Collaborative Strategy for Software Engineering Courses at

a South American University

Miguel Alfonso Feijóo-García

1 a

, Helio Henry Ramírez-Arévalo

1 b

and Pedro Guillermo Feijóo-García

1,2 c

Program of Systems Engineering, Universidad El Bosque, Bogotá, Colombia

Department of CISE, University of Florida, Gainesville, FL, U.S.A.

Keywords: Collaborative Learning, Peer-instruction, Software Engineering Education, Inter-curricular.

Abstract: Software Engineering (SE) is the discipline that integrates theory, methods, and tools to promote the

development of new informatic solutions for multiple contexts. The discipline is generally introduced in

Computer Science (CS) programs between the sophomore and junior years, adding the human being as an

actor who participates in teamwork strategies to optimize time and effort. We report on an inter-curricular

collaborative instructional strategy between two subsequent SE core courses—SE1 and SE2, at Universidad

El Bosque, Colombia. We evaluated our strategy considering students’ performance and perceptions, basing

our analysis on their grades, Likert scale (1-5) responses, and the sentiment of their open-ended feedback—

we calculated it with Natural Language Processing (NLP) techniques. Our findings suggest that an inter-

curricular strategy like the one we present can foster students’ performance, engagement, and motivation.

Moreover, the strategy supports the promotion of SE skills, such as communication and teamwork.

1 INTRODUCTION

Software Engineering (SE) is the discipline that

gathers the theory, methods, and tools used in

processes involving the development of new

informatic solutions (Somerville, 2020). This

discipline invites to go beyond technical components

to promote systemic thinking in business contexts.

Some of the perspectives promoted by SE are 1)

Methodological: how to optimize human and

technological resources in a software development

process, 2) Design and Modeling: how to optimize the

structure and dynamics of the systems to be designed,

and 3) Technological: how to gather existing

technologies in the design of solutions to contextual

problems (i.e., companies, individuals, and societies).

Hence, promoting structured and systemic thinking

skills required by this discipline, implies various

educational challenges from a holistic perspective.

At Universidad El Bosque, Colombia, we lead our

students' professional development following the

https://orcid.org/0000-0001-5648-9966

https://orcid.org/0000-0001-6420-5687

https://orcid.org/0000-0002-3024-1257

structure proposed by the Biopsychosocial & Cultural

Model (BPsy&C). The BPsy&C proposes four

dimensions based on a perspective centered in 1) the

environment, 2) the artifact, 3) the habits, and 4) the

beliefs. This model fosters the development of a

global analysis in the context of a certain project,

multi-disciplinarily helping in the understanding and

enhancement of complex needs (López-Cruz & Ortíz-

Buitrago, 2017).

SE requires of teaching-learning processes to be

incremental and evolving, based on curricular

approaches that gather previous skills and knowledge

from prior courses (e.g., CS1, CS2, Data Structures).

Software development does not just depend on the

technology used (e.g., third-party tools, context-

based components), but also on the methodologies

that lead to good practices in the management of

human resources, time, among others. Based on the

constructivist theory (Saldarriaga-Zambrano et al.,

2016), we need to foster teaching-learning processes

to be based on the construction of knowledge (i.e.,

266

Feijóo-García, M., Ramírez-Arévalo, H. and Feijóo-García, P.

Collaborative Strategy for Software Engineering Courses at a South American University.

DOI: 10.5220/0010460602660273

In Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021) - Volume 2, pages 266-273

ISBN: 978-989-758-502-9

mental models) from enriching experiences, further

from the basic transmission of concepts or topics.

The integration and relationship of CS courses

through transversal activities promotes a holistic

professional development that bridges concepts and

skills coming from different courses. Nevertheless,

we have observed at our institution that SE courses,

regardless of belonging to the same curricular line, do

not fully satisfy the integration of strategies: there is

a particular interest in micro-curricular topics. Thus,

we ask the next questions: How do we guarantee that

SE students link competencies from different

courses? How do we promote a clear learning

roadmap to our students from each one of the SE

courses? How do we make this roadmap to be learner-

centered?

This paper presents a strategy applied between

two SE core courses on subsequent semesters (SE1

and SE2), using a transversal project that demanded

competencies from both courses. Our strategy

fostered the use of good software development

practices, asking students to use agile methodologies

that promoted inter-curricular teamwork and helped

them build skills on requirements identification,

responsibilities delegation, and decision-making:

skills required in Industry. We present our findings

and results on students’ perceptions based on our

active learning approach, and the impact of our

strategy for their learning processes. Additionally, we

describe the instructors’ experiences, addressing the

pros and cons from this process.

2 RELATED LITERATURE

Software Engineering Education (SEE) has been

explored in Computing Education Research (CER)

for decades, concerning topics such as 1) software

development processes, 2) software modeling, and 3)

collaborative learning.

