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Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students


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Soft skills are important for any career and are necessary to access and face the labor market. This research focuses on soft skills by exploring engineer profiles. It also determines how soft skills are developed through the study of a representative sample of 314 undergraduate engineering students from 15 different Italian universities. The instrument used is a questionnaire that investigates soft skills and is based on the Business-focused Inventory of Personality (BIP). Answers are grouped into four areas: intrapersonal, interpersonal, activity development, and impression management. Results show that these engineers have more self-confidence than the reference sample; they demonstrated a great commitment in setting job goals and pursuing projects, a good emotional adaptation to social situations, and enough attitudes in terms of problem solving and openness to change. Perception on the ability to work under pressure is in the average, and they seem ready to take on challenging tasks. The score shows that engineers from the sample are able to express positive and negative ideas and feelings in balance with the reference average, but sometimes they have difficulties in establishing personal relationships. Therefore, they are unable to understand the moods of those who around them and may also have difficulty in understanding their expectations. This results in some difficulties in teamwork. The general result underlines the opportunity of empowerment programs regarding soft skills.
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Research Article / Education
Soft Skills in Engineers, a Relevant Field of Research:
Exploring and Assessing Skills in Italian Engineering
Habilidades transversales en ingeniería, un ámbito de investigación
relevante: Explorando y evaluando habilidades en estudiantes de
ingeniería italianos
Valeria Caggiano 1, Teresa Redomero-Echeverría 2, Jose Luis Poza-Lujan 3, and Andrea Bellezza 4
Soft skills are important for any career and are necessary to access and face the labor market. This research focuses on soft skills by
exploring engineer profiles. It also determines how soft skills are developed through the study of a representative sample of 314
undergraduate engineering students from 15 different Italian universities. The instrument used is a questionnaire that investigates
soft skills and is based on the Business-focused Inventory of Personality (BIP). Answers are grouped into four areas: intrapersonal,
interpersonal, activity development, and impression management. Results show that these engineers have more self-confidence
than the reference sample; they demonstrated a great commitment in setting job goals and pursuing projects, a good emotional
adaptation to social situations, and enough attitudes in terms of problem solving and openness to change. Perception on the ability to
work under pressure is in the average, and they seem ready to take on challenging tasks. The score shows that engineers from the
sample are able to express positive and negative ideas and feelings in balance with the reference average, but sometimes they have
difficulties in establishing personal relationships. Therefore, they are unable to understand the moods of those who around them
and may also have difficulty in understanding their expectations. This results in some difficulties in teamwork. The general result
underlines the opportunity of empowerment programs regarding soft skills.
Keywords: soft skills, engineer, BIP, curriculum, university
Las habilidades transversales son importantes para cualquier carrera y son necesarias para acceder y afrontar el mercado laboral. Esta
investigación se enfoca en el tema de las habilidades transversales explorando los perfiles de los ingenieros. También determina cómo
se desarrollan las habilidades sociales a través del estudio de una muestra representativa de 314 estudiantes de ingeniería de 15
universidades italianas diferentes. El instrumento utilizado es un cuestionario que investiga las habilidades interpersonales basado en
el Business-focused Inventory of Personality (BIP). Las respuestas se agrupan en cuatro áreas: intrapersonal, interpersonal, desarrollo
de la actividad y gestión de la impresión. Los resultados muestran que estos ingenieros tienen más confianza en mismos que la
muestra de referencia; demostraron un gran compromiso en establecer metas laborales y seguir proyectos, una buena adaptación
emocional a las situaciones sociales y actitudes suficientes en términos de solución de problemas y apertura al cambio. La percepción
sobre la capacidad de trabajar bajo presión se encuentra en el promedio, y ellos parecen dispuestos a asumir tareas desafiantes. El
puntaje muestra que los ingenieros de la muestra son capaces de expresar ideas y sentimientos positivos y negativos en equilibrio
con el promedio de referencia, pero a veces tienen dificultades para establecer relaciones personales. Como resultado, no pueden
comprender los estados de ánimo de quienes los rodean y pueden tener dificultades para comprender sus expectativas. Esto resulta
en algunas dificultades para el trabajo en equipo. El resultado general subraya la oportunidad de un programa de empoderamiento en
habilidades transversales.
Palabras clave: habilidades transversales, ingeniería, BIP, currículum, universidad
Received: November 26th, 2019
Accepted: June 23rd, 2020
1Ph.D., University Roma TRE, Department of Education, Via del Castro Pretorio
20, Rome, Italy. Affiliation: Professor Work Psychology and Organization.
2Ph.D., University Roma TRE, Department of Education. Via del Castro Pretorio
20, Rome, Italy. Affiliation: Researcher. E-mail:
3Ph.D. Universitat Polit`
ecnica de Val`
encia, School of Informatics iSchool,
Automation and Industrial Computing Research Institute, Camino de vera, sn
46022 Valencia (Spain). Camino de Vera, s/n Valencia, Spain. Affiliation: Full time
lecturer. E-mail:
4Ph.D. University Roma TRE, Department of Education, Via del Castro Pretorio 20,
Rome, Italy. Affiliation: Researcher. E-mail:
How to cite: Caggiano V., Redomero-Echeverría, T., Poza-Lujan, J. L., and
Belleza, A. (2020). Soft Skills in Engineers, a Relevant Field of Research:
Exploring and Assessing Skills in Italian Engineering Students. Ingenier´
ıa e
Investigación,40(2), 81-91. 10.15446/ing.investig.v40n2.83717
Attribution 4.0 International (CC BY 4.0) Share - Adapt
Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students
Currently, soft skills are receiving attention from different
age groups alongside occupational education programs to
better equip people for their future careers. Nevertheless,
introducing such concepts in a fitting way is an important
challenge in higher education. There are a lot of definitions
regarding soft skills. In general, education programs focused
on soft skills have the goal to make or reduce the number
of unemployed graduates and to efficiently match graduates
with companies, not only in technical matters, but also
in the aspects related to company values. According to
“The Research Agenda for the New Discipline of Engineering
Education” (Borrego and Bernhard, 2011) the skills that future
engineers must master in the classroom and develop during
their professional practice are mainly soft skills. These are
transferable behaviors that can be used in different contexts
of life, specifically in highly competitive work scenarios
(Schleutker, Caggiano, Coluzzi and Poza-Lujan, 2019). They
are absolutely necessary to access the labor market, and
they have become more crucial to acquire in engineering
professional contexts, together with hard and technical skills
(King, 2012; Gemar, Negrón-González, Lozano-Piedrahita,
Guzmán-Parra and Rosado, 2019). Today’s engineering
graduates have a plenty of technical knowledge, but mostly
lack the social skills required by current job settings, such
as leadership, communication and teamwork. One of
the crucial areas of research in engineering education is
focused on designing higher education engineering courses
to predispose competent, autonomous, and decision-making
future engineers (Itani and Srour, 2016) in order to respond
to labor market demands for highly qualified professionals.
Engineering has focused mainly on its technical aspects.
This is because engineering is more isolated from human
relations than other disciplines. In these disciplines, the
result is the most important thing, and focusing on personal
matters is not necessary to obtain successful results (Barrera,
Duarte, Sarmiento and Soto, 2015). However, currently, the
classical vision of an engineer working alone, designing some
personalized product, has changed. Companies develop a
lot of projects with a lot of people involved. That means that
relations between different people in a project are one of
the pillars to achieve its goals (Brunhaver, Korte, Barley and
Sheppard, 2017). Therefore, some personal characteristics,
which we prefer to call soft skills, such as teamwork or
leadership, have started to be recognized. Traditionally, these
skills are not considered in the curriculum of engineering
programs. However, these soft skills needs are being
considered, especially since engineers perform their work in a
project-oriented environment (Henkel, Marion and Bourdeau,
2019; Ballesteros-Sánchez, Ortiz-Marcos, Rodríguez-Rivero
and Juan-Ruiz, 2017). In emerging fields of engineering,
such as Information and Communication Technologies (ICT),
the study of soft skills is one of the future trends (Matturro,
Raschetti and Fontán, 2019).
