teach

By National Soft Skills Association 21 Comments

A lot has happened in the field of soft skills over the last few years. Awareness of the need for employees to possess soft skills such as attitude, communication, critical thinking, and professionalism, to name a few, has begun to reach a fevered pitch. High school career and technology education (CTE) programs as well as post-secondary institutions have identified the need to offer training in soft skills. Many programs have taken the approach of trying to integrate soft skills training with hard skills training. On the surface, integrating the two sounds like a good idea, however I wonder what the results of such training will provide. The reason for my doubt is that just teaching the concepts of soft skills is not good enough, you have to go deeper.

The Foundation Blocks of Soft Skills

There are hidden skills or competencies that are needed as the as foundation blocks upon which soft skills can be taught. These necessary building blocks are known as emotional intelligence or EQ. EQ is a learned ability to identify, explain, understand and express human emotions in healthy and productive ways. Without these foundation blocks, a learner’s ability to understand and to use soft skills is very limited.

Here is how this works:

soft skills research paper

In education, the targeted skill being taught is soft skills. The next step is to identify the soft skills competencies that need to be taught. Simple, right? What is missing are the foundation blocks that the soft skills competencies are built upon. Those foundation blocks are EQ competencies.

The foundation blocks of Interpersonal Skills

soft skills research paper

Interpersonal skills are actually social skills and cover how to interact with other people and present oneself in an acceptable manner. It includes such topics as interpersonal skills, controlling your emotions, socializing at work, networking, responding to conflict and helping customers.

The core EQ foundation skills needed in order to develop these interpersonal skills are self-esteem, interpersonal awareness, empathy and supportive environment.

• Self-esteem is how positively you view yourself. It is a perceived level of personal worth and is the most important EQ competency of them all for developing positive relationships. Contrary to what the current experts say about self-esteem (they think it does not exist), it is a key competency in interpersonal relationships, for it dictates how people might feel about themselves in social situations. If people feel good about themselves, they also demonstrate positive feelings about the others around them.

• Interpersonal awareness first starts with intrapersonal awareness or awareness of self. Once people become aware of themselves they can then become aware of others. Awareness of others also requires a good understanding how others might be responding to them. Many people on the autism spectrum struggle with this concept.

• Empathy is the cornerstone of EQ. Empathy covers how to sense, understand, and accept another person’s thoughts, feelings and behaviors. Empathy is a primary characteristic of skilled communicators and a key aspect in interpersonal or social skills.

• Supportive environment is the extent to which friends, family or peers have impact on an individual’s achievement and how they can positively encourage people in achieving their personal goals and improving relationships.

As you can see here, there is a lot more to the soft skill of interpersonal skills than meets the eye. Remember you cannot teach soft skill competencies while ignoring the underlying necessary EQ competencies.

The NOT So Surprising Thing that Google Learned about Its Employees – And What It Means for Today’s Students

By National Soft Skills Association 35 Comments

soft skills research paper

  In an article in today’s Washington Post written by Valerie Strauss, The surprising thing Google learned about its employees –and what it means for today’s students , the Post explains what Google learned about its employees through their own research on hiring, firing, and promotion data accumulated since the company’s founding in 1998.  This results of this research project, called Project Oxygen, shocked everyone by concluding that among the eight most important qualities of Google’s top employees, STEM skills came in dead last.

The other seven qualities were all soft skills and include:

  • Being a good coach
  • Communication skills
  • Possessing insights into others and different values and points of view
  • Empathy toward one’s colleagues
  • Critical thinking
  • Problem solving
  • Drawing conclusions (making connections across complex ideas)

While this is a very excellent insight and very important to recognize, it is not new to us at the National Soft Skills Association.  Let me quote an article we posted on August 3, 2017.

“It has been 100 years since the Carnegie Foundation for the Advancement of Teaching released a study on engineering education authored by Charles Riborg Mann. In his study, 1,500 engineers replied to a questionnaire about what they believed to be the most important factors in determining probable success or failure as an engineer. Overwhelmingly, personal qualities were considered seven times more important than knowledge of engineering science.

soft skills research paper

A second circular letter stating Mann’s results was sent to 30,000 members of four large engineering societies, and each member was asked to number the six qualities needed for top engineers. The top six qualities were:

  • Understanding of others

Notice that the top four are soft skills while only the last two were hard skills?

Education Has Not Changed

A quick study on curriculum used in high schools, community colleges, colleges and universities across this country reveals that nothing has changed in 100 years. Educational institutions simply ignore the research on soft skills along with the requests of their local employers. They continue to teach the technical knowledge and skill sets for an occupation but leave out the soft skills assessment and training that are critical to success in any occupation.

soft skills research paper

After working in this industry for over forty years, I have come up with the conclusion that soft skills are not taught because there is an assumption that students already have these skills, even when employer advisory panels tell them that their graduates do not.

Bad Assumptions Lead to Bad Results

In most situations, educational institutions assume that their students posses these skills, learning them either from their families or other life experiences. This may have had some validity in the past, but if parents or other adults do not possess soft skills, how can they teach them to others? This incorrect assumption leads to costly errors in the hiring process. I don’t have to go into the cost of a mis-hire. It is sufficient to say that, when a student leaves a college, enters the working world, and does not even know enough to show up on time every day, the cost to the employers is in the tens of thousands of dollars, to say nothing of the cost to the self-confidence of the employee.

Check the Standards

I once asked a good friend of mine who worked for a state Department of Public Instruction if he could give me the standards for freshmen algebra. After several weeks of searching, he came back to me and was embarrassed to say that there were no standards other than seat time. Since then, there has been a push to create state and national education standards for academics. A quick check on those reveals that there are still no standards for soft skills.

soft skills research paper

It was established back in 1918 by Mann’s study on engineering education that approximately 80 percent of success is due to soft skills while 20 percent is due to hard skills.

I ask a simple question—W hy has this fact been ignored by the educational establishment for 100 years?”

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The science behind soft skills: Do’s and Don’ts for early career researchers and beyond. A review paper from the EU-CardioRNA COST Action CA17129

Shubhra Acharya Roles: Investigation, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Mihai Bogdan Preda Roles: Investigation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Ioanna Papatheodorou Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Dimitra Palioura Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Panagiota Giardoglou Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Vasiliki Tsata Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Sanja Erceg Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Teodora Barbalata Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Soumaya Ben-Aicha Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Fabiana Martino Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Laura Nicastro Roles: Investigation, Writing – Original Draft Preparation, Writing – Review & Editing Antigone Lazou Roles: Conceptualization, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Dimitris Beis Roles: Conceptualization, Investigation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Fabio Martelli Roles: Conceptualization, Funding Acquisition, Investigation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Miron Sopic Roles: Conceptualization, Investigation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Costanza Emanueli Roles: Conceptualization, Funding Acquisition, Investigation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Dimitris Kardassis Roles: Conceptualization, Funding Acquisition, Investigation, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Yvan Devaux Roles: Conceptualization, Funding Acquisition, Project Administration, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

soft skills research paper

This article is included in the Research on Research gateway.

soft skills research paper

This article is included in the Horizon 2020 gateway.

soft skills research paper

This article is included in the COST Actions gateway.

