Understanding the Gaps in Software Engineering Education from the

Perspective of IT Leaders: A Field Study

Fernando Bona

, Rafael Chanin

, Nicolas Nascimento

and Afonso Sales

School of Technology, PUCRS, Porto Alegre, RS, Brazil

Keywords:

Software Engineering, Software Engineering Education, Skillset in Software Engineering.

Abstract:

Teaching software engineering is challenging as it is a ﬁeld widely desired by the market, and it requires

professionals with an increasing set of skills. There are gaps in this learning process perceived both by profes-

sionals from the academia and from the industry that need to be further investigated in order to ﬁnd strategies

to reconcile the expectations from both environments. In this sense, this study aims to investigate these gaps

from the perspective of Information Technology (IT) team leaders. In order to do so, we chose a qualita-

tive approach to absorb as much knowledge as possible from each interviewed leader by using a ﬁeld study

methodology. Among the results obtained, we identiﬁed the appropriate proﬁle to become an IT leader, what

IT leaders expect regarding the skills of IT novices, and how the academia and the industry could work to-

gether to build an environment that better prepares these professional, according to the view of the interviewed

leaders.

1 INTRODUCTION

Software engineering (SE) is the science ﬁeld which

studies the production and management of software.

It is split in many subﬁelds, such as software devel-

opment, requirements engineering and management,

software testing and many others. Each of these sub-

ﬁelds represents roles performed by industry profes-

sionals (Sommerville, 2011). Besides that, the teach-

ing of SE is based on the premisse of an optimal bal-

ance between theory and practice, so that students

can develop fundamental concepts and knowledge to-

gether with skills that aid in the resolution of real

world problems that the industry faces (Ouhbi and

Pombo, 2020).

There are different techniques employed by teach-

ers to optimize the teaching of IT students, given the

constant challenge presented by the industry to the

academia that demands learning that is focused on

what the industry requires (Bruegge et al., 2015). In

this scenario, complementary courses have appeared

(Nascimento et al., 2019). These courses do not fol-

low the formal structure of an undergraduate course,

https://orcid.org/0009-0008-7728-3244

https://orcid.org/0000-0002-6293-7419

https://orcid.org/0000-0002-0080-8822

https://orcid.org/0000-0001-6962-3706

and can be taken in parallel with college and focus on

speciﬁc tech and methodology that is demanded by

industry standards.

Some studies have presented indicatives that these

complementary courses

have a high relevance for

students that take them. Steglich et al. (Steglich et al.,

2020), for example, has identiﬁed a 88% course-to-

market ratio.

Therefore, the main goal of this research is to

identify the gaps between the formal teaching in the

academia and industry demands. Besides that, we

have a secondary goal, which is to understand how to

optimize the formal teaching so it can become closer

to the industry.

Given the aforementioned goals, we have set the

following research questions (RQ):

• RQ1: How is this academia-industry gap in skill devel-

opment perceived by IT leaders?

• RQ2: What actions and mechanisms can be adopted

by formal undergraduate programs to get closers to the

industry?

Considering the goals and questions presented, we

have performed a ﬁeld study with 25 IT team leaders,

A complementary course is usually a course performed

either by the industry or industry-academia partnerships

covering emerging technologies that are being adopted by

the market and allowing students to catch up with the in-

dustry.

Bona, F., Chanin, R., Nascimento, N. and Sales, A.

Understanding the Gaps in Software Engineering Education from the Perspective of IT Leaders: A Field Study.

DOI: 10.5220/0011959100003470

In Proceedings of the 15th International Conference on Computer Supported Education (CSEDU 2023) - Volume 2, pages 511-518

ISBN: 978-989-758-641-5; ISSN: 2184-5026

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

511

in which we sought to map the gap between academia

and industry from these professional’s perspectives.

Since they are used to lead novice developers when

they reach the industry, we might be able to under-

stand the process of learning that a novice developer

requires once inside a company. In this study we will

use the terms novice and newcomer interchangeably.

Among the main results obtained by this study, we

have found that IT leaders consider that professionals

that enter into the market have: i) lack of technical

deepness, ii) lack of communication, iii) lack of busi-

ness knowledge, iv) lack of time management skills,

v) lack of patience, vi) lack of resilience, and vii) lack

of pro-activity. To deal with this, leaders apply men-

torships, feedbacks and collaborative work.

2 BACKGROUND

In this section we depict and explore the concepts that

are important to understand this study.