These aspects raise some interesting questions: what soft
skills are necessary in engineering? Can soft skills be learned?
To answer these questions, it is necessary to know the current
state of soft skills in engineering, in other words, what are the
most common soft skills in engineers, and if these soft skills
depend on age or gender. The research presented in this
paper is focused on determining the most relevant soft skills
that engineers have in order to answer these questions, as
well as whether there are differences between the soft skills
that engineers possess and the average of other university
students. If there are, probably the syllabus of the degrees and
masters engineering curriculum must consider incorporating
them as part of their training. It is important to know these
soft skills since they are are necessary to design university
programs based on competencies (Tulgan, 2015).
Defining soft skills
There is a significant parallelism between system components:
hardware (hard skills) and software (soft skills). Without
hardware, software does not work, and without software,
hardware cannot be used efficiently. From a business point
of view, engineers need soft skills to obtain benefits from
their hard skills (Robles, 2012). Previous researchers noted
that many graduated engineers have good technical skills
(or hard skills) but not enough soft skills. That is, there is
an insufficiency of skills related to employability and moral
values, communication and leadership, confidence level, and
ability to adapt in the workplace (Beckton, 2009; Elsen,
Jaginowski anf Kleinert, 2005; Leroux and Lafleur, 2006;
McIntosh, 2008).
Empirical researches confirm that, nowadays, employers
are hunting for workers who have good technical skills but
have additional skills such as communication, interpersonal,
teamwork, problem-solving, thinking, and technology skills,
as well as continuous learning and a positive work ethic
(Raybould and Sheedy, 2005). Soft skills, as generic skills,
have become a main factor that is needed by employers, and
graduates must consider this to start any career (Hinchliffe
and Jolly, 2011; McQuick and Lindsay, 2005). This was
demonstrated when many unemployed graduates stated
that they needed additional training programs to improve
soft skills as well as lifelong learning skills, team building,
career development, interpersonal skills, and the especially
necessary entrepreneurial skills (Fabregá, Alarcon and Galiana,
2016; Pineteh, 2012).
Soft skills are among the skills that are necessary to improve
the performance of self-employment graduates in relation
to international needs. The increase in the total number of
unemployed graduates is one of the subjects that arises, due to
the lack of proficienct soft skills (Redomero, Caggiano, Poza-
Luján, and Piccione, 2019). For this reason, it is necessary to
deepen and develop this subject.
European university curriculum
Currently, continuous change in the socioeconomic
environment demands highly skilled graduates from
universities (Possa, 2006; Sleezer, Gularte, Waldner and
Cook, 2004; Weil, 1999). Consequently, it is necessary to
match companies’ skills needs with the skills provided by
universities in order to increase the quality of the alumni
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(Elias and Purcell, 2004; Teichler, 2003). Following the
Bologna Declaration on June 19, 1999, titled The European
Higher Education Area, and given their importance in the
development of a knowledge-based economy, European
universities are required to produce graduates who are able
to respond to the ever-changing workplace requirements
(Andrews and Higson, 2008). This has resulted in questions
about the ability of graduates to meet the needs of employers
(Caggiano, Schleutker, Petrone and González-Bernal, 2020).
Certainly, “serious concerns have been expressed about an
increasingly wide ‘gap”’ between the skills that graduates
have and the requirements of the global work environment
(Andrews and Higson, 2009, p.1; Mocanu, Zamfir, and
Pirciog, 2014).
Curriculum development is a key educational process that
can support the innovative capacity of a higher education
institution. Thus, implementation of educational curricula
in the European universities should always be up to date
to make certain that graduates possess not only knowledge
but also mastery of soft skills (Stevenson and Bell, 2009).
Communication skills, life-long learning, entrepreneurship
skills, and moral and professional ethics are some of the
skills needed by graduates to improve their employability
(Evans, 2006; Pineteh, 2012). There are growing concerns
for graduate employability and the expansion in the size and
diversity of student populations (Fallows and Steven, 2000).
In the case of engineering students, the importance of soft
skills has been acknowledged in recent years (Bancino and
Zevalkink, 2007). Recent studies indicate the complexity
of the learning process to determine which soft skills are
necessary for engineers (Aponte, Agi, and Jordan, 2017).
Consequently, it is very important to incorporate soft skills
to the curriculum, especially in order to obtain the degree
certifications of the international agencies. In this case, such
skills are called ‘professional skills’ (Shuman, Besterfield-
Sacre, and McGourty, 2005).
The concept of competency-based curricula appears in order
to incorporate competencies into the engineering curriculum
(Lunev, Petrova, and Zaripova, 2013). This model focuses on
the learning process and is oriented towards results (Tomi
et al., 2019). This makes the model perfect for engineering
degrees. Given that soft skills are important in engineering
and that the competency-based model is very suitable for
these disciplines, it is convenient to determine which soft
skills engineers must have and develop. These competences
must be acquired by students but are also necessary in
teachers (Carvalho, Corrêa, Carvalho, Vieira, Stankowitz, and
Kolotelo, 2018).
It is also convenient to quantize the dependence on soft skills
with regarding some structural aspects. Among the various
aspects, it is possible to highlight two statistical dimensions:
age and gender. In the case of soft skills, age can be used as
a variable (Fournier and Ineson, 2014). However, experience
is not age, and it is a more accurate factor in acquiring certain
soft skills (Joseph, Ang, Chang, and Slaughter, 2010). Usually,
students do not have enough labor experience to deem this
variable significant. In the case of this study, we consider age
because the people who answered the questionnaire were
mainly last year students who became graduates during this
The perception of the need for soft skills in engineering
varies depending on the experience (Chanduví, Martín, and
De los Ríos, 2013). That is to say, when an engineer has
been working for many years, he or she knows what hard
skills are necessary, but experience also allows to determine
which ones must be developed. This is due to the fact
that experience provides knowledge about the personal
profiles that drive engineering projects to have a good result.
Regarding gender, it is obvious that engineering has an issue
to solve (Wang and Degol, 2017). It would be very important
to know if the appreciation of transversal competences is
different in terms of gender, since it could determine whether
the low percentage of women in engineering depends on
hard skills or soft skills. Knowing what competencies are
different between men and women would make it possible to
improve the actions aimed at achieving more gender equality
in engineering.
Method and tools
This research was classified as descriptive, since the general
objective was to determine the skills already developed
by graduates in engineering, in order to address the lack
according to the needs of the job market. In this sense,
we tried to identify and characterize a series of soft skills,
highlighting their qualities and characteristics. It was a
non-experimental, cross-sectional design that simultaneously
collected data, particularly during the months of April 2015
to June 2018. The research focused on a population of
undergraduates in different engineering disciplines in Italy.
Out of this population, an accidental sample was developed
through the Department of Engineering of the University
of Roma Tre, through personal contacts with a snowball
sampling, and thanks to the publication of the questionnaire
in different social networks.
The final sample used consisted of 314 people. Although it is
a small sample, it must be considered that more than 1 000
responses were received. However, only those persons who
were students and graduated within two years after taking
the survey were considered. This is because we wanted to
determine the soft skills of the graduates, but we also desired
to know the needs of the students, in order to adapt them to
the curriculum. The result was a small but qualified sample.