In recent years, the CS community has advocated

on agile methodologies in CS curricula, referring to

its benefits compared to traditional waterfall

approaches, as also as their contribution to the

professional development of Computer Scientists

(Soundararajan et al., 2012; Soundararajan & Arthur,

2012; Campanelli & Parreiras, 2015; Tripp &

Armstrong, 2018). This has motivated the CS Ed

community to brainstorm and evaluate novel

teaching-learning strategies to introduce these

methodologies. Literature exists on game-based

activities for requirements definition (Beatty &

Alexander, 2008; Knauss et al., 2008; Hof et al.,

2017), assignments using LEGO as a tool to teach

methodologies (Kurkovsky, 2015; Kurkovsky et al.,

2019), and games designed to assist learners in SE:

board games (Brito & Vieira, 2017; Moura & Santos,

2018) and digital ones (Marinho et al., 2020;

Rodriguez et al., 2015). The CS Ed community has

also contributed to strategies to help students learn

about software modeling and software design (Pérez

& Rubio, 2020; Gayler et al., 2007; Coffey, 2017).

Technologies such as DesignDB (Goelman &

Dietrich, 2018) and Archinotes (Urrego et al., 2014)

pose as examples of tools designed to leverage

software abstraction and modeling for SE.

Finally, collaboration plays an essential role in

SE. CER literature reports that using strategies like

pair-programming positively impact intra-curricular

CS setups. Students who participated in Collaborative

Learning (CL) activities such as pair-programming

improved their learning performance (Gray et al.,

2019) as they also increased their confidence

(Celepkolu & Boyer, 2018). These outcomes relate to

research on inter-curricular CS setups between first-

year courses: CS1 and CS2 (Feijóo-García & Ortíz-

Buitrago, 2018; Cottam et al., 2011). Like pair-

programming, peer-tutoring reported helping

improve students' performance, retention, and

motivation: primarily, when students attributed a

mentor role. Additional literature presents Global

Software Engineering (GSE). GSE has taken place in

undergraduate and graduate courses all around the

world. As it reports about the benefits of CL, it also

presents challenges due to cultural and language

barriers regardless of the configuration between

institutions (Fu et al., 2018; Clear et al., 2015).

Our work contributes to CER literature on SE with

a strategy based on an inter-curricular design between

two subsequent SE courses in the same institution.

The strategy uses the benefits of peer instruction,

addressing SE concepts and skills concerning

methodology, project management, and software

design.

3 CONTEXT AND STRATEGY

This section describes the courses: SE1 and SE2, in

which we used our active-learning strategy.

Additionally, we present its evaluation and how we

carried out the data analysis to get the findings and

results we explain later in this paper.

Our strategy is carried out in two mid-

undergraduate core (i.e., mandatory) courses in the

Program of Systems Engineering— i.e., Computer

Science (CS), at a South American higher-education

institution—Universidad El Bosque, Colombia. SE1

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267

is offered to sophomore CS students. This course

introduces defined structures for the design and

development of team software projects, using

reference frameworks on traditional and agile

methodologies (i.e., TSP, RUP, Scrum, XP). On the

other hand, SE2 is offered to junior CS students. This

course addresses topics related to software patterns

and architecture (i.e., Observer, Factory, Facade,

MVC, SOA, MSA), software quality, metrics,

software estimation, usability, and distributed

software. At this mid-level point of our students’

professional development, they already have gained

concepts and skills on CS1, CS2, Data Structures

(CS3), Algorithms Design (AD), and Databases

(DB). Hence, SE1 and SE2 seek to improve skills and

abilities following the complete software

development life cycle, systems modeling, and the

administration of a software development project in

business environments.

The College of Engineering of our institution

divides each course into three academic modules.

Each course has a duration of 16 weeks (i.e.,

academic semester in Colombian standard).

Throughout the semester we proposed two projects,

aiming to apply the topics carried out in each course:

SE1 or SE2. The first project started in the second half

of the first module to the end of the first half of the

second module, with a duration of four weeks. We

proposed the second project to last five weeks, during

the third academic module of the semester. We had a

total of 36 students (N=36): 50% (n=18) from SE1,

and 50% (n=18) from SE2. We had 13.88% (n=5)

female students, and 86.11% (n=31) male students.

We had students between 18 and 41 years of age:

69.4% (n=25) between 18 and 21 years of age, 25%

(n=9) between 22 and 25 years of age, and 5.6% (n=2)

over 25 years of age.

3.1 First Project Approach

[Intra-curricular]

This subsection describes the first context-based

project, which made use of an intra-curricular design

to promote collaborative learning. The project's

context was the same for SE1 and SE2. However, we

asked some specific deliverables and tasks for each

course, depending on the topics seen to date.

In this first project of the semester, we formed

groups of six people within each course (SE1 or SE2),

to work on a web-based software solution according

to the topics carried out at the time. We formed six

working groups: three groups from SE1 and three

from SE2. Groups were asked to develop web-based

software solutions using a traditional waterfall

methodology (i.e., RUP, TSP). This project was

centered on software solutions for a national-wide

movie theater company. The software development

process promoted intra-curricular interactions

between students at the same academic level, and

fostered teamwork skills and responsibilities’

delegation. Moreover, each group had to use all the

concepts seen to date in each course.