2.1 Software Engineering

Software engineering can be deﬁned in several ways;

a standard deﬁnition is a systematic collection of good

practices in the context of software development pro-

cesses (Mall, 2018). This systematization is based on

academic research, as well as in observations from the

industry (Mall, 2018).

In this sense, the goal of the ﬁeld is to discuss

the cost-beneﬁt of software development techniques.

These techniques support the process since they were

conceived by using engineering approaches (Mall,

2018). Beslmeisl et al. (Beslmeisl et al., 2016) de-

scribe the importance of scientiﬁc research in the con-

text of software engineering education, which investi-

gates methods to teach basic as well as advance con-

cepts. The software engineering domain does not fo-

cus only on the ﬁnal product, but in the whole pro-

cess. Therefore, in order to deliver content that can

help professionals in their career, it is important to

oversee all aspects (Beslmeisl et al., 2016).

2.2 Software Engineering Education

Many scientiﬁc events have gathered researchers to

discuss techniques that can better help instructors in

the process of teaching software engineering (Cunha

et al., 2018). Several challenges have been presented:

i) difﬁculty in engaging students; ii) difﬁculty in or-

ganizing and executing hands on activities; iii) difﬁ-

culty in ﬁnding good books and articles; and iv) dif-

ﬁculty in ﬁnding tools to support the learning pro-

cess (Ouhbi and Pombo, 2020). To solve this, several

approaches have been tested by software engineer-

ing teachers: Flipped Classroom (Kiat and Kwong,

2014), Problem based learning (Richardson and De-

laney, 2009), Challenge based learning (Binder et al.,

2017), Project-based Learning (Souza et al., 2019),

Role Playing (Zowghi and Paryani, 2003), and Seri-

ous Games (Hainey et al., 2011).

2.3 Gaps Between Academia and

Industry

The connection between academia and industry is that

the ﬁrst prepares students that will become future pro-

fessionals in the market. However, it is not uncom-

mon to ﬁnd gaps in this relationship (Kumar, 2006).

This happens for a lot of reasons. One example is that

sometimes the academia is not able to keep up with

the current market needs, since it changes rapidly.

Therefore, several authors have tried to map out

the gaps between academia and industry in order to

better understand this phenomena. In this context,

Oguz e Oguz (Oguz and Oguz, 2019) have identify

the following gaps: i) the software industry is always

expanding to new areas; ii) academia does not receive

feedback from the industry; iii) software engineering

course can not keep up with the new practices in the

market; iv) courses are taught individually, as a box,

and students sometimes can not see the connection

among them; v) instructors are usually not connected

with the industry; vi) soft skills are a must in the

software engineering context; and vii) undergraduate

courses do not follow the current trends of the market.

Moreover, Oguz e Oguz (Oguz and Oguz, 2019)

investigated which abilities are most needed in the in-

dustry. In regards to hard skills the author mentioned:

i) programming; ii) database; iii) understand the soft-

ware engineering process; and iv) having work expe-

rience. When it comes to soft skills: i) being ﬂuent in

English; ii) teamwork; iii) problem solving; iv) criti-

cal thinking; and v) communication.

3 IT LEADERS FIELD STUDY

3.1 Methodology

Field studies, according to (Singer et al., 2008), seek

to investigate participants in some activity and to

characterize how these participants deal with them,

understanding how they solve problems in a deﬁned

context. Data from a ﬁeld study is usually qualitative.

However, data collection can be performed through

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512

observation, through questionnaires or through inter-

views to obtain data about the participants’ activities

(Singer et al., 2008).

In this study, we have decided to collect data

through interviews which were conducted remotely

due to the pandemic (Platto et al., 2020). Thus,

we have followed the recommendation proposed by

(Seaman, 2008) for semi-structured interviews; even

though a list of questions was established, we could

be open to other topics expressed by participants.

Initially, two pilot interviews were performed with

two professionals from the research ﬁeld but who had

experience leading IT teams in order to improve the

quality of the data collection instrument. Data from

these interviews were not considered for the study, but

it allowed us to adjust the questions so that they could

be logically organized. Further, three senior SE re-

searchers have reviewed the protocol, each of which

with had 6, 15 and 20 years of experience in the SE

ﬁeld respectively.

In a ﬁnal version, the interview protocol was com-

posed by 11 questions, with 6 proﬁle questions and 5

research-related questions. The proﬁle (Q1-Q6) and

research (Q7-Q11) questions were:

1. What is your company size? How many employ-

ees does it have approximately?