Likewise, the confidentiality of personal data was guaranteed,
requesting permission to treat them according to the Italian
law D’Lgs 196 of June 30, 2003. The next step in this research
was to collect data from Spanish informatics engineering
graduates. With this comparison, we proposed to extend
the study into two branches -European and South American
undergraduates and/or graduates- in order to compare the
cultural and economic influence in the development of
soft skills.
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Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students
Figure 1. Full process of experimentation carried out and presented
along with the performed.
Source: Authors
A representative sample of 314 engineering undergraduates
from 15 universities of Italy s selected. Among all respondents,
there were 221 (70,38%) male students and 93 female
students (29,62%), all aged between 19 and 24, with the
exception of a 52-year-old subject. To avoid altering the
presented age-related study, we had separate the main group
and the exception in another one. Results only considered
19 to 24 because one exception could cause a high bias
in the analysis. 49,68% of them were bachelor students
(three-year engineering program) and 50,32% were master’s
degree students (three-year engineering program). Regarding
the type of engineering, students came from Computing
and Systems Engineering (70,06%), Industrial Engineering
(28,66%), and the remaining percentage (1,7%) was divided
between different engineering branches: mechanical, civil,
environmental, electronic, management, transportation,
energy, and biomedical engineering.
Participant consent was obtained before undertaking the study.
The students volunteered and indicated their agreement to
participate in the study through a form.
They were informed that their participation was completely
voluntary and that all collected information would be anonymous
and confidential. The questionnaires were administered in the
last year of their degree to test the above-mentioned hypothesis:
whether soft skills were developed in their academic paths.
Detecting soft skills like creativity requires the use interesting
methods and specific tools (Olivares-Rodríguez, Guenaga,
and Garaizar, 2017). Questionnaires are the most frequent,
since they allow homogenizing results and are easily filled
out by students. The latter justifies their use in the studied
population (Fernández-Sanz, Villalba, Medina, and Misra,
2017). Questionnaires are easily included in methods. For
example Redoli, Mompó, De la Mata, and Doctor (2013)
present a full procedure to detect and train soft skills which
uses questionnaires in the early stages of the training. On the
other hand, to measure a concrete soft skill, concrete methods
can be used. For example, Joseph, Ang, Chang, and Slaughter
(2010) use the critical incidents methodology to measure
practical intelligence. A list of different methodological
approaches for measuring soft skills can be found in Balcar
(2014). The greater is the number of evaluated soft skills,
the more generic should the employed method be. That is
why we decided to use a questionnaire as a measuring tool
instead of other practical methods.
The questionnaire included the following sections:
Sociodemographic characteristics (gender, age and,
provenance) and studies (university and engineering type).
The next section was the Business-focused Inventory of
Personality (BIP). Engineers develop their activities mainly
in companies, so the use of BIP is justified by the
similarities between the evaluated competences and the
meta-competencies that are usually required in engineering
(Chanduví et al., 2013). Additionally, the questionnaire has
been adapted and translated for the Italian population by
Luissa Fossati and Matteo Ciancaleoni (2013).
Regarding BIP, to avoid equidistant position, a specific used
response format was chosen. The answers were arranged into
a six-point scale that varies between ‘completely true’ and
‘completely false’, between which four intermediate points
are not anchored. These questions are based on dichotomous
statements, so the respondent must choose between one
or the other pole. For example, ‘I prefer to answer emails
than to make phone calls’ can be answered in the range of
1 (‘completely false for me’) to 6 (‘completely true for me’).
In this case, the number of responses is even to avoid the
‘impartial’ effect; it is necessary to decide in one way or
The current version of the BIP is the result of an intense
revision (Fossati and Ciancaleoni, 2013). Not all the variables
in the questionnaire have been selected, in order to cover
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only the competences closest to the engineering field of
work (Allen, Reed-Rhoads, Terry, Murphy, and Stone, 2008).
The evaluated scales are grouped into three areas plus one
isolated Impression Management skill. Next, we present the
definition of these soft skills which were used and explained
to participants.
Figure 2. Areas in which the BIP questionnaire separates the soft skills
and their placement in the process of personal interactions.
Source: Authors
Intrapersonal area
Emotional stability
: It focuses on appropriate
management of emotional reactions. It concerns
the ability to react positively to stressful or difficult
situations in life.
It is the conviction or security of
being capable of doing a good job. When there is no
self-confidence, other personal skills can be ignored.
The ability to work under pressure
: It gives us the
image that the sample have of themselves regarding
the ability to perform their functions in adverse
circumstances while maintaining a constant level of
Interpersonal area
: It is assessed through assertiveness,
a social ability that allows us to express our rights,
opinions, ideas, needs, and feelings in a conscious,
clear, honest, and sincere way without harming others.
It includes the ability to convince others, persevering
in supporting one’s position.
Relationship building
: It is close to the Big Five Model
extroversion construct (McRae and Costa, 1987), but
there are differences with the present research. In
this case, it concerns the development of interpersonal
relationships and the creation of a network of contacts.
Orientation to group work
: The preference to work
in a group or individually is evaluated, as well as the
ability to integrate into work groups and the level of
performance in both contexts.
: It is the ability to interpret and understand
people’s thoughts, conduct, feelings, and concerns; to
perceive if any behavior is appropriate depending on
the social situation.
: This has similarities with the broad domain
of the Big Five Model’s Agreeableness (McRae and
Costa, 1987). It concerns the ability to interact friendly
and kindly. It deals with a basic social competence in
the processes of adaptability to new environments or
new conditions of social coexistence.
Activity development area
: It is inserted in the Conscientiousness
factor from the Big Five Model (McCrae and Costa,
1985). However, in the present case, we mean the
commitment with work objectives or projects. This
dimension is also based on planning, organization, and
execution of tasks.
Openness to Change
: This scale shows an overlap
with the openness to the experience construct of the
Big Five Model (McCrae and Costa, 1985). Still,
this factor has a greater breadth in the model. In
the present research, adaptability and flexibility are
evaluated. It concerns adaptation while coping with
changing situations.
Action Orientation
: It broadly corresponds to the
construct described by Kuhl and Beckmann (1994).
It is a bipolar dimension, aimed at evaluating the
orientation to the action in opposition to the orientation
to the state. The first one favors the transformation of
intention into action, while the other is characterized
by having thoughts related to the attainment of a goal
in the mind.
Impression Management
It comprises the tendency for responses to be socially
desirable. This variable refers to the own impression about
the effect of the social interaction and has a direct relation
with important aspects such as motivation and ethical point
of view (Brockmann, Clarke, Méhaut, and Winch, 2009).
Data analysis
Data was collected through Google Forms, through a payment
account for the project. This account allowed to obtain
progressive copies of all the changes and guaranteed the
integrity and full availability of the data. Access to data could
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Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students
only be done by researchers. Given that the study did not
collect private data that enabled the recognition of people, it
was not allowed to alter the response of the participants. The
data processing was carried out through the exporting a CSV
file. A data audit was performed to verify that the analysis
program had not altered the original data.
SPSS (IBM Corp., 2015) was used for all analyses. Descriptive
statistics for individual item scores of the soft skills
competency level were analyzed to establish a general profile
of the engineering students’ self-assessment qualification
patterns. The BIP is a questionnaire that refers to statistical
rules. In other words, it defines the level of each characteristic
detected in the examined subject by comparing it to the raw
score. The normative scores are expressed as stanine points
on a scale that has an average of 5,5 and a standard deviation
of 2. In order to compare results, we used the results from
the whole study performed by authors as a reference group.
