Leadership Teaching in Agile Software Engineering: A Systematic

Mapping

Nicolas Nascimento

, Afonso Sales

and Rafael Chanin

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

Keywords:

Leadership Teaching, Active Learning, Software Development.

Abstract:

The software industry is characterized by an environment of uncertainty, high volatility, and constant change.

This context has shaped the industry, its components, and actors, generating methodologies capable of meet-

ing both market expectations and software development requirements. Among these methodologies, agile has

been the most widely adopted — it provides teams with an overarching set of practices to manage software

development project requirements while maintaining ﬂexibility to incorporate changes that the business envi-

ronment presents. However, professionals equipped with the necessary skills to work in these Agile teams,

often referred to as “soft skills”, pose a challenge for universities to teach. From this set of skills, leadership,

in particular, has recently garnered attention from the software engineering education community but remains

an open research opportunity. In this context, this work aims at creating a body of knowledge regarding lead-

ership teaching in agile software engineering. To achieve this goal, we conducted a systematic mapping. From

a selection of 27 studies, our results provide indications that: (i) leadership in software engineering education

is typically deﬁned as part of teamwork, shared among team members, associated with Scrum, and applied

to provide students with experience in group representation; and (ii) it is usually taught through Scrum, in-

volving active learning methodologies (such as problem-based learning) and employing real projects either

sourced from external partners or designed to solve real-world problems.

1 INTRODUCTION

Great uncertainty, high volatility, and constant change

are inherent traits of software development. This en-

vironment has shaped the industry, its components

and actors, generating methodologies that are able to

cope both with market expectations and software de-

velopment requirements (Fowler et al., 2001). Agile

(via its derived frameworks, such as Scrum (Schwaber

and Sutherland, 2011) and XP (Beck, 2000)) is the

one which has been adopted the most. By provid-

ing teams with an overarching set of practices to han-

dle the many assignments a software development

project requires while remaining ﬂexible and adapt-

able enough to incorporate changes that business de-

mands (Dingsøyr et al., 2012).

Professionals that work in these agile teams are

expected to not only technically excel, but also to pos-

sess abilities to handle conﬂict, perform on-demand

adaptations and communicate properly and effec-

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

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

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

tively. This set of skills is usually denominated “soft

skills” (“people skills”, “social skills”, “generic

competencies”, or “human factor”) (Matturro et al.,

2015). The need for software developers to possess

this set of skills is evident provided their routines

usually include interactions with customers, team-

mates, stakeholders and leadership, where being able

to problem-solve, negotiate and resolve conﬂicts is

crucial (Ahmed et al., 2015).

From this set of soft skills, leadership, in par-

ticular, is a soft skill that has recently been stud-

ied by the software engineering research community.

For instance, the relevance of leadership in software

development (Faraj and Sambamurthy, 2006; Mat-

turro et al., 2015), styles of leadership (transforma-

tional, transactional, among others) and their impacts

on the software development life-cycle (Athukorala

et al., 2016; da Silva et al., 2016; Faraj and Sam-

bamurthy, 2006; Van Kelle et al., 2015), developing

leadership in virtual and globally distributed teams

(Furumo et al., 2012; Sangwan and Ros, 2008; Hi-

dayati et al., 2020), and leadership emergence and its

antecedents in software engineering (Przybilla et al.,

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

Leadership Teaching in Agile Software Engineering: A Systematic Mapping.

DOI: 10.5220/0013196600003932

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025) - Volume 2, pages 469-480

ISBN: 978-989-758-746-7; ISSN: 2184-5026

469

2019; Przybilla et al., 2020) are some of the angles

currently being investigated by the community. More-

over, leadership in software engineering is still a topic

not fully understood, with studies in the area not pro-

viding a uniﬁed view of leadership, although hierar-

chy and management aversiveness are commonly re-

ported (Modi and Strode, 2020).

There are some studies that touch relevant topics

on the ﬁeld, such as leadership teaching and training

for software engineering students. Some of this stud-

ies, for example, investigate leadership in distance

learning and as a component of teamwork (Marquez

et al., 2022; Vivian et al., 2013; Noguera et al., 2018),

teaching responsible leadership (Goyal et al., 2022),

using capstone projects (Schneider et al., 2020; Paiva

and Carvalho, 2018; Li et al., 2023) and even incor-

porating entrepreneurship in teaching (Moreno et al.,

2022; Tenhunen et al., 2023) and, thus, the challenge

of understanding and adopting the proper way to teach

this skill remains for educators.

This study seeks to develop a comprehensive un-

derstanding of leadership teaching in agile software

engineering. To achieve this, we conducted a system-

atic mapping to examine how leadership is deﬁned

and implemented in educational settings. Our ﬁnd-

ings indicate that leadership in software engineering

education is commonly seen as a component of team-

work, distributed among team members, and closely

tied to Scrum practices. It is predominantly taught

through active learning methodologies and real-world

projects, either sourced from external partners or de-

signed to address practical challenges.

2 BACKGROUND

2.1 Leadership

There are many deﬁnitions of leadership. In our case,

to better frame leadership, we have chosen to ground

ourselves on the concept of path-goal theory of lead-

ership. This concept refers to body of knowledge

that describes the effectiveness of leaders as a con-

sequence of their ability to positively impact peers’

motivation, ability to perform effectively and satis-

factions (House and Mitchell, 1975). Further, this

concept has been empirically studied to have positive

correlations to leadership in software projects, such as

open-source (OSS) (Li et al., 2012) and has been stud-

ied in education in various settings, such as distance

learning (Dewan and Dewan, 2010; Bickle, 2017) in

industry organizations (Malik et al., 2014).Further,

leadership, in a general sense, revolves around two

different styles of leadership, which are mostly op-

posed. These are transactional and transformational

leadership (Bass et al., 2003). Each of these style

presents different aspects on how guidance of the

leader should be provided towards his/her followers.

2.1.1 Transactional Leadership

Transactional leadership is a leadership style that re-

volves around followers being in accordance or agree-

ing with the leader either to be rewarded or to avoid

any corrective action. Prizes and rewards are awarded

based on the compliance of the followers to the expec-

tations of the leader (Podsakoff et al., 1984). Examin-

ing from a social context, this style of leadership has

been stated to be observed in a “well-ordered society”

(Bass and Bass Bernard, 1985).

2.1.2 Transformational Leadership

On the other hand, transformational leadership

achieves followers performance enhancement by set-

ting higher expectations and by increasing their will-

ingness to embrace more challenging duties. Fur-

ther, it emphasizes a greater ﬂexibility of the leader

in which better understanding of the organization’s

challenges are achieved and the solving of complex

problems is performed through cooperation between

leaders and followers (Bass et al., 2003). In addition,

leaders aid followers at performing leadership duties.