Soft skills are the elementary management, personal, and interpersonal abilities that are vital for an individual to be efficient at workplace or in their personal life. Each work place requires different set of soft skills. Thus, in addition to scientific/technical skills that are easier to access within a short time frame, several key soft skills are essential for the success of a researcher in today’s international work environment. In this paper, the trainees and trainers of the EU-CardioRNA COST Action CA17129 training school on soft skills present basic and advanced soft skills for early career researchers. Here, we particularly emphasize on the importance of transferable and presentation skills, ethics, literature reading and reviewing, research protocol and grant writing, networking, and career opportunities for researchers. All these skills are vital but are often overlooked by some scholars. We also provide tips to ace in aforementioned skills that are crucial in a day-to-day life of early and late career researchers in academia and industry.

Soft skills, early career researcher, research ethics, publication writing, career opportunities, academia, industry.

Revised Amendments from Version 1

The revised version of the manuscript, entails the addition of Leadership in the list of soft skills in Figure 1. Further, the concept of systems thinking, digital and green skills for sustainable research and innovation is included as transferable skills for ECRs. Many researchers may face problems in gaining the soft skills needed in the field, hence a new section on challenges and obstacles faced by the researchers and ways to overcome these obstacles in gaining these critical soft skills has been included in the revised version.

See the authors' detailed response to the review by Sandra Alexandra Catherine Buttigieg See the authors' detailed response to the review by Marialuisa Villani


The United Nations Educational, Scientific and Cultural Organization (UNESCO), and the Organization for Economic Co-operation and Development (OECD) have recently launched recommendations to help today's students to adapt to the changes, challenges, opportunities, and risks of the twenty-first century digital era 1 , 2 . The investments in the education of the human resource require targeted research and trainings in the essential skills for the new technologies and for the open science concept and practices. One of the first challenges in the Open Science framework is to ensure that the mentors are able to provide all the trainings they think are relevant for the trainees in a sustainable way in order to improve the quality, efficiency, and responsiveness of research. This involves, undoubtedly, the harmonious combination of ‘hard’ and ‘soft’ skills that the early career researchers (ECR) need to acquire in order to thrive in this rapidly changing world ( Figure 1 ).

Figure 1. The interrelation of the two distinct sets of “hard” and “soft” skills required for the 21st-century ECR.

‘Hard’ technical skills are easier to learn rapidly but are no longer sufficient for an ECR to withstand in this highly competitive global work environment, and the ‘soft’ social skills, like teamwork and communication, become of paramount importance 3 . The new generation of ECRs need to be equipped with skills and expertise relevant to workforce participation for decades to come, but unfortunately the unique ‘soft’ skills are currently underexamined in research and undersupplied through education 4 . Thus, in this position paper, the members of the EU-CardioRNA COST Action CA17129 network 5 provide practical guidance about some of the most valuable traits and soft skills young researchers should cultivate to succeed in the labour market.

The views expressed in this article are those of the authors. Publication in Open Research Europe does not imply endorsement of the European Commission.

Transferable skills

In order to establish and maintain a successful career in research, ECRs need to be equipped with multiple, interdisciplinary assets that can be applied to more than one instance; these skills are named transferable skills. In this first section, we underline the major and most valuable transferable skills, and discuss how young scientists should develop them as part of a successful path in research ( Figure 2 ). Firstly, since researchers regularly encounter simple or complex problems that require rigorous troubleshooting, they should be able to seek the most appropriate solution based on both their critical thinking and their creativity, in order to deal with the different situations effectively. Critical thinking and effective troubleshooting are also what employers and principal investigators seek for in an ECR. It is also a great asset for employers to incorporate in their groups people that possess analytical skills, meaning people who are able to collect and interpret new information fast and efficiently, analyse it thoroughly and develop effective strategies to approach and salvage any mishap. Intertwined with critical thinking is systems thinking, which involves analyzing complex problems by considering how the different parts of the problem are interconnected and interdependent on each other. By considering all aspects of the problem, systems thinking helps to identify the challenges of implementing and using the innovation. Importantly, working in research requires vigorous multitasking, which consumes time, energy, and great physical and mental labour. Gaining hands-on experience in handling multiple assignments is a smart way in order to manage a more effective allocation of time and it eventually maximizes one’s productivity. However, to avoid mistakes that often appear with multitasking, it is vital to establish an effective time management and organization plan.

Figure 2. Transferable skills for researchers.

Effective time management is a fairly remarkable transferable skill for ECRs. In addition, being able to set realistic goals and completing them in a certain amount of time is vital for meeting the designated deadlines and requires good organizational skills, especially for time-sensitive tasks. Thus, smart prioritization for personal tasks is key but also the time management and overall performance of all the members of a research group should be well-orchestrated to maintain the high-quality work of the team. For that reason, being as productive as one can be in a research group equals to acting as a team player and ECRs need to develop this skill over time. Working in different environments, for example as part of mobility programs, taking on tasks that challenge you to work with different people, that expand your limits, and that get you out of your comfort zone are all very effective ways to learn how to support others in terms of lab work but also to rely on them if need be. It should be noted that teamwork and collaboration skills are usually a prerequisite in job descriptions. Showing true dedication and having a strong sense of responsibility over any collaboration and task are equally important qualities of reliable team members 6 . However, being persevering, dedicated, and persistent are also intertwined with being able to adapt to any circumstance and overcome any problem, while also maintaining the motivation and momentum to move forward. Thus, the skill to planning/goal setting and forward thinking at the right time of the career is another important aspect for a researcher. The above skills can move an ECR forward and establish a very successful career. Finally, since leading a research group independently is the goal of many ECRs, acquiring strong leadership skills should be an active process of learning from the very early stages in one’s career. Attending leadership courses and taking an active role in training schools or workshops provides young scientists the opportunity to learn and actively practise. Successful leaders are a source of inspiration and motivation for their team members, even under tough situations, while they have the ability to set appropriate goals and foresee problems. Overall, acquiring and developing transferable skills is vital not only during the very first steps of an ECR, but it should be a continuous process throughout one’s career in research.