These groups included students from different degrees and
different Italian universities. The reference group consisted of
undergraduates from different degrees: 314 from engineering,
174 from education and 683 from different sciences degrees
(Chemistry, Biology, Mathematics and so on). Regarding
gender, 48,3% were women and 51,7% men. The age average
was 21,3 years old. The characteristics of the reference group
were close to the characteristics of the applied questionnaire.
The average of these groups, including other degrees, were
the values used as a reference group in the soft skills level
analysis. This group was used to compare the results of
concrete subsets. For example, in Redomero et al. (2019),
only education and engineer degrees were compared.
Then, a psychometric validation was performed for the item
set. The reliability analysis of the questionnaire was carried
out with the sample of engineers by using Cronbach’s internal
consistency method. This coefficient allows to verify that the
items measured the same variable on a Likert-type scale and
were highly correlated. It varies in value from 0 to 1: the
higher the score, the more reliable the scale will be.
The comparison between means of different groups (age,
gender) was carried out through independent samples T-
test, checking first if the variances were similar through the
Levene contrast test. Both Mann-Whitney U and Kolmogorov-
Smirnov non-parametric tests were performed to compare
two different and unpaired groups of two-variable data. These
methods compute P values that test the null hypothesis that
the two compared groups have the same distribution. For all
tests, a significance value of 5% was accepted (p <0,05).
Soft skills level in engineering students
In the first phase of the research, the first deep analysis
was performed on a sample of 100 subjects, but only 88
questionnaires were considered valid. The fee costs and time
invested in carrying out a complete test is very high. For this
reason, a first sample was chosen to determine which soft
skills should be analyzed in more detail. This research was
intended to verify that soft skills were below the reference
group average of the questionnaire. In this case, with a
representative sample of 88 subjects, with scores above the
average and with the knowledge that, by shortening the test,
more subjects would be reached. Table 1 shows the high
scored soft skills in engineering students.
Table 1. Soft Skills with high scores obtained by engineering students
Soft Skill N Mean Standard deviation
1. Emotional stability 88 6,204 2,029
2. Self-confidence 88 6,375 1,883
9. Self-Control 88 6,727 1,679
10. Openness to Change 88 5,818 1,698
Source: Authors (data analysis performed by SPSS v.23).
These results suggest that engineering students have
intrapersonal and activity development skills above the level
of previous studies. As a consequence, we decided to increase
the application of the BIP questionnaire to a representative
sample of 314.
The soft skills shown in Table 1 do not change in the results.
The other soft skills included in the BIP questionnaire are
shown in Table 2. The results observed in it show that the
scores on all the variables of the interpersonal skills area are
below the average with respect to the reference group in
which the mean was 5,750.
Table 2. Soft Skills results in the Interpersonal area and corresponding
stanines of the whole group of students
Soft Skill N Mean Standard deviation
3. Ability to work under pressure 314 5,675 1,614
4. Communication 314 5,675 1,614
5. Relationship building 314 3,427 0,888
6. Orientation to group work 314 3,306 1,034
7. Sensitivity 314 3,854 1,068
8. Sociability 314 4,789 1,571
11. Action Orientation 314 4,153 1,022
Source: Authors (data analysis performed by SPSS v.23).
The result is really interesting, since it indicates a lack in
the development of soft skills in personal relationships
for teamwork. This lack implies that the engineering
curriculum should include training in teamwork or learning
methodologies such as team-project-based learning, through
which these soft skills can be developed. In order to anticipate
this aspect, the questionnaire included another important
question: whether the respondent was willing to be an
active researcher by participating in the training project for
the development of these skills. 62,1% showed interest
by responding positively to the proposal to participate in
a Soft Skills Training Laboratory. This aspect implies that
undergraduates know their needs.
Reliability evidence
The study of the internal consistency (CI) of the BIP scales
with the engineers’ samples was measured by calculating
Cronbach’s alpha coefficient. As can be seen in the
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Table 3, the reliability of the scales is very good in self-
control, relationship building, orientation to teamwork,
communication, emotional stability, ability to work under
pressure, and self-confidence. The scales with moderate
reliability are openness to change, sociability, sensitivity, and
impression management. The action orientation scale has an
unacceptable reliability.
Table 3. Reliability evidence of soft skill scales
Soft Skill 𝜶Number of items
1. Emotional stability 0,840 13
2. Self-confidence 0,810 12
3. Ability to work under pressure 0,750 13
4. Communication 0,740 11
5. Relationship building 0,840 15
6. Orientation to group work 0,870 13
7. Sensitivity 0,700 11
8. Sociability 0,510 11
9. Self-control 0,750 14
10. Openness to Change 0,690 10
11. Action Orientation 0,320 14
12. Impression Management 0,540 5
Source: Authors (data analysis performed by SPSS v.23).
Soft kills relation with gender and age
The age of the respondents was between 19 and 52 years,
with a mean age of 25,04 years being the standard deviation
of 3,83. It grouped the age of the sample participants from
19 to 25 and from 26 to 54 years in order to facilitate the
subsequent statistical analysis of this variable with the other
variables included in the study.
The Levene test for the difference in means between each of
the variables observed and the gender is not significant in
any case. T-Student was used with parametric variables, and,
although it is true that there is some small difference, there
were no significant differences between men and women.
With non-parametric variables, two independent samples
have been used: Mann-Whitney U (U-MW) and Kolmogorov-
Smirnov (K-S).
Table 4. T-test for difference between means and Mann-Whitney U/
Kolmogorov Smirnov tests in gender in the intrapersonal area
Soft Skill Levene T p
1. Emotional stability 0,535 -1,380 0,169
2. Self-confidence 0,719 - 0,126 0,900
3. Ability to work under pressure 0,157 0,577 0,564
Source: Authors (data analysis performed by SPSS v.23).
In the intrapersonal area, there are no significant differences
in gender (Table 4) or age (Table 5). The ‘p’ associated
with the statistical T is greater than the prefixed level of
= 0,05. Results demonstrate that, in personal
engineering-related skills, both men and women are equally
prepared. This result suggests that the small number of
women in technical degrees is not related to gender. The
Table 5. T-test for difference between means and Mann-Whitney U/
Kolmogorov Smirnoff tests in age in the intrapersonal area
Soft Skill Levene T p
1. Emotional stability 0,621 -0,824 0,411
2. Self-confidence 0,167 -1,901 0,058
3. Ability to work under pressure 0,535 -1,380 0,169
Source: Authors (data analysis performed by SPSS v.23).
next analysis focused on the interpersonal area, regarding
both gender (Table 6) and age (Table 7).
Table 6. T -test for difference between means and U-Mann Whithey/
Kolmogorov Smirnoff in gender in the Interpersonal Area
Soft Skill Levene T p
4. Communication 0,011 U-MW: 0,510
K-S: 0,526
5. Relationship building 0,343 - 1,018 0,310
6. Orientation to group work 0,742 - 0,665 0,507
7. Sensitivity 0,798 0,737 0,462
8. Sociability 0,326 0,109 0,789
Source: Authors (data analysis performed by SPSS v.23).
Table 7. T-test for difference between means and Mann-Whithey U/
Kolmogorov Smirnoff tests in age in the interpersonal area
Soft Skill Levene T p
4. Communication 0,915 -1,006 0,315
5. Relationship building 0,849 -0,103 0,918
6. Orientation to group work 0,512 0,976 0,330
7. Sensitivity 0,621 -0,824 0,411
8. Sociability 0,020 U-MW: 0,625
K-S: 0,845
Source: Authors (data analysis performed by SPSS v.23).