2. For how long have you been a part of the com-

pany?

3. For how long have you been leading IT teams?

4. What technical characteristics do you consider to

be the most important to lead an IT team?

5. What behavioral characteristics do you consider

to be the most important to lead an IT team?

6. What is the frequency with which you have con-

tact with newcomers in the tech ﬁeld?

7. When newcomers arrive, what skills do they usu-

ally have and that are extremely important to the

working environment?

8. When newcomers arrive, what skills do they usu-

ally lack and that are extremely important to the

working environment?

9. Regarding these skills that newcomers usually

lack, how do they usually deal with this and what

are the most assertive strategies?

10. Can you identify mechanics in the academia that

aid newcomers to outperform others in the work-

ing environment?

11. How do you consider that the formal teaching can

aid these professionals to arrive better prepared?

In total, 40 IT leaders were invited, by conve-

nience, to participate in the study, with 25 of these

leaders actually participating. To identify the amount

of participants in the study, we have used the concept

of saturation presented by (Creswell, 1998) which

consists in performing a set of interviews and assess

them until new data is not obtained anymore. Initially,

we have performed 10 interviews and did not reach-

ing saturation. After that, we performed 10 more in-

terviews, still not reaching saturation. Next, we per-

formed 10 more interviews and, once we had ana-

lyzed 25 participants data points, we realized that the

last ﬁve did not add any new evidence (reached satu-

ration) and only deepened already-mapped topics.

These interviews were recorded, always with the

authorization from the participants. However, these

audio ﬁles were only used for the transcription of

each interview, preserving the identity and privacy of

them. The interviews lasted between 20 and 40 min-

utes, with an average time of 28 minutes.

Data analysis was performed according to

(Bardin, 2004), in which we have analyzed the con-

tent of the answers, grouped them by opinion agree-

ment of the participants, taking note of the disagree-

ments when they occurred and extracting as much in-

formation as possible from the interviews’s transcrip-

tions to answers the selected questions. After that,

we created categories for the extracted information,

allowing for a categorization of the answers through

the participants’s point of view.

3.2 Participants Proﬁle Questions

The proﬁle questions were proposed in order to char-

acterize the IT leaders that participated in this study.

The ﬁrst questions (with their respective answers) can

be found in Table 1. ID identiﬁes the participants.

To sum up, 13 leaders worked in big size compa-

nies, 7 in medium size companies and 5 in small com-

panies. The number of workers varied from 3 (which

is a startup) up to multinational companies with over

400,000 employees. Moreover, we interviewed pro-

fessionals with only one year as a leader as well as

others with up to 23 years as IT leaders.

Participants also characterized what they believe

to be the most important abilities in a IT leader. This

information is presented in Figure 1. As it can be no-

ticed, we group these abilities into for subgroups:

Technical Knowledge of Utilized Technology: IT

leaders usually do not act as programmers, but they

need to know how the technology works and need to

know how to guide the team about these technologies.

Management and Leadership Capacity: It is ex-

pected from a leader, beyond technical knowledge, a

proper usage of management and leadership skills to

keep the commitments that the company demands.

Understanding the Gaps in Software Engineering Education from the Perspective of IT Leaders: A Field Study

513

Table 1: IT leaders professional proﬁle.

Company

Size

Number of

Workers

Years of

Service

Year Leading

Teams

L1 Big 10.000 9 years 9 years

L2 Big 1.500 1 month 8 years

L3 Small 40 7 years 20 years

L4 Medium 200 1 year 10 years

L5 Big 28.000 3 months 15 years

L6 Big 3.100 3 months 8 years

L7 Big 6.000 2 years 7 years

L8 Medium 300 5 months 4 years

L9 Big 10.000 3 years 6 years

L10 Big 6.000 3 years 1 year

L11 Medium 500 3 months 5 years

L12 Medium 110 7 months 4 years

L13 Big 34.000 1 year 4 years

L14 Medium 120 3 years 20 years

L15 Big 1.500 10 years 6 years

L16 Medium 50.000 2 years 14 years

L17 Small 70 5 months 7 years

L18 Big 400.000 21 years 18 years

L19 Small 3 5 years 5 years

L20 Small 18 5 years 4 years

L21 Medium 300 4 years 9 years

L22 Big 3.000 7 years 6 months

L23 Big 1.500 2 months 2 years

L24 Small 4 1 year 9 years

L25 Big 4.000 31 years 23 years

Team Formation Knowhow: IT leaders need to use

the proﬁle of team members, knowing the characteris-

tics and skills that each member possesses in order to

design teams where members complement each other.