Preparing for an interview

While the first part of obtaining a position is the evaluation of the candidate’s application, interview performance is the next determinant of the decisive assessment of the applicant 7 . Interviewing is a critical step to successfully obtain a position in both academia and industry. In essence, it is a communication procedure that serves the purpose of exchanging information which will help the employer evaluate the candidate but also concurrently, it will give the opportunity to the employee to access to the critical information on the job position. Therefore, acquiring certain interview skills is essential in order to be effective throughout the selection process. Here, we display critical features for a fruitful interview that can be divided in three instants: before, during, and after the interview ( Figure 3 ) 8 – 10 .

Figure 3. Features for a fruitful interview.

Before the interview: It is highly important to invest time on gathering and reviewing all the information regarding both the job position and the perspective research group or company/team. In case of academia, this could include the main field of scientific interest, detailed list of publications and hosting facilities of the institute/university, whereas in case of industrial position that might include innovations/achievements of the working group and expertise of the specific private sector. Secondly, it is essential for the candidates to be prepared regarding possible conversation topics and how they should address the potential interview questions. On that note, creating a list of previous job experience including challenges and achievements the candidate has faced and rehearsing all the aforementioned issues could strengthen the responses and build the confidence of the interviewee.

During the interview: On the day of the interview, punctuality is highly appreciated. The candidate should reach the location of the meeting slightly before the scheduled time considering the required transportation time along with possible unforeseen factors. Most interviewers aim to seek for skills, motivation, enthusiasm, and professionalism on the job candidate. Therefore, attending the interview with an appropriate attire, positive posture and voice-tone will gain a great first impression. Communication skills (verbal and nonverbal) are vital for the success of an interview. During the interview, the candidate must respond to the questions clearly and concisely as well as listen attentively. Undoubtedly, confidence and use of professional language are important components with significant impact on the general interview performance. Finally, the interviewee should have prepared a list of questions to ask regarding the position (research line/project), the work environment, and policy while avoiding inquiries of salary/vacation as first question.

After the interview: As the interview is completed, the candidate could thank the interviewer for the chance to attend, show genuinely interest in the position, and kindly ask to be informed about the outcome of the discussion. This could be either the interviewers deciding on a candidate or to be followed by a further step of a second interview. In case of rejection, the interviewee may request feedback in order to improve the interview performance in future cases.

Good scientific practices- a key to perform ethical research

In the previous chapter, we described a toolbox that could assist ECRs in landing their dream job for the interview. What ensures, though, that the job is done right? From human stem cells and organoid research to animal experimentation and clinical trials, biomedical research involves a wide range of ethical concerns that confront scientists with moral decisions 11 .

To create a framework in which animal research is performed in humane conditions, Russell and Burch introduced the principles of the 3Rs (Replacement, Reduction, and Refinement), that should already be considered, when designing any experimental protocol involving animals. These aim to i) replace animals used for scientific reasons with other alternatives, ii) reduce their number to the minimum required to obtain reproducible results, and iii) ensure the animals’ welfare throughout its life and the duration of the scientific procedure by minimizing pain and/or suffering 12 . More recently, the ARRIVE guidelines have come to complement the 3Rs in order to ensure that publications describing animal research are reported in enough detail to add to the knowledge base 13 . In this regard, the United Nations has proposed Sustainable Development Goals (SDGs; ). Following the SDGs, it is essential for the researchers to focus on both digital and green skills which could help in the use of technology to manage and solve problems and to reduce the environmental impact of research activities ensuring the sustainability of health systems.

Similarly, to reflect and address the complicated ethical issues that arise with scientific and technological advances in the fields of 1) genome editing, 2) embryo culture, embryo models and gametogenesis research, and 3) organoid and chimera research, the International Society for Stem Cell Research regularly updates its guidelines 14 . These guidelines set up specific standards not only for scientists and clinicians treating patients, but also for policymakers, funders, and potential recipients of any treatments that result from it. They define clear and external boundaries ensuring that biomedical research is conducted and communicated with ethical integrity.

Biomedical research is being transformed through the use of high-throughput genome sequencing of humans using big data approaches that may lead to personalized / precision medicine. While our knowledge of what our genomic data means deepens by the day, lots of variants are still uncharacterized and have unknown significance. Several ethical issues should be addressed when dealing with releasing human genomic data. These include, for example, family members of patients with genetic predisposition to a disease, life insurance policies, and informed consent policies concerning patients 15 , 16 . To ensure proper collection, handling and release of such information, the European Union (EU) has enforced the General Data Protection Regulation (GDPR), a privacy and security law that sets a strict framework onto organizations collecting data related to people in the EU and protects the right to privacy for every individual 17 .

It should be noted that ethics is not limited to issues that are generally supervised by ethics committees for human and animal studies. Correctly performed, recorded, and communicated science is also intrinsically ethical 18 . Effort has been put in recent years to highlight the importance of good data handling, management, and presentation to promote transparency in all scientific studies, irrespective of the field or the sample size. According to the FAIR Principles, data should be findable, accessible, interoperable, and reusable (FAIR), putting specific emphasis on enhancing the ability of machines to automatically find and use acquired data, in addition to supporting its reuse by individuals 19 . Focus should be also given during data reporting and especially on choosing the correct type of graphic (i.e., dot, box, and/or violin plot) to accurately present the data depending on the study design, the sample size, and the type of variable, allowing a direct evaluation of individual data points, their distribution, and their statistical analysis to display the data as they are 20 . Another more technical aspect to be taken into account is image data processing as image manipulation can in some cases be classified as scientific misconduct. In cell biology, images often serve as primary data and for the microscopy field “seeing is believing” as stated by Prof. Alison North in her publication 21 . However, digital manipulation can be done very easily nowadays and it can be difficult to find the ethical lines of what is and what is not allowed in digital manipulation of the scientific raw data. Imaging processing workflows have been introduced that allow authors to present images effectively and ethically while publishing truthful and legible images 22 , 23 . Images and their containing elements should be properly annotated and scaled, while colors should be chosen wisely, allowing people with color vision deficiencies to efficiently distinguish them (for example: red–green color blindness is the most common form of color vision deficiency) 24 . Furthermore, image manipulations such as i) non-linear color, brightness, and contrast adjustments, ii) cropping, re-sizing, and selective enhancements of specific parts, and iii) cloning of objects in an image in which they did not previously exist are considered a misconduct and should be avoided or clearly stated 25 , 26 .

Finally, in an era of immense scientific output, researchers -but also publishing groups- should be actively trained in original writing, avoiding plagiarism -in all of its forms 27 , building a strong, ethical science culture and keeping literature and academia honest.

Scientific communication - Oral and presentation skills

Along with performing good research, ECRs must know how to disseminate their research to benefit a wider audience. Scientific conferences are one of most common ways for ECRs to communicate their work and to gain wider exposure. These are events that bring together researchers of similar interests, encouraging them to discuss and exchange views on topics from specific areas. The oral presentations represent the main focus of conferences, but the ones that provide the most opportunities for interaction, and therefore networking, are posters. The oral presentations are mostly reserved for more experienced researchers, while posters are attended mainly by younger researchers. Both of them have their own advantages 28 . Thus, for maximizing an ECR’s exposure to conferences, there are several written and unwritten rules that could be followed.