In this style, followers present personal and socially

identiﬁcation towards the missions of the organization

and build identiﬁcation and motivation on the follow-

ers through personal and social identiﬁcation. From

a social context, this style of leadership is stated “to

emerge in times of distress and change” (Bass and

Bass Bernard, 1985).

2.2 Agile Software Development

In modern software development, change is a con-

stant and it is often caused by external and uncon-

trollable factors (Barry et al., 2002). As markets and

economies quickly and unpredictably change, tradi-

tional software development practices, tool and tech-

niques become difﬁcult to apply and to follow ap-

propriately. In addition, these changes impact on

the software development project, which commonly

grows both in scope and cost, a phenomenon known

as Scope Creep (Barry et al., 2002; Melegati et al.,

2019). This results in high costs for the development,

maintenance and update of software products, thus re-

ducing the competitiveness of software development

companies. In this context, as faster and more ﬂex-

ible software development techniques became more

CSEDU 2025 - 17th International Conference on Computer Supported Education

470

necessary, in 2001, the “Manifesto for Agile Software

Development” (Fowler et al., 2001) was created.

3 RESEARCH METHOD

According to standard guidelines for performing this

research method (Budgen et al., 2008; Petersen et al.,

2008; Kitchenham et al., 2011), a systematic mapping

review (SMR) is relevant in software engineering as

it “provides a structure of the type of research reports

and results that have been published by categorizing

them.” Furthermore, SMR provides an overview of

the knowledge in an area, usually aided by a visual

summary and can beneﬁt researchers by establishing

baselines for further research activities.

Thus, we have followed these standard guidelines

and performed our search. At this point, it is impor-

tant to mention that the research question used for the

systematic mapping focused on the concept of how

leadership is taught in software engineering educa-

tion environments more generally, not constrained to

only active learning environments. This decision was

made to maximize the potential studies and ﬁndings

from this systematic mapping so that we could create

a body of knowledge regarding leadership teaching in

software engineering education by characterizing and

deﬁning it appropriately.

As stated previously, the research conducted aims

at characterizing and deﬁning leadership teaching in

software engineering education. As such, the research

questions to be addressed in this study are:

• (RQ1) “How is leadership teaching deﬁned in

agile software engineering education environ-

ments?”

• (RQ2) “How is leadership taught in agile soft-

ware engineering education environments?”

In order to answer these questions, a systematic

mapping was conducted. The review design was

based on some of the most relevant studies in the area

(Budgen et al., 2008; Petersen et al., 2008; Kitchen-

ham et al., 2011).

3.1 Data Source and Search Strategy

As a way of ﬁnding studies with high relevance to the

research questions proposed, we deﬁned our search

string following the guidelines proposed by (Kitchen-

ham, 2004). As such, the search string addresses

the population, intervention and outcome expected.

We have chosen exclude Comparison and Context as

the research conducted followed the principle of ex-

ploratory research. Table 1 summarizes the search

string used. It is important to mention that search

string could be adapted based on the limitations of the

database, such as limitation in the number of search

items. In this case, the last item from the outcome

portion of the string was to be removed.

Table 1: Search string.

Population (Agile Software Engineering OR

Agile Software Development OR

Agile Software)

AND

Intervention (Leadership)

AND

Outcome (Teaching OR Educating OR

Training OR Education)

As for the search strategy, we have also followed

the guidelines proposed by Kitchenham (Kitchenham

and Charters, 2007). Table 2 presents the summary

of the applied search strategy. All available databases

were selected with the exception of Citeseer library,

Inspec, due to difﬁculties using these platforms. The

minimum publication year was not set. The selection

criteria for the search was deﬁned based on the goal of

the study. Studies not written in English or not pub-

lished in any journal, conference, workshop or sym-

posia were not considered. Regarding the number of

pages, which usually reﬂects the depth of the analysis

conducted by the authors, we have chosen to accept a

minimum of 6 pages, as our intention was to capture

even results from preliminary studies.

Table 2: Search strategy.

Databases IEEExplore; ACM; Scopus;

searched El Compendex; Science@Direct

Selection available online; 6 pages minimum

criteria written in English; up to 2023

in: Journals/Conferences/Workshops/Symposia

Search Title; Abstract; Keywords

applied to

From this point, we have applied our search string

and used the search criteria previously speciﬁed (Ta-

ble 2) to all the speciﬁed databases. Regarding orga-

nization of the results, we have created a spreadsheet

which contained the necessary information, meaning

that we could apply the established inclusion and ex-

clusion criteria.

Each element in the spreadsheet contained meta-

data about the retrieved studies. Table 3 presents the

attributes assigned to each study. In addition to the

standard information of the studies, we have added

three additional attributes, which were related to the

possibility of exclusion of a given study. These at-

tributes were assigned based on other attributes from

the study, such as abstract and keywords.

Leadership Teaching in Agile Software Engineering: A Systematic Mapping

471

The goals of these attributes was to better catego-

rize studies and serve as our exclusion criteria, thus

answering three additional questions: “Is this study

duplicated?” to verify whether the study is duplicated

in the studies’ database, “Is this study relevant?” to

certify that the study is relevant to the subject of this

study after reading the study once and “Does this

study ﬁt in the criteria?” to verify whether the study

meets the Selection Criteria mentioned in Table 2.

Table 3: Metadata information of each study

Info. retrieved Explanation

Database Identiﬁer of the database

Title Study title

Authors List of all authors

Type of forum Journal/conference/workshop/symposium

Abstract Study abstract

Keywords Study keywords

Control 1 Duplicate

Control 2 Does not ﬁt into criteria

Control 3 Is relevant

In this sense, Table 4 presents the studies retrieved

from each base. Following the standard guidelines,

we have read every title, abstract and keywords of

the studies, answering the control questions (exclu-

sion criteria) for them. If the study was duplicated,

did not ﬁt inclusion criteria or was not relevant for

the review topic, the study was excluded. The read-

ing process was initially conducted by one researcher,

then veriﬁed independently by one other author.

Table 4: Search results.

Base Studies

Found

Selected Studies

(Abstract + Keywords)

Selected Studies

(Full Read)

ACM DL 449 43 13

IEEExplore 864 21 5

Science@Direct 528 20 2

El Compendex 25 10 1

Scopus 1594 38 6

Total 3460 132 27

From the total of 3460 studies found, our research

selected 132 studies which would be fully analyzed.

After fully reading these 132 studies (in a similar

manner to the previous step where one of the authors

read all studies and had other authors double-check

them), we further reduced our list of studies to 27. It

is important to note that the complete analysis of stud-

ies gave us better understanding of their research fo-

cus and thus enabled us to exclude 105 studies which

were not related to our research questions.