Figure 1: Most important abilities according to the partici-

pants.

Communication: Leaders need to be be understood

by the team, transmitting information clearly or being

transparent whenever possible.

Behavioral skills are expressed in Figure 2, where

12 codes have emerged after summarization:

Active Listening: IT leaders must listen to their

teams and gather information even when performing

other task within the project.

Communication: Communication between the

leader and his/her team needs to be transparent, and

everyone must try to understand each other.

Empathy: In some situations it is recommended to

exercise empathy within the team, trying to put your-

self in someone else’s shoes.

Resilience: A leader must persist until it ﬁnds a vi-

Figure 2: IT leaders most important behavioral characteris-

tics.

able alternative. Since the leader is usually the most

experience person in the team, he/she needs to set an

example.

Leadership: Not everyone is naturally prepare to be-

come a leader. Most of the times It is necessary to

develop this ability throughout the process.

Flexibility: A leader must be ﬂexible, knowing how

to talk to the team members and, in some cases, give

in to the team members’ needs.

Adaptable: Projects constantly change and so must

the leader and team be able to cope with these

changes.

Technical Support: In many cases, the leader is the

most experienced person in the team, even in the tech-

nical aspect. So, in difﬁcult situations, the leader

needs to guide the learning process to solve these sit-

uations.

Collaboration: The leader is part of the team and as

such should collaborate and try to ease internal team

processes.

Concern for People: The leader must worry with the

well-being of his/her team members, ensuring they

are comfortable with their roles as this could some-

times depend on the execution of projects.

Knowing How to Provide Feedbacks: The leader,

given in many cases possesses the most experience,

can and should support the professional development

of team members, utilizing feedback to point the good

points and the improvement opportunities.

The interviewed leaders were also questioned

about when they were used interact with IT newcom-

ers/novices (Figure 3), where 3 codes were identiﬁed:

Figure 3: Leaders’s interaction with IT newcomers.

Little: Does not possess frequent contact with IT

newcomers.

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514

Often: Does not have daily contact, but often interact

with IT newcomers.

Daily: Interacts with IT newcomers everyday.

As such, the leader proﬁle tends to be diverse, pos-

sessing this characteristics in common, according to

the answers to this question, but with some particular

ways leader handle their teams.

3.3 Field Study Research Questions

Participants also provided their opinions regarding

skills that newcomers have when joining and IT team.

The skills that they use to have when they arrive in

this team is expressed in Figure 4, where in this ques-

tion 6 codes emerged after summarization:

Figure 4: Skills newcomers usually have.

Desire to Learn: Newcomers usually arrive in com-

panies with a desire to learn with industry profession-

als.

Knowledge Base: The newcomer needs to have a

base knowledge, even just programming logic, to be

able to trained on the more complex technologies be-

ing used by the team.

Curiosity: The newcomer usually questions team

members about the usage of certain technologies.

New Ideas: When newcomers arrive from Academia,

they usually have seen new technological tendencies

and sometimes bring new options for the development

team.

Sharing: Newcomers usually have an open mind to

knowledge sharing, besides, they beneﬁt widely with

knowledge shared by others.

Honesty: A person that is just arriving is usually care-

ful when commenting their limitations or difﬁculties,

generating issues, but that can be avoided with dialogs

and honesty with their team colleagues.

The skills that newcomers usually do not pos-

sess are expressed in Figure 5, where 9 codes have

emerged in this question after summarization:

Lack of Technical Depth: Newcomers, as the name

suggests, arrive with limited knowledge. This is un-

derstandable, and they evolve as they participate more

in projects.

Lack of Communication: Some newcomers are shy.

However, it is vital to communicate to avoid misun-

derstandings.

Figure 5: Skills newcomers usually do not possess.

Lack of Business Knowledge: Newcomers tend to

think of IT projects just the in term of technical as-

pects, but not in regards to the business.

Lack of Sense of Time: Another issue with newcom-

ers is related to tasks estimations. Newcomers tend to

underestimate the difﬁculty of the tasks.

Impatience: IT leader have reported that newcomers

try to deliver tasks as fast as they can without paying

attention to the quality of their work.

Lack of Resilience: IT leaders pointed out that new-

comers give up very quickly when they face a harder

challenge.