1. Selection of appropriate conferences - To meet learning and networking needs, it is important to choose the appropriate conference, whether it is local, national, or international 28 . The conference topic should be evaluated first as well as potential conference participants 28 – 30 . Once the conference has been selected, the next step would be submitting an abstract. If the abstract is accepted, it will be included in the conference proceedings that allow conference participants to read it beforehand. Only selected abstracts will be designated for oral presentations, while the rest will be transformed into poster presentations 28 .

2. Know your stakeholders- Special attention should be paid to whom a researcher will present their work 28 – 30 . It is not the same if there are researchers of similar interests in the audience or if there are people with only marginal interests. For example, if scientists in a related field are addressed, then the focus will be on the methodology part, and if there are clinicians in the audience, the focus will be on connecting a particular discovery with a diagnosis, prevention, and treatment of a disease. So, it should be kept in mind what are the expectations of the audience and how the researcher’s presentation can bring them benefits 29 .

3. Keep calm- Nervousness is always present before and during a presentation of any kind. The way to fight it is to be well-prepared. As a part of the preparation, a speaker should practice in front of their colleagues, who are familiar enough with the work and thus can make useful corrections. The anxiety is on the highest level at the beginning of a presentation, and as it progresses, a speaker becomes more relaxed, taking care mostly of the remaining time 29 . During lectures, notes may be useful, but they should be in some form of bullet points, not long paragraphs 28 , 30 .

4. Time limits- Whether it is an oral or a poster presentation, speakers must consider the time they have available 29 , 30 . Oral presentations usually last 10–20 minutes, sometimes up to an hour. Occasionally the questions at the end are counted within the given time, so it is important to consider those as well. It is advisable to prepare a complete presentation within the duration of 80 percent of the given time. At the event, the presentation time is extended mainly due to the numerous pauses that are unconsciously taken while waiting for the reaction of the audience 29 . Exceeding the available time is considered very unprofessional because it disrupts the busy schedule of the conference, and also distracts the audience who needs a lot of concentration to follow all the sessions during the day 29 , 30 . Posters are also time-limited. In moderated poster sessions, each presenter has three minutes on average to explain the basic concept of their work and then answer the delegates’ questions. There is definitely not enough time for the presenter to explain the complete research, as well as for the viewers to absolutely understand the topic. The emphasis should be on opening the door for possible cooperation in the future 28 .

5. Make it interactive- Both oral and poster presentations must be accompanied by appropriate visual material. It allows the speaker to follow the story, and the audience to concentrate, because listening without accompanying visual material is quite challenging. If the necessary equipment is available and functional, and visual material is prepared in advance, the presenter does not have to think about it during their speech 28 , 29 . Table 1 presents the general rules for presentation design, both for oral and poster presentations, as well as what should be avoided 28 – 30 .

6. Dress code- Although scientific conferences do not require participants to follow a specific dress code, there are some unwritten rules that should be kept in mind when it comes to dressing. It is important to be relaxed enough in the clothes that are worn, but more formal is better than less formal. In that manner, the audience feels respected. The way the presenter is dressed up can greatly affect their professional image 29 .

Table 1. General rules for presentation design for early career researchers.

On the other hand, there are things that cannot be predicted and influenced, but it is important to be aware of them. It may happen that the projector does not work for some reason, that the microphone is turned off suddenly, that the laser pointer does not work because the battery is low, and many more. In these cases, the speaker should remain calm and relaxed enough to find an alternative solution, for example, to speak louder or to point directly at the screen 29 . Being confident and well prepared is the key to a good presentation.

Literature reading and reviewing articles

Literature reading.

Literature reviewing is a necessary and important activity in the academic life of an ECR. It is very likely one will need to include a literature review during their research career either for a long report, a dissertation, or a PhD thesis. However, the flood of scientific papers available today might paradoxically prevent finding relevant literature and stop new ideas from appearing. There is a high burden to find and choose right papers and learn about a particular field 31 . For this concern, choosing journals that publish ‘good’ science, meaning systematic, rigorous, and reproducible research is imperative. On the other hand, one needs to be open-minded and not only track the credentials linked to reputable scientific journals and top scientists.

In this section, we focus on the difficulties that an ECR may experience in following the literature and offer instructions to perform this exciting scientific activity. Firstly, a comprehensive understanding of a scientific paper requires more than one reading, making it an effort of several hours. Generally, one should start reading the title and the abstract, followed by the conclusions. This helps in understanding if the goal of the described work is of interest for one’s own study. In the first comprehensive reading, the focus should be on getting general overview of the aims and methods. Then, the focus must be directed on the details of the methodology, results, and interpretation. Following, we list some tips for critical assessment of a scientific article:

1. Keep an open mind to the findings outlined in the article.

2. Read and summarize each article noting its main findings and impressions.

3. Examine each article for the strengths and weaknesses related to credibility and authenticity or appropriate standards.

4. Try to extract the unique central ideas of the article.

5. Look for points of difference between articles.

Literature reviewing

With the advancement of career and increased experience in the field, different journals might contact the researcher to serve as a peer reviewer for a potential article. This can be important as it shows that other researchers in the field recognize one’s expertise. a, such as MDPI, Elsevier, or Wiley 32 – 34 . Unfortunately, the skill of reviewing a paper is something that is rarely taught during one’s graduate degree program, so many ECRs are left feeling ill equipped in this area 35 . In this section, we discuss the main aspects that should be considered when reviewing a scientific paper. Since the peer-review method of a potential scientific paper is the way to ensure that the respective paper is accurate and in its full potential, its importance cannot be stressed enough 36 . Following points must be taken in account while reviewing a paper:

1. Does the paper fall within the scope of the journal or the special issue? The editor, who also checks if the manuscript follows the structure guidelines of the journal, usually takes this decision. After editors decision, the manuscript is forwarded to reviewers, who have expertise in the respective research field 35 .

2. The overall coherence of paper must be taken into account. The aim of the study and how well the obtained results demonstrate it must be clearly mentioned.

3. The abstract must accurately summarize the main aim, methods and findings of the study. A graphical abstract could be used to visually describe the same.

4. The methods section should have sufficient details for other researchers to reproduce the experiments if needed. Another aspect regarding methodology is data processing; a clear description of informatics tools can highly enhance the quality of a paper.

5. In the results section, authors should not re-mention the details already found in tables or figures, rather highlight the trend and significance of these data. The figures and graphs in the manuscript, with appropriate title and legend, are the ones that tell the story of the paper and attract the reader. Thus, adequate representation of the results to fit the data profile is extremely important. The figure legends should be self-explanatory, containing a suggestive title, the sample size, methodology used, and the full terms alongside any abbreviations.