3.2 Data Extraction and Classiﬁcation

From the initial metadata assigned to the 27 selected

studies in the spreadsheet, we have also added some

additional attributes:

• Contribution Facet: type of contribution. Based on a

work from (Shaw, 2003);

• Research Method: the research method applied (case

study, survey etc);

• Research Type: type of research (based on work from

(Wieringa et al., 2005));

• Study Quality: a grade from 0 to 10, based on the work

from (Salleh et al., 2011). Details on Table 5;

• Contribution: the research contribution from the study.

3.3 Classiﬁcation Scheme

Regarding study quality, we have assigned a score for

each study, based on the work from (Salleh et al.,

2011). In this sense, eight (8) questions were used

to provide a grade to the work under analysis. Each

question could be either completely answered, mean-

ing the work will be assigned the complete score for

the question, partially answered, meaning that the

work will be assigned half the points for the ques-

tion, and not answered, meaning that the work will be

assigned zero points for the question.

We have chosen to better classify studies which

were closely related to our research questions, thus

each of these questions are worth 2 points. Once

a study is graded, it is assigned a quality category,

meaning that the study possesses:

• High quality: 8 to 10 points;

• Medium quality: between 5 and 8 points;

• Low quality: 0 to 5 points.

Based on the work from (Chanin et al., 2018a), we

have created a completed classiﬁcation scheme and

present it in Table 5.

4 RESULTS

Based on the 27 selected studies, we have performed

a classiﬁcation based on the scheme presented in Ta-

ble 5 and the results are presented in Table 6. Figure

1 presents the distribution of the analyzed work based

on the year of publication.

Figure 2 summarizes the results from the system-

atic mapping from the facets of research type, focus

and contribution of the 27 studies. The ﬁrst publica-

tion found is relatively old, published in 2005, which

indicates a spark of interest, but the ﬁgure indicates

that starting 2018, the amount of studies stayed at

a decent level (3.8 on average per year since 2018)

which could be an indicative that the theme has be-

come more relevant for the research community.

CSEDU 2025 - 17th International Conference on Computer Supported Education

472

Table 5: Classiﬁcation Scheme.

Category Description

Research Method Facet

Case Study Report from a speciﬁc situation being studied (Kitchenham et al., 1995).

Empirical Study Study based on empirical evidence (Perry et al., 2000).

Experimental Study Study in which an intervention is introduced to observe effects (Sjøberg et al., 2005).

Survey Process to collect data, analyze it and report results (Pﬂeeger and Kitchenham, 2001).

Research Type Facet

Evaluation Research Evaluation of a method or technique in practice.

Experience Study Personal experience of the author depicting how something has been done in practice.

Opinion Study Personal opinion on a certain technique.

Philosophical Study New way of looking at an existing context.

Solution Proposal The proposition of a solution to a problem.

Validation Research New techniques being implemented in experiments, simulations or in practice.

Focus Facet

Classroom The focus is on classroom education strategies for leadership teaching in SE.

Real Projects The focus is leadership teaching in SE on real-world project execution.

Synthesis Focus is a review of primary (or secondary) studies on leadership teaching in SE.

Contribution Facet

Advice/Implication Recommendations based on personal opinions.

Framework/Method Framework/Method used to teach (or to learn).

Guidelines Advices based on the research results.

Lessons Learned Actionable advices derived from the obtained research results.

Model Representation of a given context based on a conceptualized process.

Tool Tools used to teach (or to learn).

Study Quality Facet

References Are the references adequate and well-cited? (1 point)

Goal Is the goal clearly stated? (1 point)

Sample Observation Data collection and sample strategy was carried out correctly? (1 point)

Research Method The analysis methodology was well applied? (1 point)

Clear Description Is the context of the study clearly described? (1 point)

Findings Are ﬁndings credible? (1 point)

RQ1 Does the study answer RQ1? (2 points)

RQ2 Does the study answer RQ2? (2 points)

Table 6: Overview of results.

Authors [year] Research method Research type Focus Contribution Study

Quality

(Noguera et al., 2018) Mixed Experience Study Teaching Lessons Learned 10

(Khakurel and Porras, 2020) Empirical Study Experience Study Real Projects Lessons Learned 10

(Paasivaara, 2021) Case Study Experience Study Real Projects Lessons Learned 9

(Vivian et al., 2013) Survey Evaluation Research Teaching Guidelines 9

(Christensen and Paasivaara, 2022) Empirical Study Experience Study Real Projects Lessons Learned 9

(Fontão et al., 2019) Mixed Evaluation Research Teaching Lessons Learned 9

(Li et al., 2023) Survey Experience Study Teaching Lessons Learned 9

(Ceh-Varela et al., 2023) Empirical Study Experience Study Teaching Guidelines 9

(Libreros et al., 2020) Experimental Study Solution Proposal Teaching Framework/Method 9

(Heggen and Myers, 2018) Case Study Evaluation Research Real Projects Framework/Method 8

(Ha et al., 2019) Mixed Evaluation Research Teaching Lessons Learned 7

(Schneider et al., 2020) Case Study Validation Research Teaching Model 7

(Tenhunen et al., 2023) Empirical Study Solution Proposal Real Projects Lessons Learned 7

(Hogan and Thomas, 2005) Survey Evaluation Research Real Projects Guidelines 7

(Johnson et al., 2020) Survey Validation Research Teaching Framework/Method 6

(Kapitsaki and Loizou, 2018) Survey Experience Study Real Projects Lessons Learned 6

(Poženel, 2013) Case Study Evaluation Research Teaching Framework/Method 6

(Watson and Cutting, 2022) Empirical Study Evaluation Research Real Projects Guidelines 6

(Sundaram, 2023) Survey Experience Study Teaching Framework/Method 6

(Boiangiu and St

anic

a, 2019) Empirical Study Experience Study Teaching Model 5

(Paiva and Carvalho, 2018) Empirical Study Experience Study Teaching Framework/Method 5

(Budu, 2018) Empirical Study Validation Research Teaching Lessons Learned 5

(Peters and Moreno, 2015) Empirical Study Philosophical Study Synthesis Guidelines 4

(Kawano et al., 2019) Empirical Study Opinion Study Teaching Framework/Method 4

(Moh’d A, 2021) Empirical Study Philosophical Study Teaching Guidelines 3

(Moreno et al., 2022) Empirical Study Experience Study Teaching Lessons Learned 2

(Escudeiro et al., 2020) Empirical Study Experience Study Real Projects Framework/Method 1

Leadership Teaching in Agile Software Engineering: A Systematic Mapping

473

Figure 1: Distribution of selected studies by year.