In both cases, gender and age, there are no significant
differences between the groups in the interpersonal area,
since the ‘p’ associated with the statistical T is greater than the
prefixed level of significance
= 0,05. Although an increase in
the mean is observed as the age increases. Consequently, the
skills necessary for team interactions in current engineering
do not differ either. Finally, Tables 8 and 9 present the results
of the activity development area.
Table 8. T-test for difference between means and Mann-Whitney U/
Kolmogorov Smirnoff tests in gender in the Activity Development Area
Soft Skill Levene T p
9. Self-control 0,742 -0,665 0,507
11. Action Orientation 0,199 0,268 0,789
Source: Authors (data analysis performed by SPSS v.23).
Levene’s test is not significant in any of the performed
analyses. Consequently, the minimum differences that may
exist between the different age and gender groups are not
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Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students
Table 9. T-test for difference between means and Mann-Whitney U/
Kolmogorov Smirnoff tests in age in the activity development area
Soft Skill Levene T p
9. Self-control 0,512 0,976 0,330
11. Action Orientation 0,167 -1,901 0,058
Source: Authors (data analysis performed by SPSS v.23).
Detecting and measuring soft skills in people through
questionnaires allows researchers to access relevant
information to design syllabi adapted to the social and
economic environment. In this study, the BIP questionnaire
has been used to detect the soft skills in engineering
students. This study shows the state of soft skills in
Italian undergraduate engineering students: self-control, self-
confidence, emotional stability and openness to change are
above the average of different fields analyzed for the reference
group. These skills are mainly related to the intrapersonal and
activity development areas. Perhaps, these high scored skills
are due to engineers’ having a high demand for understanding
physical concepts not directly related to people. Skills close
to the average are the ability to work under pressure and
communication. These skills are common for degree and
master students. The skills below the average are sociability,
action orientation, sensitivity, relationship building, and
orientation to group work. These skills are only needed
in a social context. Perhaps, the perception of an engineer
working alone and using their own knowledge is a stereotype
and can force people to avoid these skills. Consequently,
it would be interesting to reinforce the social aspects of
Regarding self-control, flexibility, emotional stability, and
self-confidence, statistical data indicate scores above the
average. Thus, they were deemed to be far from one of
the main objectives of the project: to design a university
program that improves soft skills. Furthermore, the evaluated
sample is considered significant to draw conclusions from
this descriptive analysis.
It is interesting to observe how the engineers’ soft skills that
are above the means of the previous studies are the soft skills
related to the intrapersonal and activity development areas.
The results with the expanded group suggest that the soft skills
related to the interpersonal area, such as teamwork, should be
reinforced. This reinforcement can be done, either by specific
training or through teamwork-oriented methodologies in the
engineering curricula.
Engineers who participated in the research have more self-
confidence than the reference sample, which means they
rely fully on their ability to perform tasks in their field. They
are active people who are confident when they face new
challenges. Potential training in this area can be very useful.
Self-confidence is something that is not usually hard-wired in
us, and we must try to develop it. The results also show a
great commitment in setting job goals and following projects.
A good emotional adaptation to social situations is observed,
since attitudes for a good problem solving are involved. The
scores obtained for openness to change were similar to those
of the reference sample. Probably, scores close to the average
like this one are a common aspect of university students and,
consequently, graduates. There is not a clear reason for this
absence of differences between degrees. A possible cause
may be that, at the intellectual level of a university, research
provides a continuous change in the knowledge base. This
implies that the technical contents of the subjects change over
time. Therefore, in any area of knowledge, students assume
these changes and, at the end of their studies, they know
that they must be flexible and open to admit that, during
their career, they will develop in a changing and innovative
With the total sample and the rest of the variables, some
conclusions have been drawn. The perception of the ability
to work under pressure that engineers have of themselves
is in the normative average. The subjects show that they
are ready to deal with challenging tasks. This ability can be
achieved by managing stress and correctly organizing the
tasks to achieve the proposed objectives. These skills are
relevant to explain a general openness to change; students
are aware of the need to be flexible in the current job market.
An important aspect in the field of interpersonal relationships
is the ability to communicate. Assertiveness is a way to
firmly communicate one’s rights. The score shows that
the engineers of the sample are able to express positive
and negative ideas and feelings in an open, honest, and
direct way, thus finding themselves in the reference average.
The data reflects the fact that sometimes they avoid social
gatherings and have some difficulties in establishing personal
contacts, particularly with strangers. This is the result of
personal interviews with some students after obtaining the
results. It is important to highlight that the perception of
their social relationships is characterized by friendliness and
respect, although the data also shows that in conversations
it is possible that they are unable to understand the moods
of those who are facing them and, therefore, may also have
difficulty in understanding what their expectations are. From
the results, it has been interpreted that there are some
difficulties in working as a team compared to other people in
the reference sample. They feel more comfortable and show
greater efficiency by working individually and at their own
pace. Currently, there is a greater demand for group thinking
in many professional areas, which is why individuals with
an individual focus must increase their range of behaviors
in order to contribute to effective group collaboration when
necessary. The engineers involved in this research are at an
intermediate point between the two forms of orientation: to
action and to the state. The statistical data indicate similar
scores to the reference samples. The results are relevant for
the future of engineering masters and degrees and can be
used to determine the needs and adapt the syllabus for the
future of engineering students.
Orientation to action favors the transformation of intention
into action. On the other hand, orientation towards the state is
characterized by having thoughts related to the attainment of
a goal in the mind. It is important not to forget the fact that the
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sample of engineers is heterogeneous. The study represents
a relevant trend regarding the engineering curriculum degree,
an opportunity to highlight the strengths and the weaknesses
relative to implement the curriculum dedicated to engineers.
The feature they share is the engineering degree, having in
common an interest in the development of technical issues,
but there are many types of engineering and, in turn, a large
number of jobs and a wide range of functions to be performed.
The result of the research presented in the article generates
a wide set of future works. The world of soft skills is in
continuous growth. In the field of engineering, it is especially
important. Traditionally, soft skills have been associated with
the field of humanities, but their acquisition in engineering
can lead to an increase in the efficiency and the addition of
the ‘human touch’ of the resulting work.
Regarding soft skills, possible paths can be suitable for
engineering should be sought. In our research, we
have used soft skills related to the business environment,
but some soft skills start to be associated with specific
engineering fields, such as the ‘structured mind’ in the
case of industrial engineering, or ‘resilience’ in the case
of computing engineering. Matching soft skills with concrete
engineering can adapt curricula to fit with specific engineers
and companies’ needs.
Regarding syllabi in engineering, it is necessary to look for
ways to include soft skills. There is no efficient recipe.
Including soft skills contents in all subjects will increase
study hours or decrease the time dedicated to hard skills.
Using teaching methods appropriate to specific soft skills
could improve their acquisition by the students. This implies
that research should be done on how to associate teaching
methodologies with the necessary soft skills in engineering.
This aspect is also a good field of work.
Finally, the detection and evaluation of soft skills is another
issue that must be solved. Currently, for large groups,
questionnaires like the BIP used in the article are the most
efficient method. However, methods such as observation by
experts, or empirical measurement of aspects such as the
efficiency of team communication will be of great value in
order to ensure and certify the acquisition soft skills.
This work was supported by the Erasmus+ program of the
European Commission under Grant 2017-1- ES01-KA203-
038589 within project CoSki21-Core Skills for 21th-century
professionals and the research program 2020 of the Education
Department at Roma Tre University
The authors would like to thank the people who
have collaborated with the research and answered the
Allen, K., Reed-Rhoads, T., Terry, R. A., Murphy, T. J., and Stone, A.