6. The discussion section of the paper should address its findings, give them context and interpret them in relation with the existing literature, making sure that the references used fit the idea emitted by the respective paragraph. The authors should try to cite other researchers’ work before and then their own previous work to a reasonable extent. In addition, the novelty that the paper brings to the field and if it furthers current knowledge, along with study limitations should be precisely mentioned in the discussion. It must be noted that novelty might be a critical criteria for some journals, while for others it might not be as important.

7. In the conclusions section of the paper, authors should draw an inference that should be sustained by the presented results (exaggeration of the importance of the results is not advised) and speculate (but not over speculate) on possible future directions of their research work. All these steps to be followed during the review process are summarized in Figure 4 .

Figure 4. Components of a paper reviewing process.

Research protocol and grant writing.

Reading and writing are basic skills that are acquired throughout the education of a young person. Young researchers who have decided to pursue an academic path will need to develop a set of additional scientific writing skills in order to support their research activity. The three most important types of scientific writing skills are research protocol writing, scientific publication writing, and grant writing.

Writing a research protocol

In the early stages of an ECR’s career, research protocol writing is often done primarily by the supervisor or other experienced researchers from the laboratory, and so the ECR does not have to worry too much about this issue. However, from the very beginning, all ECRs must learn and practice their scientific writing skills in order to become successful scientists.

Writing a research protocol could be a difficult and time-consuming process and it is important to emphasize that protocols have different features when it comes to clinical trials or basic and translational research. A protocol for a randomized clinical trial is a framework of a clinical study, demonstrating the guidelines for conducting the trial. Any clinical trial protocol must be registered and must conform the international standard for trials protocols (SPIRIT guidelines) 37 . This topic has been well described in several review articles 38 – 40 and it will not be our focus in this chapter. Another comprehensive description of clinical trial protocols can be found in the book by Hulley et al., ‘Designing Clinical Research, 4th Edition’ 41 . In their book, Hulley et al., developed the FINER (feasible, interesting, novel, ethical, relevant) criteria that helps researchers formulate a solid research question, by highlighting useful concepts ( Figure 5 ). The FINER criteria is particularly useful for ECRs as they can be guided on how to find a good research question and how to design an efficient research protocol.

Figure 5. FINER criteria for a good research protocol.

Adapted from 41 .

In basic or in translational research, a research protocol is a detailed and well-structured plan of a project. It can be also an essential component of a research proposal submitted for funding. The plan is structured in a document that specifies the systematic details of a research study, starting from the hypothesis, rationale and background information, primary and secondary objectives, approach or methodology, data management, ethical and gender issues, and statistical analysis.

The scientific process is an activity that involves the rejection of hypotheses that are inconsistent with the experimental results. Testing a hypothesis is what we call an experiment and for a hypothesis to be not only valid but also valuable, a good and detailed research protocol is required. When writing a research protocol, following points should be addressed:

1. The project title should be as clear as possible. It should not be lengthy and should be accompanied by an acronym to be used throughout the text;

2. The project summary should define all the research objectives and the rationale so that there are no doubts that the proposed research is timely and addresses a scientifically important subject;

3. Schemes often help reviewers to understand the strategic plan;

4. The methodology should be described and justified appropriately;

5. Ethical considerations are very critical especially when dealing with humans or experimental animals; risk management and contingency plan must not be forgotten.

The most important element for a successful research proposal is the original hypothesis (or idea). Where do good research ideas come from? It is imperative for an ECR to continuously read relevant literature, actively attend meetings, discuss with colleagues, and to go back to previous data to develop new ideas.

Writing a grant

A research protocol can be a main part of a grant proposal that is submitted to funding agencies. Grants are the primary source of funding and, consequently, the engine that allows academic research to exist. Grant applications need to be carefully prepared and written in advance to allow several rounds of proof-reading and increase the chances of being financially supported. For ECRs, writing a proposal for a research grant or for a fellowship can be the first step towards scientific independence.

A grant proposal is an unambiguous, direct document written to a particular organization or funding agency to persuade the reviewers to provide you with financial support because: 1) you have a clear idea with a valuable aim that tackles an important and timely matter, and 2) you are capable of implementing that plan.

To succeed, it is vital to build grant-writing skills 42 , 43 . There are a few steps to follow in order to write a successful grant application ( Figure 6 ), including:

Figure 6. Tips to writing a successful grant application.

1. Get the timing right. While scheduling the writing time, it is important to allow enough time for rewrites, proofreads, and unforeseeable events.

2. Formulate an impactful scientific question. Having a clear scientific hypothesis is essential to succeed. The proposed idea must be novel, timely, and increasingly important to funding bodies.

3. Get advice at an early stage. This allows increasing the chances of success and formulating a clear, ambitious but realistic objective. It is recommended to seek suggestions from a range of sources.

4. Choose the right funder and scheme for your proposal. Doing extensive research of available grants and identifying different research interests, missions and priorities of funding bodies will help to increase the likelihood of funding success.

5. Get the right partners. Demonstrating having the right background to carry on the proposed project is essential. Collaborating with experts in the different research areas covered by the project will help counteract criticism during the reviewing process and expand your network.

6. Tell a compelling story with clear language. The project needs to deliver your message clearly and concisely. Obey the three Cs rule: Concise - Clear - Complete 44 .

7. Include relevant preliminary data. Showing solid preliminary data will support the credibility and feasibility of your scientific hypothesis and the proposed methodology, thus helping convince the evaluation panel.

8. A good grant structure is key. Divide your proposal into stand-alone but also interconnected sections (work packages). Use schemes to convey your message.

9. Justify your budget. Convince the reviewers that the proposed personnel and consumables will be sufficient for the described project and that no shortage of resources will be faced. On the other side, an inefficient use of the resources is equally negative, decreasing the chances to be funded.

10. Consider all ethics issues. If your project involves human subjects or animals, make sure that you have done your ethics self-assessment before submitting the proposal and familiarize yourself with all national or international regulations.

11. Mitigate the risks. Each proposal is exposed to criticism, and each study has limitations. Presenting a risk mitigation strategy within your proposal will increase the credibility of your project and yours as a research leader.

12. Get your proposal reviewed internally. Asking other people to read your proposal will improve its clarity, structure and accessibility.

13. Follow the guidelines. Each grant application comes with specific guidelines. Usually, a template is also provided. Make sure you read the guidelines before you start writing and follow them strictly.

14. Never give up on the final checks. Check and double-check punctuation, presentation and grammar. This will determine how people will perceive your work.