In a general sense, majority of the studies found

were classiﬁed as “High” with regard to our “study

quality” facet. This indicates that the teaching of

leadership in software engineering is a topic which

is being undertaken by the scientiﬁc community and

robust studies are addressing it. In addition, speciﬁ-

cally regarding the Focus facet, we can clearly see that

there are studies many studies being conducted with

regard to teaching leadership in software engineering.

This is an indicative that the software engineering ed-

ucation research community is interested in the topic

and conducting efforts to teach leaderships skills in

software engineering.

After fully reading and comprehending the se-

lected studies, we have proceed to extract data to an-

swer our proposed research questions. This discus-

sion is presented next.

4.1 RQ1 - How Is Leadership Teaching

Deﬁned in Agile Software

Engineering Education

Environments?

There are many deﬁnitions to what could be consid-

ered leadership teaching the studies we have found.

In general, we have found 4 categories of deﬁnition

in the studies analyzed. Those deﬁne leadership as:

4.1.1 Part of Teamwork and Shared Among

Team Members

(Noguera et al., 2018), based on (Eubanks et al.,

2016), deﬁned leadership as encompassing “task

management” and “team development”.The study

emphasizes teamwork, with leadership as an impor-

tant component of teamwork. Speciﬁcally, the study

proposed two roles in an agile software development

educational context, Project Manager and “Work-

Cycle” manager, where each one of these two roles

is responsible for management and leadership tasks.

(Vivian et al., 2013) use the deﬁnition of lead-

ership as being an emergent trait of self-organizing

teams when conducting “teamwork”. This deﬁnition

is based on the concept of “Team Leadership” from

(Dickinson and McIntyre, 1997) and states leadership

as a component of teamwork which “involves provid-

ing direction, structure, and support for other team

members. It does not necessarily refer to a single

individual with formal authority over others; several

members can show team leadership”.

Similarly, (Poženel, 2013) deﬁnes leadership us-

ing the concept of shared leadership from (Moe et al.,

2009) where among many speciﬁcs, important deci-

sion making is shared among all team members. Ex-

cessive centralization is discouraged (e.g., decision

making made by a single team member) as well as

excessive decentralization (e.g., tasks not being at-

tributed to speciﬁc team members).

(Hogan and Thomas, 2005) acknowledge the ex-

istence of formal and informal roles regarding leader-

ship, in which a formal role refers to when the role

is explicitly assigned to a team member (e.g., SM)

and informal refers to when there is not explicit as-

signment of roles, but a team member exhibits leader-

ship behavior and performs leadership tasks (this for-

mal/informal dichotomy could be an indicative of the

concept of shared leadership found in the other stud-

ies).

4.1.2 Associated with Scrum

(Paasivaara, 2021), in a study applying Scrum in ed-

ucation, has deﬁned that the Scrum Master (SM) is a

leading team member in the initial phases of the de-

velopment, after which leadership can become shared

among other team members. Furthermore, the study

indicates that a shared leadership is an indication of

a mature team. The deﬁnition of leadership as a role

also appears in (Fontão et al., 2019), in which authors

describes leadership as being a role of the SM in a

Scrum team and further deﬁning the SM as a “techni-

cal leadership”.

Furthermore, in (Li et al., 2023) which also add

that some personality traits such as openness and

agreeableness may be relevant for a leading SM. (Li-

breros et al., 2020) report a study in which Team

Leader Rotation was adopted and Scrum teams had a

team member denominated “team leader” (different

from the SM and/or PO). As the study was conducted

in a Scrum context, the team leaders in the study were

acting as a complementary role to the SMs and the

POs.

4.1.3 Representing the Group in Academic

Settings

(Budu, 2018) used a deﬁnition of a member of the

team who had the responsibility to present results for

CSEDU 2025 - 17th International Conference on Computer Supported Education

474

Figure 2: Summary of the studies. X axis represents facets of the studies (research type, focus and contribution) and the Y

axis represents study quality

their working group to the class. This deﬁnition im-

plies a very academic setting. (Khakurel and Porras,

2020) deﬁne leadership as a trait of being more “re-

sponsible”, managing the project and handling cus-

tomer interactions. In the study, the role adopted by

students participating the study who reported on lead-

ership was of a project manager.

4.1.4 Not Explicitly Deﬁned

(Christensen and Paasivaara, 2022) created a deﬁni-

tion based both on the work from (Matturro et al.,

2019) and the context of their study. This concept can

be summarized in “the ability to lead and supervise

others”. The study was conducted in a course which

students were intended to learn soft skills, among of

which was leadership.

(Sundaram, 2023) deﬁnes leadership in the study

by comparing the difference between a “leader” and

a “manager”. A manager being the role which tends

to “push” the team and focuses on the work being

delivered, while the leader is stated to “guide” team

members and to put more emphasis on aiding team

members themselves.

(Kawano et al., 2019) applies the deﬁnition of

leader for the “next generation software develop-

ment”. This concept is not further speciﬁed, so it

somewhat vague. In addition to this, the author also

deﬁnes leadership as when a student is interested in

leading junior colleagues.

(Moh’d A, 2021) deﬁnes leadership as being able

to both manage and lead, in the context of a profes-

sional denominated software project manager. This

deﬁnition is further speciﬁed as encompassing pro-

viding supervision, motivation, monitoring and keep-

ing track of the project.

4.2 RQ2 - How Is Leadership Taught in

Agile Software Engineering

Education Environments?

Results indicate convergence on how leadership is

taught in software engineering education. We have

found 4 manners in which leadership is taught.

4.2.1 Using Scrum

Majority of the studies that we have analyzed incor-

porate Scrum as their software development method-

ology and use its roles (Product Owner, Scrum Master

etc.) to provide students with the opportunity to de-

velop “soft skills”. Among these soft skills, there is

leadership.

For example, (Noguera et al., 2018) have taught

leadership in software engineering by incorporat-

ing agile in education, speciﬁcally, an adaption of

the Scrum framework (Schwaber and Sutherland,

2011). (Paasivaara, 2021) has used professional agile

coaches and communities of practice (CoP). CoP are

exchange sessions that the students who are learning

to be SM participate and exchange ideas. The projects

developed in the are provided by real industry com-

panies and external agile coaches help the assigned

SM (who is a student of the course). (Christensen

and Paasivaara, 2022) teach soft skills through a dis-

Leadership Teaching in Agile Software Engineering: A Systematic Mapping

475

tributed software development course which applied

a Casptone project. It used Scrum as its develop-

ment framework. The projects were provided by real

Danish companies. (Heggen and Myers, 2018) have

taught through practical experience in real software

projects that address community and/or university de-

partments’ needs. All development is performed us-

ing Scrum as the primary framework. (Fontão et al.,

2019) applied project-based learning (PBL) in a Cap-

stone project in combination with Scrum. (Li et al.,

2023) also uses Scrum and proposes a multi-team

Capstone project to provide real experience to stu-

dents, where a project is developed by more than one

team. (Libreros et al., 2020) have taught adopting

team leader rotation in agile software development.