D. (2008). Coefficient alpha: An engineer’s interpretation
of test reliability. Journal of Engineering Education. 97(1),
87-94. 10.1002/j.2168-9830.2008.tb00956.x
Andrews, J., and Higson, H. (2008). Graduate employability,‘soft
skills’ versus ‘hard’business knowledge: A European
study. Higher education in Europe, 33(4), 411-422.
Aponte, C., Agi, K., and Jordan, R. (2017). International Profile of a
Global Engineer. In 2017 7th World Engineering Education
Forum (WEEF) (pp. 470-477). Kuala Lumpur, Malaysia:
IEEE. 10.1109/WEEF.2017.8467050
Balcar, J. (2014). Soft skills and their wage returns: Overview
of empirical literature. Review of Economic Perspectives,
14(1), 3-15. 10.2478/revecp-2014-0001
Ballesteros-Sánchez, L. Ortiz-Marcos, I. Rodríguez-Rivero, R.,
and Juan-Ruiz, J. (2017). Project management training: an
integrative approach for strengthening the soft skills of
engineering students. International Journal of Engineering
Education, 33(6a), 1912-1926.
Bancino, R. and Zevalkink, C. (2007). Soft skills: The
new curriculum for hard-core technical professionals.
Techniques: Connecting Education and Careers (J1), 82(5),
Barrera, M. C., Duarte, O. G., Sarmiento, C., and Soto,
R. A. (2015). A quantitative definition of engineering
professional profiles. Ingeniería e Investigación,35(2),
89-95. 10.15446/ing.investig.v35n2.46318
Beckton, J. (2009). Educational development units: The challenge
of quality enhancement in a changing environment.
In Bell, L., Stevenson, H., and Neary, M. (Eds) The
future of higher education: Policy, pedagogy and the
student experience (pp. 57-68) New York: Continuum
International Publishing Group.
Borrego, M. and Bernhard, J. (2011). The emergence of engineer-
ing education research as an internationally connected
field of inquiry. Journal of Engineering Education,100(1),
14-47. 10.1002/j.2168-9830.2011.tb00003.x
Brockmann, M., Clarke, L., Méhaut, P., and Winch, C. (2008).
Competence-based vocational education and training
(VET): the cases of England and France in a European
perspective. Vocations and Learning,1(3), 227-244.
Brunhaver, S. R., Korte, R. F., Barley, S. R., and Sheppard,
S. D. (2017). Bridging the gaps between engineering
education and practice. In Freeman, R. B. and Salzman,
H. (Eds.) US engineering in a global economy (pp.
129-163). Chicago, IL: University of Chicago Press.
Caggiano, V., Schleutker, K., Petrone, L., and González-Bernal,
J. (2020). Towards Identifying the Soft Skills Needed in
Curricula: Finnish and Italian Students’ Self-Evaluations
Indicate Differences between Groups. Sustainability,
12(10), 4031. 0.3390/su12104031
. 40 N
. 2, A
- 2020
(81-91) 89
Soft Skills in Engineers, a Relevant Field of Research: Exploring and Assessing Skills in Italian Engineering Students
Carvalho, G. D. G., Corrêa, R. O., Carvalho, H. G.,
Vieira, A. M. D. P., Stankowitz, R. F., and Kolotelo,
J. L. G. (2018). Competencies and Performance of
Engineering Professors: Evidence from a Brazilian
Public University. Ingeniería e Investigación,38(3), 33-41.
Chanduví, G., Martín, D. A., and De los Ríos, I. (2013). Modelos
internacionales de competencias profesionales. DYNA:
ingeniería e industria, 88, 266-270. 10.6036/5269
Elias, P. and Purcell, K. (2004). Is Mass Higher Education
Working? Evidence from the Labour Market Experiences
of Recent Graduates. National Institute Economic Review,
190(1), 60-74. 10.1177/002795010419000107
Elsen, P., Jaginowski, J., and Kleinert, R.A. (2005). 2005 Skill gap
Evans, K. (2006). The rainbow concept of lifelong learning.
British Educational Research Journal, 32(3). 527-534.
Fabregá, M. B., Alarcon, J. P. A., and Galiana, J. (2016).
Competencias emprendedoras y su relación con el perfil
académico: ¿tienen los estudiantes de ingeniería más
competencias emprendedoras que los que provienen de
las ciencias sociales? DYNA: ingeniería e industria, 91(2),
134-135. 10.6036/7774
Fallows, S. and Steven, C. (2000). Building employability skills
into the higher education curriculum: a university-
wide initiative. Education and Training, 42 (2), 75-83.
Fernández-Sanz, L., Villalba, M. T., Medina, J. A., and Misra,
S. (2017). A study on the key soft skills for successful
participation of students in multinational engineering
education. International Journal of Engineering Education,
33(6B), 2061-2070.
Fossati, L., Ciancaleoni, M. (Ed.) (2013). Business-focused
Inventory of Personality (BIP) (Edizione italiana). Florence,
Italy: Hogrefe.
Fournier, S. M. and Ineson, E. M. (2014). Age, gender and
work experience as predictors of success. Education and
Training, 56(1), 59-77. 10.1108/ET-10-2012-0093
Gemar, G., Negrón-González, A. M., Lozano-Piedrahita, C. J.,
Guzmán-Parra, V. F., and Rosado, N. (2019). Procedure
for the continuous improvement of human resource
management. Ingeniería e Investigación,39(1), 53-62.
Henkel, T. G., Marion Jr, J. W., and Bourdeau, D. T. (2019). Project
Manager Leadership Behavior: Task-Oriented Versus
Relationship-Oriented. Journal of Leadership Education,
18(2), 1-15. 10.12806/V18/I2/R8
Hinchliffe, G.W. and Jolly, A. (2011). Graduate identity and
employability [electronic version]. British Educational
Research Journal, 37(4), 563-584.
IBM Corp. (2015). IBM SPSS Statistics for Windows, Version 23.0.
Armonk, NY: IBM Corp.
Itani, M. and Srour, I. (2016). Engineering students’ perceptions
of soft skills, industry expectations and career aspirations.
Journal of Professional Issues in Engineering Education
and Practice,142(1), 04015005. 10.1061/(ASCE)EI.1943-
Joseph, D., Ang, S., Chang, R. H., and Slaughter, S. A. (2010).
Practical intelligence in IT: assessing soft skills of IT
professionals. Communications of the ACM,53(2), 149-
154. 10.1145/1646353.1646391
King, C. J. (2012). Restructuring Engineering Education. Journal
of Engineering Education, 101(1), 1-5. 10.1002/j.2168-
King, Z. (2003). New or Traditional Careers? A Study
of UK Graduates’ Preferences. Human Resource
Management Journal, 13(1), 5-26. 10.1111/j.1748-
Kuhl, J. and Beckmann, J. (1994). Volition and Personality:
Action Versus State Orientation. Seattle, G
ottingen, Bern:
Hogrefe & Huber Publisher.
Leroux, J. A. and Lafleur, S. (2006). Employability skills: the
demands of the workplace. The Vocational Aspect of
Education, 47(2), 189-196.
Lunev, A., Petrova, I., and Zaripova, V. (2013). Competency-
based models of learning for engineers: a comparison.
European Journal of Engineering Education, 38(5), 543-
555. 10.1080/03043797.2013.824410
Matturro, G., Raschetti, F., and Fontán, C. (2019). A Systematic
Mapping Study on Soft Skills in Software Engineering.
Journal of Universal Computer Science, 25(1), 16-41.