Despite all the points mentioned above, there is no guarantee that a grant proposal will be funded. Getting a grant is very difficult. Competition is usually stiff. However, the process of writing your project in a well-structured proposal helps to improve the hypothesis, the impact and the approach regardless of the final evaluation committee decision. Also, paying attention to reviewers’ feedback after a rejection helps strengthen future proposals, thus increasing the chances of success.

Considering the best-case scenario, the grant gets funded! However, the writing will not be over. In fact, many grants require progress reports and updates, so be prepared to keep on writing and developing your grant writing skills.

Writing a scientific publication

If funds are secured, and research work is preformed rigorously, the time comes to share the data obtained and make the research accessible for the scientific community. In order to do that it is essential to present and contextualize the results in an understandable way, following some general criteria and particular requirements (author guidelines) imposed by the chosen journal.

Choosing the right journal for your manuscript is extremely important, as it will determine the target audience and the impact of your research. Journal selection is a daunting task. It requires a careful evaluation of the aim and scope of the journal, the peer-reviewing process, the journal indexing, its network and the publishing time. Once the authors agree on the journal, the main author has to download the journal guidelines and prepare the first draft accordingly. Presenting the data in an organized and clear manner is a must. Exposing the draft to several rounds of revisions by all authors will help to improve its quality. Additionally, if important gaps are detected, further scientific work should be performed before the submission to avoid an editorial rejection. Opposite to grant writing, no strict deadline is set, but writing needs to be planned in advance in order to be efficient and not to compromise the novelty of the work performed. Once all authors are in accordance with the good quality of the research and the writing, your paper is ready for submission. In the best scenario, after passing the editorial selection, the quality of the manuscript will be assessed by peer reviewers and revisions will be requested. Regardless of the type of revisions requested (major or minor), be prepared to work hard and fast to answer the reviewers’ questions. Despite being often a stressful process, the aim of peer reviewing is to improve the quality and impact of your work and make your research more clear and accessible for the expert scientific community.

Networking as a key to success in research

Networking is part of our day-to-day lives. It helps in establishing and building new relationships in both personal and professional aspects. In this chapter, we discuss how networking can help in technical advancements, technology transfer, collaborations, career development and professional success in research 45 . It should be noted that research performed in an isolated atmosphere, is less efficient than performed in collaboration. Thus, it is imperative to know the type of networking activities researchers can and should engage into and the outputs to expect from these activities. Figure 7 shows a puzzle of networking activities and their expected outcomes.

Figure 7. Different networking activities for researchers and expected outcomes.

Networking activities.

Attendance in networking activities can help to improve communication skills and to boost career opportunities 46 . For ECRs, the most recommended way to initiate communication is by being regularly active in scientific/non-scientific discussions and presenting their research work in laboratory or in institutional meetings. Initiating a conversation and presenting one’s opinion to experienced scientists and professors might get overwhelming for some researchers. Thus, to widen the network, researchers can start with attending courses at their university or abroad- to expand the network with their peers which indirectly boosts the confidence. Further, attending scientific conferences and presenting their work to establish network with peers along with experienced scientists helps build important connections that significantly enhance the research capacities and boost research outputs. Coffee breaks and social events like dinners or excursions organised during the conferences could help in making professional as well as friendly connections 47 . The researcher must contact and connect with peers and senior scientists via email or appropriate social media tools after the meeting to stay in touch with them. The use of social media has become imperative in these times. Posting about your lab activities, new publications or simply commenting your opinion on other researchers’ post might significantly help in promoting the research work and broadening the network 48 . Taking initiative and volunteering to co-ordinate meetings is another way for ECRs to increase their network and confidence. Activities like taking part in journal clubs is also a great opportunity to widen the research horizon. In this regards, ECRs from the EU-CardioRNA COST Action CA17129 network 5 have initiated a monthly journal club that aims to catalyse scientific discussions and collaborations between ECRs and senior scientists from across the globe.

Networking outputs

Each type of networking activity will produce different outputs. To start with, regular communication and liaising with peers improves a researcher’s confidence, which is important to communicate with senior scientists. Attending courses in the university and abroad also helps a researcher to widen their perspective and get ideas to conduct inter-disciplinary research. Other activities like conferences and symposia can help in building connections that can lead to collaborations for ongoing and future projects 49 . The established connection with a person could also turn into a potential referee for future employments. Another important outcome that needs to be highlighted is successful public-private partnerships. Private companies often sponsor international conferences where they have representatives who present their recent research developments. Collaborations with these private companies can broaden the research outcomes to a translational level. This creates a high impact not only to the researcher’s personal profile but also makes a synergistic effect in improving the need of novel therapies for improved healthcare 50 .

One important aspect when it comes to participating in networking activities is funding. Several government and private agencies financially support these networking activities, helping researchers, especially ECRs, to attend scientific meetings with the final goal to boost their research outcome. One such example is the European COST Association (European Cooperation in Science and Technology; ) funded by the Horizon Europe research and innovation framework programme. COST supports the so-called “Actions” which are networks of scientists and key stakeholders aiming to engage into networking activities (meetings, short-term scientific missions, conference grants and so on) towards the satisfaction of an innovative and unmet research topic, while contributing to catalyse collaborations between scientists and boost the career of young researchers. The European Union's flagship programme ‘Marie Skłodowska-Curie Actions’ is another example of funding schemes aiming to support scientific excellence and cooperation across countries, sectors and research fields, particularly adapted for ECRs 51 . Likewise, several similar funding bodies in different countries support grants for networking to promote transfer of technology for inter-disciplinary research and to promote inter-institutional and public-private collaborations.

Career development in academic and/or private sector

The ‘publish or perish’ philosophy together with the constant technological advancements puts a lot of pressure on the ECR community. Keeping up the pace in order to build up a successful career in the academic sector seems very challenging 52 . Thus, it is of great importance for an ECR to carefully plan their roadmap to a successful academic career. During the course of the Ph.D. thesis, researchers should acquire all the technical skills that are state-of-the-art in the field, and improve critical thinking, problem-solving, and scientific writing skills. Equally important, during this period researchers should start to build international liaisons that will be exploited in the later stages of their careers for post-doctoral studies, collaborations, and international projects. With the ever-growing need for an interdisciplinary approach in research, it is essential to establish good connections with reliable and competent peers and work together on the realization of new ideas and concepts 53 . This is even more relevant for researchers coming from developing countries 54 . After finishing a Ph.D., the researcher should have a clear idea about the next career steps. The researcher interested in a traditional academic career (tenure positions at faculty, research positions at institutes), should proceed with a post-doctoral program, preferably outside the university where the Ph.D. thesis was obtained. By going abroad, the researcher gains more international recognition, expands their cultural horizon, and acquires social skills, thus gaining qualities that will be useful for becoming an independent researcher and eventually a team leader. The criteria for the choice of post-doctoral position should not only be related to the level of excellence of the research facilities, but should also include an assessment of the working environment and if it is stimulating and encouraging enough for the development of the independent researcher 55 . Considering that after a post-doctoral period, the researcher should be a fully competent group leader, in addition to research skills, it is important to take time during the post-doctoral period to master grant writing skills, management, and leadership skills. By fostering good research practice, international collaborations, and project leading, there is no doubt that the researcher will have a successful academic career.