Scrum is applied as the chosen development process.

(Johnson et al., 2020) have taught through a course

that simulates real-world environment. Scrum is ap-

plied as the chosen development process. (Paiva and

Carvalho, 2018) have taught using Capstone Projects

and Scrum software development. (Poženel, 2013)

have assessed student who worked on large capstone

courses. Scrum is applied as the chosen development

process. (Sundaram, 2023) have taught using tradi-

tional teaching, but Scrum is studied and simulated

by students.

4.2.2 Using Active Learning Methodologies

Another ﬁnding is that leadership teaching is usually

performed using active learning strategies (e.g., PBL).

For example, (Ceh-Varela et al., 2023) used

project-based learning in the development of a soft-

ware project. The software development methodol-

ogy applied by students is deﬁned as “relaxed plan-

based model”, a combination of cascade, spiral and

prototype model. (Hogan and Thomas, 2005) have

taught using problem based learning in addition to

real projects that connect students to the industry. Ag-

ile software development is applied. Furthermore,

(Fontão et al., 2019) applied project based learning

in a Capstone project in combination with Scrum.

4.2.3 Using Real Projects Either Originating

from External Partners or Which Propose

to Solve Real-World Problems

Real projects, either proposed by industry partners or

solving real-world problems, being incorporated in

the teaching process was also reported in our ﬁnd-

ings. For instance, (Khakurel and Porras, 2020) have

taught through Capstone projects, with real projects

from Finish companies. (Schneider et al., 2020) have

taught through Capstone projects, adopting industry

practices in the development process. The model

adopted is inspired by Spotify’s “Tribes and Squads”

(Alqudah and Razali, 2016). (Watson and Cutting,

2022) have taught using capstone project. Projects

could be from the industry Agile software develop-

ment is incentivized. (Tenhunen et al., 2023) have

taught through real world projects. This was achieved

via a “Software Development Academy” (SDA), a

startup concept inside the university with internal

projects developed by student. Students are paid to

participate in the SDA. (Kapitsaki and Loizou, 2018)

have taught by working on Real project and in teams

that mix undergraduate and postgraduate students.

The integration of Minimum Viable Products and

continuous experimentation in real-world projects has

shown to be an effective strategy for teaching practi-

cal software engineering skills (Melegati et al., 2020).

4.2.4 Using Other Learning Methodologies

and/or Teaching Strategies

Two of the studies we have found to use other learn-

ing methodologies and/or teaching strategies method-

ologies for teaching. (Boiangiu and St

anic

a, 2019)

present a conceptual model that can be instantiated

depending on the “type” of general-purpose edu-

cation envisioned. (Ha et al., 2019) used a con-

cept named “Conceive-Design-Implement-Operate”

approach (CDIO), with two levels. Level 1 addresses

simple projects and fundamental knowledge, while

level 2 addresses complex projects and advanced

knowledge. (Vivian et al., 2013) have performed two

online collaborative sessions where students had to

solve a “difﬁcult” problem by creating a document

which contained answers. From the results and over-

all presentation of the ideas of the studies we found

during the analysis step, we have proceeded to dis-

cussion on our ﬁndings.

5 DISCUSSION

In this section, we discuss some of the results ob-

tained from our mapping from the perspective of our

research questions and the general implications of

these ﬁndings.

From the analyzed data, it was possible to ﬁnd

different deﬁnitions for the teaching of leadership in

software engineering education. Many of the authors

have deﬁned leadership as a component that is inte-

grated into teamwork and thus is shared among team

members (Noguera et al., 2018; Vivian et al., 2013;

Poženel, 2013; Hogan and Thomas, 2005).

Furthermore, Scrum has been a base for deﬁning

leadership “roles” in software engineering education.

CSEDU 2025 - 17th International Conference on Computer Supported Education

476

Although using Scrum is expected as it the most used

agile framework in the industry 63% of agile teams

(of Agile, 2023), this could indicate that the roles pro-

vided by Scrum (e.g., Scrum Master, Product Owner)

serve as a comprehensive set of skills for students to

develop leadership abilities. For example, practices

such as Behavior-Driven Development (BDD) have

been shown to enhance team collaboration and lead-

ership development when integrated with agile frame-

works like Scrum (Nascimento et al., 2020).

Our data also revealed that being a “leader” from

a software engineering education perspective can also

be associated with performing group presentations

and interactions with external actors (Budu, 2018;

Khakurel and Porras, 2020). This is a traditional ap-

proach to group education and revolves around as-

signing responsibility to a team member as a manner

of teaching this skill to the assignee.

Another interesting ﬁnding was that in software

engineering education, it is not unusual to deﬁne lead-

ership more generically, such as “being able to lead

a team”, with specifying the details of what exactly

this implies (Christensen and Paasivaara, 2022; Sun-

daram, 2023; Kawano et al., 2019; Moh’d A, 2021).

Further, provided that other authors propose leader-

ship as a component of teamwork, this ﬁnding could

be a symptom of the difﬁculty of isolating leadership

from teamwork in software engineering education.

In terms of how to teach leadership in software

engineering education, Scrum appeared as the most

adopted development methodology (Noguera et al.,

2018; Schwaber and Sutherland, 2011; Paasivaara,

2021; Christensen and Paasivaara, 2022; Heggen and

Myers, 2018; Fontão et al., 2019; Li et al., 2023; Li-

breros et al., 2020; Johnson et al., 2020; Paiva and

Carvalho, 2018; Poženel, 2013; Sundaram, 2023).

Finally, regarding active learning, many of the

studies adopt active learning as the preferred teach-

ing strategy. Collaborative approaches, such as

Challenge-Based Learning (CBL), have proven ef-

fective in fostering leadership and teamwork skills

within software engineering education (Chanin et al.,

2018b). As these methodologies are student-centered,

it is not surprising that they are adopted to provide

students with practical experience with leadership.

6 LIMITATIONS

This study contributes insights into leadership teach-

ing in agile software engineering. However, it is nec-

essary to recognize its limitations regarding reliabil-

ity, construction/internal/external validity, which may

inﬂuence the interpretation and generalization of the

ﬁndings (Runeson and Höst, 2009).

Construction Validity: The operationalization of

key concepts may not fully capture the complex and

multifaceted nature of leadership in software engi-

neering. We minimize this by looking into the most

commonly adopted digital libraries.