Lack of Proactivity: According to the IT leader,

newcomers could be more proactive and take more

risks.

Lack of Flexibility: Sometimes newcomers do not

understand the company structure and feel frustrated

when something can not be done their way.

Lack of Self Conﬁdence: In some situations, new-

comers do not fell comfortable to take responsibility

since they do not know if they can deliver the given

task.

In order to support newcomers, IT leaders came up

with a few strategies that are presented in Figure 6.

Figure 6: Strategies to help newcomers.

Mentoring: In this process, more experienced team

members are selected to partner with newcomers.

Feedback: More experienced team members can pro-

vide feedback to newcomers so they can improve their

learning process.

Collaborative Work: When working is pairs or in

groups, newcomers can develop their abilities faster

since they can learn from others.

IT leaders also mentioned what they believe to be

effective in the classroom context in order to put stu-

Understanding the Gaps in Software Engineering Education from the Perspective of IT Leaders: A Field Study

515

dents more connected to the market (see Figure 7).

We identify 10 itens:

Figure 7: Academia mechanisms to connect students to the

market.

Speciﬁc Disciplines: Some disciplines are speciﬁc

to get students close to the industry, making learning

closer to the professional reality.

Internship: An effective mechanism is internship, as

it inserts the student in the industry. However, the

Academia is dependent on the local industry to open

this positions.

Labor Market: Some leaders believe that students

only learn when they enter the labor market.

Disbelief in the Mechanisms: Some IT leaders do

not believe in the Academia mechanisms, considering

all of them inefﬁcient to some degree to support the

demands.

Knowledge Base: Some leaders point that the ole of

the Academia should continue to be just provide basic

knowledge and allowing that the industry to perfect

the professional.

Hackathons: Events such as hackathons have a po-

tential to approximate the student of real scenarios

and to create some networking with industry profes-

sional.

Practical Labs: Some universities offer practical labs

in which students take on roles in IT teams, as it is the

case of the AGES (Experimental Software Agency)

from PUCRS (Yamaguti et al., 2017).

Research: Academia engaging the student to re-

search the industry and its roes to support students’

decision-making for what to enter.

Complementary Courses: Some programs offered

by the industry in partnership with the Academia in

which students are taught members of both institu-

tions (Steglich et al., 2020).

Group Work: In some ways, group work when well-

structured help in the development of soft skills that

are important for the IT labor market.

Leaders also explain the ways in which formal

study could support students to reach the market bet-

ter prepared (Figure 8). Regarding ways in which

Academia can support students, 9 codes were iden-

tiﬁed:

Figure 8: Graduation course strategies to support students.

Students Market Insertion: The Academia needs to

seek more partnerships with the industry so that to-

gether they can insert students directly in IT industry

environments.

Courses Modernization: Some courses are obsolete

with the reality being presented by the market, given

that the tech ﬁelds have a high update frequency of

their techniques, methods in which the Academia usu-

ally struggles to keep up with.

Business Needs: Students usually possess a decent

technical notion in contrast to business notion. These

students need to be equally prepared to understand

the business ecosystem in which the product he/she

builds are inserted.

Market Professionals: The addition of some market

professionals as teachers tends to develop some skills

before the student joins the job market.

More Soft skills: Some courses emphasis too much

the technical aspect, with space to add more disci-

plines that bring personal and professional develop-

ment to students through soft skills.

Practical Classes: Practical classes are usually sim-

ulations of what the students may ﬁnd in the market,

if well-implemented.

Knowledge Base: Academia usually prepares stu-

dents by providing the technical base so that profes-

sionals can join the market.

Training Courses: In some speciﬁc technologies that

are interesting to the student, it can be a good ex-

perience to join a training course (Nascimento et al.,

2019) about a speciﬁc technology.

Bring in Market Professionals: Reducing the dis-

tance between Academia and Industry in which mem-

bers of both parts have an open dialog seeking to re-

duce these gaps.

As such, through these obtained results, it is pos-

sible to understand the position IT leaders have in

which they have demands for IT newcomers/novices

and try to support them on the other hand, thus, de-

veloping the necessary skills to perform in their com-

panies.

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516

4 DISCUSSION

QP1. How Is this Academia-Industry Gap in Skill

Development Perceived by IT Leaders? First of

all, we have decided to understand what the indus-

try has demanded from these IT novices, in which the

IT leaders invited to this study recognize that novice

professionals have positive characteristics such as a

willingness to learn and a speciﬁc knowledge base,

but they do not have some skills that would be im-

portant to develop for a professional in a way to work

in the IT market, such as: technical depth, communi-

cation, business knowledge, sense of time, patience,

resilience, pro-activity, among other skills.