According to Denton et al., around 80 percent of US ECRs (postdocs) in life sciences are employed in academic sector, whilst the rest are working in governmental institutions, industry, or non-profit organizations 56 . However, the opportunities for researchers to leave academia and work in the private sector as employees or entrepreneurs have significantly increased in the past decade. Large funds are being designated for the development of technology and innovation parks that are seen as crucial ecosystems where innovations can thrive 57 . The scientific achievements produced in universities are being exploited through creation of spin-off or start-up companies. This, in fact, became one of the most widespread approaches to commercializing scientific discoveries 58 . Thus, scholars nowadays should gain experience in the private sector through internship programs, and learn about the commercialization of research, technology transfer steps, technology readiness levels, intellectual property, and patents ( Figure 8 ). By doing so, academics can bridge the gaps between the academic and non-academic sectors, and open doors to new career opportunities.

Figure 8. Opportunities for carrier development of ECRs.

Figure created in BioRender.

Obstacles in acquiring soft skills

The standards and competition in today’s research environment are continuously increasing. Even though the aforementioned soft skills significantly contribute to the advancement of an ECR’s career, they might not be sufficient for career progress due to various external factors. Structural disparities, such as, ethnicity, gender, disabilities, health conditions, and institutional barriers, can notably impede an ECR's acquisition of transferable skills during their research journey 59 . Women and other marginalized gender identities, people with disability and minority ethnic groups experience with numerous disadvantages. Gender disparities in research can rise from implicit biases and added need for work-life balance among women, resulting in fewer opportunities. ECRs dealing with disabilities or chronic health conditions may face challenges in managing their workloads and may encounter difficulties in accessing the necessary resources and support to develop these transferable skills. For instance, people with disabilities are 30 percent less likely to enter professional roles compared to those without disabilities 60 . Additionally, students from low-income countries traveling to explore an international and developed research environment may face problems due to financial constraints, language barriers, cultural differences and visa restrictions that hinder their ability to pursue an advanced research career. These inequalities significantly affect ECRs' productivity during their professional development and their ability to establish research networks.

Therefore, besides supporting emerging scholars in gaining transferable skills, it is imperative to firstly recognize and then address the structural imbalances some ECRs face. This can be partially achieved by researchers themselves supporting peers who face disadvantages. Additionally, established scientists can make a significant difference by providing development opportunities and overseeing research practices at the institutional level. Creating an inclusive and welcoming environment while providing mentorship and offering options of professional development can help students from marginalized groups to overcome these obstacles and thrive in their careers.

Conclusions and key messages

The life of an ECR is made of successes and failures. Even though sometimes failures can be more frequent than successes, the most important thing to remember is to keep going and to not feel discouraged. Soft skills and the helpful suggestions provided in this article should help ECRs as well as other more advanced researchers to build their niche in the highly competitive research arena. Writing a scientific publication is an essential step in a researcher’s life and sometimes it takes several rounds of revision before a paper is accepted. However, for sure these revisions will highly improve the quality of the paper. Grant applications take an increasing amount of time as long as the ECR becomes an established researcher. Even though most prestigious grant schemes have very low success rates, close to 10 percent or below in some cases, never give up! Only the most hard-worker and galvanized applicants will succeed and will be rewarded by the satisfaction of having won a high-level competition. Keep the eyes widely open, share ideas and findings with colleagues, talk to peoples with complementary expertise, be part of research networks, be proactive, multitask, and forget about your shyness. These are key soft skills that will help ECRs achieve a successful and enjoyable research career.

Data availability

No data are associated with this article.


This article is based upon work from EU-CardioRNA COST Action CA17129 ( ) funded by COST (European Cooperation in Science and Technology).

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Reviewer Expertise: Sociology of Education, Education Policies, Higher Education Studies