Internal Validity: While the systematic approach

aimed to minimize biases and errors in selecting and

synthesizing studies, it is possible that researchers

might have been inﬂuenced to ﬁnd leadership con-

cepts in the analyzed studies. To mitigate this, ini-

tially one of the researchers conducted the analysis

steps separately and independently. After results were

obtained, an alignment meeting was conducted to dis-

cuss doubts and reach consensus.

External Validity: Generalization of our ﬁndings

is constrained by the focus on agile software engi-

neering education. This limitation restricts the appli-

cability of our results to educational contexts in which

agile software engineering is applied.

Reliability: The reproducibility of this study’s

ﬁndings may be inﬂuenced by the dynamic nature of

software engineering and leadership practices, which

are continually evolving. To mitigate this, we have

provided all the parameters applied in our mapping

study so that other researchers are able to replicate it.

7 CONCLUSION

This study presented the results from a systematic

mapping about teaching leadership in software engi-

neering education. The results were analyzed from

the perspective of two researched questions.

Upon meticulous evaluation of 27 studies selected

for their relevance to the proposed research topic,

we discerned preliminary indicators highlighting key

facets of leadership instruction within software engi-

neering education. Firstly, it is discernible that leader-

ship is commonly deﬁned as an integral component of

teamwork, distributed among team members and as-

sociated with Scrum, thereby providing students with

practical experiences of group representation. Sec-

ondly, it is mostly taught using Scrum, involved in ac-

tive learning strategies, such as problem-based learn-

ing, and incorporating real-world projects, either pro-

vided by external partners or aimed at addressing real-

world challenges.

As for future work, we intend to propose a leader-

ship teaching framework that incorporates these ﬁnd-

ings and perform a case study in software engineering

education environment.

Leadership Teaching in Agile Software Engineering: A Systematic Mapping

477

ACKNOWLEDGMENT

This study was partially supported by the Ministry

of Science, Technology, and Innovations from Brazil,

with resources from Law No. 8.248, dated October

23, 1991, within the scope of PPI-SOFTEX, coordi-

nated by Softex.

REFERENCES

Ahmed, F., Capretz, L. F., Bouktif, S., and Campbell, P.

(2015). Soft skills and software development: A re-

ﬂection from the software industry. arXiv preprint

arXiv:1507.06873.

Alqudah, M. and Razali, R. (2016). A review of scaling

agile methods in large software development. Inter-

national Journal on Advanced Science, Engineering

and Information Technology, 6(6):828–837.

Athukorala, C., Perera, I., and Meedeniya, D. (2016). The

impact of transformational and transactional leader-

ship styles on knowledge creation in sri lankan soft-

ware industry. In 2016 Moratuwa Engineering Re-

search Conference (MERCon), pages 309–314. IEEE.

Barry, E. J., Mukhopadhyay, T., and Slaughter, S. A. (2002).

Software project duration and effort: an empirical

study. Journal of Information Technology and Man-

agement, 3(1-2):113–136.

Bass, B. M., Avolio, B. J., Jung, D. I., and Berson, Y.

(2003). Predicting unit performance by assessing

transformational and transactional leadership. Jour-

nal of applied psychology, 88(2):207.

Bass, B. M. and Bass Bernard, M. (1985). Leadership and

performance beyond expectations. Free press New

York.

Beck, K. (2000). Extreme programming explained: em-

brace change. Addison-Wesley Longman.

Bickle, J. T. (2017). Developing remote training consultants

as leaders—dialogic/network application of path-goal

leadership theory in leadership development. Perfor-

mance Improvement, 56(9):32–39.

Boiangiu, C.-A. and St

anic

a, I.-C. (2019). The mosaics

model of educational approaches for teaching the

practice of software project management. Education

Sciences, 9(1):26.

Budgen, D., Turner, M., Brereton, P., and Kitchenham,

B. A. (2008). Using mapping studies in software en-

gineering. In Ppig, volume 8, pages 195–204.

Budu, J. (2018). Applying agile principles in teaching un-

dergraduate information technology project manage-

ment. Int. Journal of Information and Communication

Technology Education, 14(3):29–40.

Ceh-Varela, E., Canto-Bonilla, C., and Duni, D. (2023). Ap-

plication of project-based learning to a software engi-

neering course in a hybrid class environment. Infor-

mation and Software Technology, 158:107189.

Chanin, R., Sales, A., Pompermaier, L., and Prikladnicki,

R. (2018a). A systematic mapping study on software

startups education. In Proceedings of the 22nd Inter-

national Conference on Evaluation and Assessment in

Software Engineering, pages 163–168.

Chanin, R., Sales, A., Santos, A. R., Pompermaier, L. B.,

and Prikladnicki, R. (2018b). A collaborative ap-

proach to teaching software startups: ﬁndings from

a study using challenge based learning. In Sharp,

H., de Souza, C. R. B., Graziotin, D., Levy, M., and

Socha, D., editors, Proc. of the 11th International

Workshop on Cooperative and Human Aspects of Soft-

ware Engineering, ICSE 2018, Gothenburg, Sweden,

May 27 - June 03, 2018, pages 9–12. ACM.

Christensen, E. L. and Paasivaara, M. (2022). Learning soft

skills through distributed software development. In

Proceedings of the International Conference on Soft-

ware and System Processes and International Confer-

ence on Global Software Engineering, pages 93–103.

da Silva, F. Q., Monteiro, C. V., dos Santos, I. E., and

Capretz, L. F. (2016). How software development

group leaders inﬂuence team members’ innovative be-

havior. IEEE Software, 33(5):106–109.

Dewan, S. and Dewan, D. (2010). Distance education

teacher as a leader: Learning from the path goal lead-

ership theory. Journal of Online Learning and Teach-

ing, 6(3):673–685.

Dickinson, T. L. and McIntyre, R. M. (1997). A conceptual

framework for teamwork measurement. Team perfor-

mance assessment and measurement, pages 19–43.

Dingsøyr, T., Nerur, S., Balijepally, V., and Moe, N. B.

(2012). A decade of agile methodologies: Towards

explaining agile software development.

Escudeiro, N., Barata, A., Escudeiro, P., Welzer, T.,

Almeida, R., and Papadourakis, G. (2020). Blended

academic international mobility: tearing down bar-

riers to mobility in a sustainable way. In 2020

IEEE Global Engineering Education Conference

(EDUCON), pages 1434–1443. IEEE.

Eubanks, D. L., Palanski, M., Olabisi, J., Joinson, A., and

Dove, J. (2016). Team dynamics in virtual, partially

distributed teams: Optimal role fulﬁllment. Comput-

ers in Human Behavior, 61:556–568.

Faraj, S. and Sambamurthy, V. (2006). Leadership of infor-

mation systems development projects. IEEE Transac-

tions on engineering management, 53(2):238–249.