McIntosh, S. (2008). Education and employment in OECD
countries. Paris: United Nations Educational. Scientific
and Cultural Organization.
McQuick, R.W. and Lindsay, C. (2005). The concept of
employability. Journal of Urban Study, 42(2), 197-219.
McCrae, R. R., and Costa Jr, P. T. (1985). Comparison
of EPI and psychoticism scales with measures of
the five-factor model of personality. Personality and
Individual Differences, 6(5), 587-597. 10.1016/0191-
McCrae, R. R., and Costa, P. T. (1987). Validation of the five-factor
model of personality across instruments and observers.
Journal of Personality and Social Psychology, 52(1), 81-90.
Mocanu, C., Zamfir, A. M., and Pirciog, S. (2014).
Matching curricula with labour market needs for higher
education: state of art, obstacles and facilitating factors.
Procedia-Social and Behavioral Sciences, 149, 602-606.
. 40 N
. 2, A
- 2020
Olivares-Rodríguez, C., Guenaga, M., and Garaizar, P. (2017).
Automatic assessment of creativity in heuristic problem-
solving based on query diversity. DYNA: ingeniería e
industria, 92(4), 449-455. 10.6036/8243
Pineteh, E. A. (2012). Using virtual interactions to
enhance the teaching of communication skills to
information technology students. British Journal of
Educational Technology, 43(1), 85-96. 10.1111/j.1467-
Possa, G. (2010). Europe’s Universities Response to Europe’s
Challenges. Higher Education in Europe,31(4), 355-357.
Raybould, J. and Sheedy, V. (2005). Are graduates equipped
with the right skills in the employability stakes?
Industrial and Commercial Training,37(5), 259-263.
Redoli, J., Mompó, R., De la Mata, D., and Doctor, M.
(2013). DLP: A tool to develop technical and soft skills
in engineering. Computer Applications in Engineering
Education, 21(S1), E51-E61. 10.1002/cae.20572
Redomero, T., Caggiano, V., Poza-Lujan. J. L., and Piccione,
V. A. (2019). Fostering and assessing soft skills
of engineering students. The International journal of
engineering education, 35(6), 1656-1666.
Robles, M. M. (2012). Executive perceptions of the
top 10 soft skills needed in today’s workplace.
Business Communication Quarterly, 75(4), 453-465.
Schleutker, K. J., Caggiano, V., Coluzzi, F., and Poza-Lujan.
J. L. (2019). Soft Skills and European Labour Market:
Interviews with Finnish and Italian Managers. Journal
of Educational. Cultural and Psychological Studies (ECPS
Journal), 19, 123-144. 10.7358/ecps-2019-019-schl
Sleezer, C.M., Gularte, M.A., Waldner, L., and Cook, J. (2004).
‘Business and Higher Education Partner to Develop a
High-skilled Workforce: A Case-Study. Performance
Improvement Quarterly 17(2), 65-82. 10.1111/j.1937-
Shuman, L. J., Besterfield-Sacre, M., and McGourty, J. (2005).
The ABET “Professional Skills” Can They Be Taught?
Can They Be Assessed? Journal of Engineering Education,
94, 41-55. 10.1002/j.2168-9830.2005.tb00828.x
Stevenson, H. and Bell, L. (2009). Introduction universities
in transition: themes in higher education policy. In Bell,
L., Stevenson, H., and Neary, M. (Eds). The future of
higher education. New York: Continuum International
Publishing Group. (pp. 1-16).
Teichler, U. (2003). The future of higher education
and the future of higher education research.
Tertiary Education & Management,9(3), 171-185.
c, B., Jovanovi
c, J., Miliki
c, N., Deved
c, V., Dimitrijevi
S., Duri
c, D., and
Sevarac, Z. (2019). Grading students’
programming and soft skills with open badges: A case
study. British Journal of Educational Technology,50(2),
518-530. 10.1111/bjet.12564
Tulgan, B. (2015). Bridging the soft skills gap: How to teach the
missing basics to todays young talent. John Wiley & Sons.
Wang, M. T. and Degol, J. L. (2017). Gender gap in
science, technology, engineering and mathematics
(STEM): Current knowledge, implications for practice,
policy and future directions. Educational psychology
review,29(1), 119-140. 10.1007/s10648-015-9355-x
Weil, S. (1999). Re-creating universities for ‘beyond the
stable state’: from ‘Dearingesque’ systematic control
to post-Dearing systemic learning and inquiry.
Systems Research and Behavioral Science: The
Official Journal of the International Federation for
Systems Research,16(2), 171-190. 10.1002/(SICI)1099-
. 40 N
. 2, A
- 2020
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... Soft skills refer to a collection of interpersonal skills that enable people to enhance their relationships and performance at work [12]. These skills are necessary for any career and are crucial for joining and facing the labor market [13]. Soft skills in software development processes (SDP) are generally considered complementary to hard skills [14]. ...
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Software requirement engineering (SRE) is the process of establishing, documenting, and maintaining software requirements. The goal of this research is to investigate the importance of soft skills in SRE. The data collection was performed through an on-line questionnaire. Descriptive statistics, principal components analysis (PCA), and stepwise regression techniques were used to analyze the data. A comprehensive review determined the 31 soft skills associated with SRE. There were 122 software development experts in Gaza who participated in the survey. The PCA analysis extracted six factors, named problem solving , learning willingness, commitment, pressure resilience, critical thinking, and interper-sonal skills. The analysis discovered that the level of SRE practice in Gaza is 73.71%. Furthermore, it was determined that 89.2% of respondents have critical thinking skills, and 85% have problem-solving and commitment skills. The result shows that all soft skills factors have strong links to SRE. However, only four soft skills (problem-solving, willingness to learn, pressure tolerance, and critical thinking) were found to have an impact on SRE. Considering these findings, we recommend focusing on the development of soft skills, especially problem-solving and willingness to learn skills, for the team analyzing software system requirements. ACM CCS (2012) Classification: Software and its engineering → Software creation and management → Software development process management
... (g) Engineering skill: professional skills of engineering students suitable for smart construction include both hard and soft skills. Hard skills refer to generic skills in specified engineering majors, such as design and development, application of modern tools, project management and financial analysis, research and study, and engineering analysis [31,32,64], while soft skills include exploring and management skills as well as communication skills [65][66][67]. [68] were the first to introduce and use the concept of "linguistic landscape" and defined it as "the language of public road signs, advertising billboards, street names, place names, commercial shop signs, and public signs on government buildings combines to form the linguistic landscape of a given territory, region, or urban agglomeration." e linguistic landscape has two main types of functions, namely, informative and symbolic. ...
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This study investigates the mechanism of digital linguistic landscapes in enabling engineering education for smart construction according to the educational dimensions of A (ability), S (skill), and K (knowledge). A questionnaire survey was conducted based on the core concepts of the informative dimension and symbolic dimension in digital language landscape as well as the ability dimension, knowledge dimension, and skill dimension in engineering education. Structural equation modeling (SEM) was used as the test method. The results of the research demonstrate that the informative dimension and symbolic dimension are two main aspects of DLL in education of engineering students for smart construction. Additionally, DLL has a significant positive impact on the ability, knowledge, and skill education of engineering students for smart construction. The research has theoretical and practical significance, as it not only enriches research on the relationship between DLL and engineering education for smart construction but also expands the theoretical understanding of engineering education from the perspective of linguistics. Furthermore, the study explores the path of the practical application of digital language landscape to engineering education for smart construction.