  • Author Response 24 Nov 2023 Yvan Devaux , Cardiovascular Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, 1445, Luxembourg 24 Nov 2023 Author Response Reviewer 2 comments : The paper provides an extensive exploration of topics related to the career development of Early Career Researchers (ECRs) and how soft skills can contribute to their professional ... Continue reading Reviewer 2 comments : The paper provides an extensive exploration of topics related to the career development of Early Career Researchers (ECRs) and how soft skills can contribute to their professional growth. The authors offer comprehensive insights into various research-related tasks, such as conducting literature reviews and following research protocols in the science field. However, the paper predominantly portrays the transfer of soft skills as a linear process and briefly acknowledges the challenges that the educational environment may pose. While they acknowledge the importance of a strong trainer-trainee relationship at the outset, they do not delve into potential critical aspects of skills transfer. In the open letter, the authors imply a linear progression from the acquisition of soft skills to the success of ECRs. Nevertheless, they fail to consider factors such as gender, disabilities, health, and nationality, which can significantly impact the acquisition of transferable skills during PhD or Post-Doc programs. These inequalities also affect ECRs' productivity during their career development and their ability to establish research networks. The paper only briefly touches on the influence of available funding on networking and the open science publication process. As it stands, the paper places the onus of ECR success or underperformance squarely on the individual trainee. However, within sociological literature, including education and work studies (e.g., Bourdieu 1984, Bozzon et al. 2018, Crew T.), scholars have emphasized the role of structural inequalities related to gender, disabilities, ethnic origin, and health conditions. While I appreciate the recommendations put forth by the EUCardioRNA COST Action CA17129, if they aim to provide meaningful and practical guidance for students seeking to pursue a Ph.D. program and a research career, it is essential to comprehensively address all aspects of an academic career path. This should encompass not only recognizing the importance of acquiring soft skills but also acknowledging the influence of structural inequalities and their impact on the journey of ECRs. Answer: We thank this reviewer for her comments and fully agree with her recommendations. We have addressed the raised points in the updated version of the manuscript by including a chapter as follows.  “ Obstacles in acquiring soft skills The standards and competition in today’s research environment are continuously increasing. Even though the aforementioned soft skills significantly contribute to the advancement of an ECR’s career, they might not be sufficient for career progress due to various external factors. Structural disparities, such as, ethnicity, gender, disabilities, health conditions, and institutional barriers, can notably impede an ECR's acquisition of transferable skills during their research journey 59 . Women and other marginalized gender identities, people with disability and minority ethnic groups experience with numerous disadvantages. Gender disparities in research can rise from implicit biases and added need for work-life balance among women, resulting in fewer opportunities. ECRs dealing with disabilities or chronic health conditions may face challenges in managing their workloads and may encounter difficulties in accessing the necessary resources and support to develop these transferable skills. For instance, people with disabilities are 30 percent less likely to enter professional roles compared to those without disabilities 60 . Additionally, students from low-income countries traveling to explore an international and developed research environment may face problems due to financial constraints, language barriers, cultural differences and visa restrictions that hinder their ability to pursue an advanced research career. These inequalities significantly affect ECRs' productivity during their professional development and their ability to establish research networks. Therefore, besides supporting emerging scholars in gaining transferable skills, it is imperative to firstly recognize and then address the structural imbalances some ECRs face. This can be partially achieved by researchers themselves supporting peers who face disadvantages. Additionally, established scientists can make a significant difference by providing development opportunities and overseeing research practices at the institutional level. Creating an inclusive and welcoming environment while providing mentorship and offering options of professional development can help students from marginalized groups to overcome these obstacles and thrive in their careers.” Reviewer 2 comments : The paper provides an extensive exploration of topics related to the career development of Early Career Researchers (ECRs) and how soft skills can contribute to their professional growth. The authors offer comprehensive insights into various research-related tasks, such as conducting literature reviews and following research protocols in the science field. However, the paper predominantly portrays the transfer of soft skills as a linear process and briefly acknowledges the challenges that the educational environment may pose. While they acknowledge the importance of a strong trainer-trainee relationship at the outset, they do not delve into potential critical aspects of skills transfer. In the open letter, the authors imply a linear progression from the acquisition of soft skills to the success of ECRs. Nevertheless, they fail to consider factors such as gender, disabilities, health, and nationality, which can significantly impact the acquisition of transferable skills during PhD or Post-Doc programs. These inequalities also affect ECRs' productivity during their career development and their ability to establish research networks. The paper only briefly touches on the influence of available funding on networking and the open science publication process. As it stands, the paper places the onus of ECR success or underperformance squarely on the individual trainee. However, within sociological literature, including education and work studies (e.g., Bourdieu 1984, Bozzon et al. 2018, Crew T.), scholars have emphasized the role of structural inequalities related to gender, disabilities, ethnic origin, and health conditions. While I appreciate the recommendations put forth by the EUCardioRNA COST Action CA17129, if they aim to provide meaningful and practical guidance for students seeking to pursue a Ph.D. program and a research career, it is essential to comprehensively address all aspects of an academic career path. This should encompass not only recognizing the importance of acquiring soft skills but also acknowledging the influence of structural inequalities and their impact on the journey of ECRs. Answer: We thank this reviewer for her comments and fully agree with her recommendations. We have addressed the raised points in the updated version of the manuscript by including a chapter as follows.  “ Obstacles in acquiring soft skills The standards and competition in today’s research environment are continuously increasing. Even though the aforementioned soft skills significantly contribute to the advancement of an ECR’s career, they might not be sufficient for career progress due to various external factors. Structural disparities, such as, ethnicity, gender, disabilities, health conditions, and institutional barriers, can notably impede an ECR's acquisition of transferable skills during their research journey 59 . Women and other marginalized gender identities, people with disability and minority ethnic groups experience with numerous disadvantages. Gender disparities in research can rise from implicit biases and added need for work-life balance among women, resulting in fewer opportunities. ECRs dealing with disabilities or chronic health conditions may face challenges in managing their workloads and may encounter difficulties in accessing the necessary resources and support to develop these transferable skills. For instance, people with disabilities are 30 percent less likely to enter professional roles compared to those without disabilities 60 . Additionally, students from low-income countries traveling to explore an international and developed research environment may face problems due to financial constraints, language barriers, cultural differences and visa restrictions that hinder their ability to pursue an advanced research career. These inequalities significantly affect ECRs' productivity during their professional development and their ability to establish research networks. Therefore, besides supporting emerging scholars in gaining transferable skills, it is imperative to firstly recognize and then address the structural imbalances some ECRs face. This can be partially achieved by researchers themselves supporting peers who face disadvantages. Additionally, established scientists can make a significant difference by providing development opportunities and overseeing research practices at the institutional level. Creating an inclusive and welcoming environment while providing mentorship and offering options of professional development can help students from marginalized groups to overcome these obstacles and thrive in their careers.” Competing Interests: No competing interests were disclosed. Close Report a concern Reply -->
  • Respond or Comment
  • Leadership should be in the list of soft skills in Figure 1. it is mentioned sparingly, albeit illustrated in Figure 2 together with adaptability as transferable skills. An ECS should have the vision in terms of the strategic positioning/purpose of research so as to achieve maximum impact and implementation. The pandemic has shown us the importance of compassionate, agile, adaptive and distributed/collaborative leadership. Leadership is an important process that could make or break a team of researchers. There is ample research on destructive toxic leadership in particular in highly competitive environments.  
  • Systems thinking: as part of patient safety and risk management, ECRs should be able to understand the principles of systems thinking that helps in identifying challenges with impact, implementation, and adoption of innovation.   
  • In line with UN's SDGs, a great deal of attention is being given to both digital and green skills that ensure sustainability of health systems. In particular, the importance of circular economy and its 3R's reduce, reuse and recycle should be important skills to acquire.

Reviewer Expertise: Clinical performance and quality assurance in healthcare; Patient safety and clinical risk management; Organisational behavior, SHRM, SHRD; Research methods; Operations management/research (length of stay, readmissions, delayed discharges); Health policy issues (ageism, migrant health, One Health); Information technology in health care management

  • Leadership should be in the list of soft skills in Figure 1. it is mentioned sparingly, albeit illustrated in Figure 2 together with adaptability as transferable skills. An ECS should have the vision in terms of the strategic positioning/purpose of research so as to achieve maximum impact and implementation. The pandemic has shown us the importance of compassionate, agile, adaptive and distributed/collaborative leadership. Leadership is an important process that could make or break a team of researchers. There is ample research on destructive toxic leadership in particular in highly competitive environments.
  • Systems thinking: as part of patient safety and risk management, ECRs should be able to understand the principles of systems thinking that helps in identifying challenges with impact, implementation, and adoption of innovation.
  • In line with UN's SDGs, a great deal of attention is being given to both digital and green skills that ensure sustainability of health systems. In particular, the importance of circular economy and its 3R's reduce, reuse and recycle should be important skills to acquire.

Reviewer Status

Alongside their report, reviewers assign a status to the article:

Reviewer Reports

  • Sandra Alexandra Catherine Buttigieg , University of Malta, Msida, Malta; Mater Dei Hospital, Buenos Aires, Argentina
  • Marialuisa Villani , Universita degli Studi di Bologna, Bologna, Italy

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