Fontão, A., Gadelha, B., and Júnior, A. C. (2019). Bal-

ancing theory and practice in software engineering

education–a pbl, toolset based approach. In IEEE

Frontiers in Education Conference, pages 1–8. IEEE.

Fowler, M., Highsmith, J., et al. (2001). The agile mani-

festo. Journal of Software Development, 9(8):28–35.

Furumo, K., de Pillis, E., and Buxton, M. (2012). The im-

pact of leadership on participation and trust in virtual

teams. In Proceedings of the 50th annual conference

on Computers and People Research, pages 123–126.

Goyal, D., Cortinovis, R., and Capretz, L. F. (2022). A

framework for class activities to cultivate responsible

leadership in software engineering students. In Proc.

of the 15th Int. Conf. on Cooperative and Human As-

pects of Software Engineering, pages 96–101.

CSEDU 2025 - 17th International Conference on Computer Supported Education

478

Ha, N.-H., Nayyar, A., Nguyen, D.-M., and Liu, C.-A.

(2019). Enhancing students’ soft skills by implement-

ing cdio-based integration teaching mode. In The 15th

International CDIO Conference, page 569.

Heggen, S. and Myers, C. (2018). Hiring millennial stu-

dents as software engineers: a study in developing

self-conﬁdence and marketable skills. In Proceedings

of the 2nd International Workshop on Software Engi-

neering Education for Millennials, pages 32–39.

Hidayati, A., Budiardjo, E. K., and Purwandari, B. (2020).

Hard and soft skills for scrum global software devel-

opment teams. In Proceedings of the 3rd International

Conference on Software Engineering and Information

Management, pages 110–114.

Hogan, J. M. and Thomas, R. (2005). Developing the soft-

ware engineering team. In Proceedings of the 7th Aus-

tralasian conference on Computing education-Volume

42, pages 203–210.

House, R. J. and Mitchell, T. R. (1975). Path goal theory of

leadership. Faculty of Management Studies, Univer-

sity of Toronto.

Johnson, W. G., Sunderraman, R., and Bourgeois, A. G.

(2020). Teaching strategies in software engineering

towards industry interview preparedness. In Proceed-

ings of the 9th Computer Science Education Research

Conference, pages 1–11.

Kapitsaki, G. M. and Loizou, S. K. (2018). Bringing

together undergraduate and postgraduate students in

software engineering team project: Experiences and

lessons. In Proc. of the 23rd Annual ACM Conference

on ITiCSE, pages 320–325.

Kawano, A., Motoyama, Y., and Aoyama, M. (2019). A lx

(learner experience)-based evaluation method of the

education and training programs for professional soft-

ware engineers. In Proceedings of the 2019 7th Int.

Conf. on Inf. and Ed. Technology, pages 151–159.

Khakurel, J. and Porras, J. (2020). The effect of real-world

capstone project in an acquisition of soft skills among

software engineering students. In 2020 IEEE 32nd

Conference on Software Engineering Education and

Training (CSEE&T), pages 1–9. IEEE.

Kitchenham, B. (2004). Procedures for performing sys-

tematic reviews. Keele, UK, Keele University,

33(2004):1–26.

Kitchenham, B. and Charters, S. (2007). Guidelines for per-

forming systematic literature reviews in software en-

gineering. Tech report, Keele University and Durham

University.

Kitchenham, B., Pickard, L., and Pﬂeeger, S. L. (1995).

Case studies for method and tool evaluation. Journal

of Software, 12(4):52–62.

Kitchenham, B. A., Budgen, D., and Brereton, O. P.

(2011). Using mapping studies as the basis for further

research–a participant-observer case study. Informa-

tion and Software Technology, 53(6):638–651.

Li, Y., Tan, C.-H., and Teo, H.-H. (2012). Leadership char-

acteristics and developers’ motivation in open source

software development. Information & Management,

49(5):257–267.

Li, Z. S., Arony, N. N., Devathasan, K., and Damian,

D. (2023). " software is the easy part of software

engineering"–lessons and experiences from a large-

scale, multi-team capstone course. arXiv preprint

arXiv:2302.05536.

Libreros, J., Viveros, I., Trujillo, M., Gaona, M., and

Cuadrado, D. (2020). Improving soft skills in agile

software development by team leader rotation. In In-

ternational Congress on Information and Communi-

cation Technology, pages 186–194. Springer.

Malik, S. H., Aziz, S., and Hassan, H. (2014). Leadership

behavior and acceptance of leaders by subordinates:

Application of path goal theory in telecom sector. Int.

Journal of Trade, Economics and Finance, 5(2):170.

Marquez, J. M. D., Aguja, S. E., and Prudente, M. S. (2022).

Evaluation of student leadership development amidst

online distance learning set-up. In Proceedings of the

2022 13th Int. Conf. on E-Education, E-Business, E-

Management, and E-Learning, pages 118–123.

Matturro, G., Raschetti, F., and Fontán, C. (2015). Soft

skills in software development teams: A survey of the

points of view of team leaders and team members. In

2015 IEEE/ACM 8th Int. Work. on Cooperative and

Human Aspects of Soft. Eng., pages 101–104. IEEE.

Matturro, G., Raschetti, F., and Fontán, C. (2019). A sys-

tematic mapping study on soft skills in software engi-

neering. J. Univers. Comput. Sci., 25(1):16–41.

Melegati, J., Chanin, R., Sales, A., Prikladnicki, R., and

Wang, X. (2020). MVP and experimentation in soft-

ware startups: a qualitative survey. In 46th Euromicro

Conference on Software Engineering and Advanced

Applications, SEAA 2020, Portoroz, Slovenia, August

26-28, 2020, pages 322–325. IEEE.

Melegati, J., Chanin, R., Wang, X., Sales, A., and Prik-

ladnicki, R. (2019). Enablers and inhibitors of ex-

perimentation in early-stage software startups. In

Franch, X., Männistö, T., and Martínez-Fernández, S.,

editors, Product-Focused Software Process Improve-

ment - 20th International Conference, PROFES 2019,

Barcelona, Spain, November 27-29, 2019, Proceed-

ings, volume 11915 of Lecture Notes in Computer Sci-

ence, pages 554–569. Springer.

Modi, S. and Strode, D. (2020). Leadership in agile soft-

ware development: a systematic literature review. In

Proceedings of the Australasian Conference on Infor-

mation Systems, pages 1–12.

Moe, N. B., Dingsøyr, T., and Røyrvik, E. A. (2009).