... There is no research like the present that allows corroborate the results; however, it is relevant to highlight the study of Zhang (2012) For its part, the study of Caggiano et al. (2020) determined the importance of soft skills by obtaining that the engineers of the sample under consideration were able to express positive and negative ideas and feelings in balance with the reference mean, although they sometimes struggled to establish personal relationships. In this research the students studied show that they almost always perceive compliance with the elements evaluated, both in perception of interaction in virtual classroom and in soft skills. ...
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The purpose of this study is to specify the relationship between the perception of classroom interaction and the level of soft skills. A cross-cutting, correlal observational study was conducted on a sample of 507 students from the seventh to tenth cycle of the branch's professional schools in Arequipa from a private Peruvian university, recruited electronically in 2020. The instruments applied were the Virtual Classroom Interaction Perception Scale and the Soft Skills Scale. The results show the existence of a positive weak relationship between the perception of virtual classroom interaction and soft skills. The correlation was .114, the size of the effect is medium, being 0.3376389. In terms of statistical power, the value exceeds 0.80, obtaining the value of 0.950. It is concluded that there is a significant and positive relationship between the variables, even though the relationship between the two variables is weak.
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Given the current need to provide students with all the tools to develop in the professional world, research on soft skills and student stress becomes relevant. In this sense, the present investigation had the objective of determining how soft skills influence the reduction of student stress; Thus, the methodology used was the systematic review of the literature (SLR), in addition the systematic search has been developed under the parameters of the PRISMA flowchart. Finally, the study found that there are various investigations that prove that student stress decreases due to the implementation of soft skills within the classroom.
The importance of soft skills in the professional work of an engineer is becoming increasingly important, even more so since the emergence of Covid-19 boosted the digitization of all professional sectors. In order for future engineers to acquire this type of skills, it is necessary for engineering professors to have an optimal level of technical and transversal skills. This article analyzes the assessment made by a group of engineering professors about their degree of development of soft skills and describes gender gaps in these assessments. Based on a self-created survey to evaluate different families of soft skills relevant to engineering education, a sample of 284 Latin American engineering professors reported: 1) high evaluations of their soft skills and 2) the existence of gender gaps in the families of work behavior and social skills in favor of females. This gap is especially wide among participants younger than 45 and older than 65 in the social skills family. In addition, females also rate their work motivation skills higher, except in the 55–64 age range.
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Background: The identification of soft skills by Higher Education (HE) students is important for curriculum design, as is to evaluate if the students’ soft skills are adapted to the needs of the socioeconomic environment. This paper presents a study conducted to determine to what extent Finnish and Italian students’ perceptions of their own soft skills differ. Methods: The cohort of the study consisted of 80 Finnish and 80 Italian HE students. Results: The results reveal that, regardless of cultural aspects, both groups share specific soft skills whilst showing significant differences in others. The observed differences in the profiles of the two countries are explained on the basis of the cultural and curricula design frameworks that are well established in Finland and Italy. Conclusions: The implications of the findings for HE teachers and researchers are presented, which may bear relevance in guiding the implementation of curriculum design in Finland, Italy and beyond.
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The hotel sector in the historic center of Havana reveals deficiencies in customer satisfaction regarding human resource. This research is aimed at analyzing the results of the implementation of a continuous improvement of human resource management that allows the enhancement of services quality, assuming the Cuban norm. The main results show that 55% of the items identified with the application of the SERVQUAL model show quality deficit associated with processes of human resource management, such as work competences and work organization. The main dysfunctions identified were unproductive times due to organizational and technical issues and labor fluctuation. Subsequently, hidden costs due to deficiencies were calculated, which amount to a value of 13 249,89 MU/year. To monitor these problems, objectives and indicators are proposed through the Integral Command Table, as well as a plan of corrective and preventive actions.
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To participate in software development projects, team members may need to perform different roles and be skilled in diverse methodologies, tools and techniques. However, other skills, usually known as “soft skills” are also necessary. We report the results of a systematic mapping study to identify existing research on soft skills in software engineering and to determine what soft skills are considered relevant to the practice of software engineering. After applying an explicit mapping protocol, 44 papers were finally selected, and 30 main categories of soft skills were identified. At least half of the studies selected mention five skills: communication, teamwork, analytical, organizational, and interpersonal skills. We also identified the data collection methods commonly used for research on this topic: job advertisements and surveys were the main ones. The results of this work are of interest to researchers in human aspects of software engineering, to those responsible for Human Resource in software development companies, and to curriculum designers in careers related to software engineering and development.
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This research aims to analyze the influence of Engineering professors’ competencies on their performance, as perceived by Engineering students and graduates from a Brazilian federal public university. Regarding methodology, a set of Engineering educators’ competencies were proposed, identified, and validated by exploratory factor analysis (EFA), parallel analysis, internal consistency (Cronbach’s alpha), and partial confirmatory factor analysis (PCFA) in a sample of 139 Engineering students and graduates (engineers), who answered a 35-item questionnaire. Results reveal three main competencies (namely, content-pedagogical knowledge, innovation-inspiring attitudes, and emotional skills) that further the research on the competencies of Engineering professors. First, content-pedagogical knowledge is perceived by students as a single, merged competence. Second, Engineering students not only need to develop innovation competencies, but Engineering educators also have to develop innovation-inspiring attitudes to motivate students’ innovativeness. Third, emotional skills also play an important role in professors’ performance. Finally, the impact of these competencies on Engineering educators’ performance was confirmed and analyzed by means of a logistic regression.
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Soft-skills have proved to be a necessary complement to technical skills in today’s multinational workplaces. As universities are facing the challenge of promoting internationalization and mobility in students and teachers, they have to decide how to help their students in developing these skills as well as increase their awareness on the cultural differences in multinational settings. After a long trajectory of participation in multinational educational experiences, the authors launched a survey to check if their previous findings on the preferred soft skills by educational experts and managers still remain valid after 5 years. Another goal of the study was the analysis of the link between preference for specific soft skills and cultural background in each country as characterized by Hofstede’s indicators. The data collected from 123 experts from 45 different countries have confirmed the existence of a stable core set of preferred soft skills at global level and also for European countries. Results have also shown links between specific cultural indicators and preference for some soft skills.
This chapter examines the disjunctures between engineering education and practice to identify ways to better connect the two. Qualitative interviews with engineering students and new engineers are used to compare the knowledge and skills that engineers learn in school and those that they learn on the job. Our findings demonstrate that, while engineering practice requires the integration of several kinds of knowledge and skills, engineering education focuses mainly on the technical side. Engineers learn most professional and organizational knowledge and skills only after entering the workforce. Even when they are exposed to professional skills such as teamwork and communication in school, they may not see true representations of what these skills look like on the job or consider the work as “real engineering”. The results suggest deficiencies in the current model of engineering education that constrain its ability to produce effective graduates. Implications for engineering education, professional practice, and educational research are discussed.
Well-developed programming (technical) skills are very important for software engineers, information systems engineers and programmers in general. However, they must also possess relevant personal skills (soft skills) to be successful at the workplace (eg, collaboration, solving real-world problems and communication). The latter, however, are rarely assessed and acknowledged in regular software engineering courses. This paper describes the results of a small case study involving an extracurricular Java programming course in which, in addition to knowledge and skills in relevant technologies, students' soft skills were also assessed. As part of the assessment, students have been awarded Open Badges. The study was exploratory in nature, aimed at examining Open Badges as a motivational mechanism, students' engagement in attaining soft skills and students' perception of soft skills and Open Badges. The results suggest that Open Badges may not be so effective in motivating students to complete the assignments nor attend the course, although students' perception of Open Badges is generally positive. Soft skills were generally perceived as important as hard skills. Students' engagement in attaining soft skills could be affected by assignment announcement time and its level of difficulty.