The industry has strategies to overcome these

gaps, such as mentorship programs, feedbacks and

collaborative work that put pace in the novice pro-

fessional to understand the logic that the industry de-

mands. However, in order to overcome this gap there

are also initiatives recognized by the academy, such as

internship programs, speciﬁc disciplines/courses and

approaches to the job market for students to try to

learn their professional assignments in immersive en-

vironments of industry, but which still demand con-

siderable efforts from both academia and industry.

IT leaders recommend some strategies such

as putting students into the market, modernizing

courses, teaching about business needs, classes with

market professors, soft skills training, practical

classes, focusing on knowledge bases, and training

courses and complementary training. These strategies

were properly debated by the IT professors, who re-

ported that have their respective interests in bringing

students closer to the market, but that in some cases

there has been little receptiveness on the part of the in-

dustry, especially when looking for projects that have

some ﬁnancial support that motivates their students.

QP2. What Action and Mechanisms Can Be

Adopted by Formal 88 Undergraduate Programs

to Get Closers to the Industry? Updating courses

is a process that takes a consider period of time,

since it demands legal procedures with the Ministry

of Education, in addition to the fact that technolo-

gies are constantly changed in the industry. Teach-

ing about business aspects and soft skills are consid-

ered important by teachers, but have seen with some

“strangeness” by students and some teachers, who

think that this knowledge seems to “blur” what is re-

ally the core of Computing. As a result, teachers tend

not to focus on speciﬁc technologies but on knowl-

edge bases that reconcile their activities for the devel-

opment of soft skills and business knowledge.

Finally, the courses offer certain practical sub-

jects, including some optional ones in which students

can explore themselves into speciﬁc topics, but teach-

ers recognize that formal education cannot be speciﬁc

to the needs of all companies in the industry.

Therefore, complementary education (i.e., a

course performed by partnerships between industry

and academia, and sometimes only by the industry)

becomes an alternative that can be stimulated by both

academia and industry to mitigate this gap between

formal education and the demands from the industry,

where these courses are offered in different ways and

focused on speciﬁc technologies that may represent a

demand from the industry.

5 THREATS TO VALIDITY

The results found by a ﬁeld study can sometimes be

limited to the interviewees’ perspective. Even though

we sought to reduce the impacts generated by biases

through the opinion of more than one leader, there

were somewhat divergent opinions on speciﬁc topics

in this research. An example of this is how many

mechanisms currently exist in the academy for the

student formation to the market (where the most part

of the leaders believe in these mechanisms), but three

of them have do not believe in effectiveness as ex-

pressed in Figure 7. Moreover, it was sought through

writing to present and elect the results in the most

transparent way as possible to protect the understand-

ing of the data as well as the terms or expressions that

can be understood as ambiguity by the readers.

6 CONCLUSION

The gaps in the training of IT professionals are chal-

lenges for both academia and industry, and common

solutions cannot fully resolve this distance that both

have between them. In this way, it is essential to

provide ways to reduce these gaps, where comple-

mentary training courses can be a promising solution:

they are relatively faster courses than formal educa-

tion and focused on a technology or methodology that

is highly demanded by the Industry.

Dialogue between academia and industry is fun-

damental, especially when designing projects such as

complementary training courses, which are focused

on the needs of the industry in a way that tradi-

tional/formal training courses cannot due to several

factors, leading in this case to the formal education

not being able to handle all technologies and method-

ologies in the way that the industry wants.

Understanding the Gaps in Software Engineering Education from the Perspective of IT Leaders: A Field Study

517

Complementary training courses do not replace

the need for formal courses, but tend to explorer

deeper into topics that are seen more superﬁcially in

the academy, offering more opportunities for practice

and increasing students’ opportunities to enter the job

market. Industry professionals who have taken these

courses consider that the impact of additional training

courses have been extremely beneﬁcial for their pro-

fessional careers, and IT leaders recognize that the ad-

dition of mechanisms by the academy tends to reduce

the gaps in professional training in IT novices.

As future work, we intend to conduct a study

with the participation of teachers of formal education

(e.g., undergraduate courses), professors of comple-

mentary training courses and members of the indus-

try in search of the preparation of a model that can be

used by both in the reduction of gaps in professional

training between academia and industry.

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