Putting agile teamwork to the test–an preliminary in-

strument for empirically assessing and improving ag-

ile software development. In Agile Processes in Soft-

ware Engineering and Extreme Programming: 10th

Int. Conf., XP 2009, Pula, Sardinia, Italy, May 25-29,

2009. Proceedings 10, pages 114–123. Springer.

Moh’d A, R. (2021). Shifting the paradigms from teach-

ing project management to teaching software project

management at jordan university of science and tech-

nology based on the ieee software engineering man-

agement knowledge area. In 2021 International Con-

ference on Computational Science and Computational

Intelligence (CSCI), pages 1072–1078. IEEE.

Leadership Teaching in Agile Software Engineering: A Systematic Mapping

479

Moreno, E. D., Fernandes, J. M., Alves, V., Leon Olave,

M. E., and Afonso, P. (2022). Transforming ideas and

developing entrepreneurship skills in computing sci-

ences and informatics engineering courses. In Pro-

ceedings of the 11th Euro American Conference on

Telematics and Information Systems, pages 1–6.

Nascimento, N., Santos, A. R., Sales, A., and Chanin, R.

(2020). Behavior-driven development: A case study

on its impacts on agile development teams. In ICSE

’20: 42nd International Conference on Software En-

gineering, Workshops, Seoul, Republic of Korea, 27

June - 19 July, 2020, pages 109–116. ACM.

Noguera, I., Guerrero-Roldán, A.-E., and Masó, R. (2018).

Collaborative agile learning in online environments:

Strategies for improving team regulation and project

management. Computers & Education, 116:110–129.

of Agile, S. (2023). The 17th state of agile report.

Technical report, https://info.digital.ai/rs/981-LQX-

968/images/RE-SA-17th-Annual-State-Of-Agile-

Report.pdf?version=0.

Paasivaara, M. (2021). Teaching the scrum master role

using professional agile coaches and communities of

practice. In 2021 IEEE/ACM 43rd Int. Conf. on Soft-

ware Engineering: Software Engineering Education

and Training (ICSE-SEET), pages 30–39. IEEE.

Paiva, S. C. and Carvalho, D. B. F. (2018). Software

creation workshop: A capstone course for business-

oriented software engineering teaching. In Proc. of

the XXXII SBES, pages 280–288.

Perry, D., Porter, A., and Votta, L. (2000). Empirical studies

of software engineering: a roadmap. In Proceedings

of the 1st Conference on the Future of Software Engi-

neering, pages 345–355.

Peters, L. and Moreno, A. M. (2015). Educating software

engineering managers-revisited what software project

managers need to know today. In 2015 IEEE/ACM

37th IEEE International Conference on Software En-

gineering, volume 2, pages 353–359. IEEE.

Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M.

(2008). Systematic mapping studies in software en-

gineering. In 12th international conference on evalu-

ation and assessment in software engineering (EASE).

BCS Learning & Development.

Pﬂeeger, S. L. and Kitchenham, B. (2001). Principles of sur-

vey research: part 1: turning lemons into lemonade.

Journal of Software Engineering Notes, 26(6):16–18.

Podsakoff, P. M., Todor, W. D., Grover, R. A., and Huber,

V. L. (1984). Situational moderators of leader reward

and punishment behaviors: Fact or ﬁction? Organiz.

behavior and human performance, 34(1):21–63.

Poženel, M. (2013). Assessing teamwork in a software en-

gineering capstone course. World Transactions on En-

gineering and Technology Education, 11(1):6–12.

Przybilla, L., Präg, A., Wiesche, M., and Krcmar, H. (2020).

A conceptual model of antecedents of emergent lead-

ership in agile teams. In Proceedings of the 2020 on

Computers and People Research Conference, pages

164–165.

Przybilla, L., Wiesche, M., and Krcmar, H. (2019). Emer-

gent leadership in agile teams–an initial exploration.

In Proc. of the 2019 on Computers and People Re-

search Conference, pages 176–179.

Runeson, P. and Höst, M. (2009). Guidelines for conduct-

ing and reporting case study research in software engi-

neering. Empirical software engineering, 14(2):131–

164.

Salleh, N., Mendes, E., and Grundy, J. (2011). Em-

pirical studies of pair programming for cs/se teach-

ing in higher education: a systematic literature re-

view. Journal of Transactions on Software Engineer-

ing, 37(4):509–525.

Sangwan, R. S. and Ros, J. (2008). Architecture leader-

ship and management in globally distributed software

development. In Proc. of the 1st Int. Work. on Lead-

ership and Manag. in Soft. Architecture, pages 17–22.

Schneider, J.-G., Eklund, P. W., Lee, K., Chen, F., Cain, A.,

and Abdelrazek, M. (2020). Adopting industry agile

practices in large-scale capstone education. In Pro-

ceedings of the ACM/IEEE 42nd International Con-

ference on Software Engineering: Software Engineer-

ing Education and Training, pages 119–129.

Schwaber, K. and Sutherland, J. (2011). The scrum guide.

Scrum Alliance.

Shaw, M. (2003). Writing good software engineering re-

search papers: minitutorial. In Proc. of the 25th Int.

Conf. on Software Engineering, pages 726–736.

Sjøberg, D. I., Hannay, J. E., Hansen, O., Kampenes, V. B.,

Karahasanovic, A., Liborg, N.-K., and Rekdal, A. C.

(2005). A survey of controlled experiments in soft-

ware engineering. Journal of Transactions on Soft-

ware Engineering, 31(9):733–753.

Sundaram, R. (2023). Incorporation of signiﬁcant project

experiences within the undergraduate engineering cur-

riculum. In 2023 ASEE Annual Conf. & Exposition.

Tenhunen, S., Männistö, T., Ihantola, P., Kousa, J., and

Luukkainen, M. (2023). Software startup within a

university–producing industry-ready graduates. arXiv

preprint arXiv:2301.07020.

Van Kelle, E., Visser, J., Plaat, A., and van der Wijst, P.

(2015). An empirical study into social success factors

for agile software development. In 2015 IEEE/ACM

8th Int. Work. on Cooperative and Human Aspects of

Soft. Eng., pages 77–80. IEEE.

Vivian, R., Falkner, K., and Falkner, N. (2013). Analysing

computer science students’ teamwork role adoption in

an online self-organised teamwork activity. In Proc.s

of the 13th Koli Calling Int. Conf. on Computing Edu-

cation Research, pages 105–114.

Watson, E. M. and Cutting, D. (2022). Engagement contexts

of software engineering education projects. In 31st

Annual Conf. of the European Ass. for Ed. in Elect.

and Inf. Eng. (EAEEIE), pages 1–6. IEEE.

Wieringa, R., Maiden, N., Mead, N., and Rolland, C.

(2005). Requirements engineering paper classiﬁcation

and evaluation criteria: a proposal and a discussion.

Journal of Requirements Engineering, 11(1):102–107.

CSEDU 2025 - 17th International Conference on Computer Supported Education

480