After the groups’ completion of the software

development process, we proceeded with an inter-

curricular peer-reviewing approach. We selected

three members from each group in each course (SE1:

n=9, SE2: n=9). Groups in SE2 were reviewed by SE1

students, as groups in SE1 received feedback from

SE2 students. Each reviewer was asked to solely

evaluate one group. This approach helped us to

explore how an inter-curricular design could work

between SE1 and SE2.

3.2 Cross-sectional Project Approach

[Inter-curricular]

This subsection describes the second context-based

generic cross-sectional project. The project's context

was the same for SE1 and SE2. However, differently

from the first project, this second project’s design was

inter-curricular between SE1 and SE2 for the

software development process.

In this second project of the semester, we formed

groups of six people between both courses (SE1 and

SE2), to work on a web-based software solution

according to the topics carried out at the time. We

formed six inter-curricular working groups. Groups

were asked to develop web-based software solutions

using an agile methodology (i.e., Scrumban, Scrum,

XP, LSD). This project was centered on software

solutions for a national-wide parking management

company. The inter-curricular design for the software

development process promoted teamwork skills and

responsibilities’ delegation, considering different

levels of expertise between students. Additionally,

our approach fostered a collaborative learning

environment that contributed to both kinds of

students: SE1 students were introduced to new

concepts common in SE2, while SE2 students

reinforced previous concepts and skills from SE1.

We had two clients and each of them were

assigned to three groups—first and second authors of

this paper. As clients, we monitored each group's

development, progress, and evolution, both

documentary and technologically. After the groups

completed the second project (five weeks), we

evaluated each solution through a formal presentation

(i.e., postmortem) asking for the required

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deliverables: e.g., Software Architecture Document

(SAD), video-demo, web-based software—deployed

in a cloud platform. During these presentations, we

provided feedback on groups’ decisions, outcomes,

and teamwork process. We also provided a survey

where our students were asked to self-evaluate and

co-evaluate according to their contributions. Students

also responded to a survey to assess the activity's

effectiveness based on their perception, reporting on

the benefits, difficulties, and impact of the project and

the proposed strategy.

Differently from the first project, we had to work

for this second project online. This, due to limitations

because of COVID-19. The pandemic brought

limitations in terms of communication, software

development, and teamwork, in addition to the stress

of the pandemic. However, the use of new alternative

resources for synchronous and asynchronous

teamwork allowed our students to gain new skills on

time management and usage of resources. Moreover,

the inter-curricular design helped them to keep

engaged and motivated. We first thought that students

were not going to respond successfully to our

approach due to the pandemic. However, their

participation was active, and the outcomes were

satisfying.

4 DATA ACQUISITION

We evaluated the effectiveness of the strategy

mentioned above considering the following aspects:

1) students’ submissions, reviewed by the instructors

and their peers [quantitative— ratio data from 0.0 to

5.0], and 2) the students’ perceptions on their

experience with the strategy [quantitative—1-5

Likert scales, and qualitative—open-ended

questions]. In this section, we present the data

acquisition for each aspect.

4.1 Data Acquisition: Evaluation Phase

For each project, we asked our students to create a

presentation, in addition to a documentation on their

software development process. Both projects were

graded on a scale between 0.0 and 5.0 and had three

components—the leading instructors determined the

percentage weights based on their experience with

both courses. The evaluation criteria considered:

Presentation—30% of the Project’s Grade: We

evaluated the presentation’s content, the number of

functionalities developed for the web-based software,

the rationale behind the software development

process, their communication skills, and their

responses to their observations and questions posed

by their instructors.

Documentation—50% of the Project’s Grade:

We asked students to document their process and

results on a software architecture document (SAD), in

addition to a test-planning document, and two

manuals: a technical one, and a usability one—this

one included a video-demo. Documentation was

evaluated by their instructors.

Peer-reviewing—20% of the Project’s Grade:

Peers were asked to review their teammates

considering time management, effort, and

engagement with the software development process.

4.2 Data Acquisition: Perceptions

We gathered our students’ perceptions on the second

project (i.e., inter-curricular) with a questionnaire that

had five Likert-scale (1-5) questions and three open-

ended questions (see Table 1).

Table 1: Questionnaire for our student’s perceptions.

Question

Option

Q1: If you had to evaluate this

strategy, with its methodology,

advantages, disadvantages,

opportunities and difficulties,

how useful would you find it?

(1 – 5)

1: Not useful at all.

5: Very useful.

Q2: Indicate how comfortable

you felt with this inter-

curricular strategy that involved

two courses from different

academic semesters.

(1 – 5)

1: Very uncomfortable.

5: Comfortable.

Q3: Indicate how much effort

did you have to invest in for

this inter-curricular strategy.

(1 – 5)

1: No effort at all.

5: Much effort.

Q4: Indicate how much did the

inter-curricular strategy

contribute to your professional

development.

(1 – 5)

1: No contribution at all

5: It contributed very

much.

Q5: Indicate the impact of the

inter-curricular strategy for

your professional development.

(1 – 5)

1: No impact at all.

5: It impacted very

much.

Q6: Indicate the positive

aspects of the inter-curricular

strategy you were asked to

follow.

Open-ended question

Q7: Indicate the difficulties

of the inter-curricular strategy

you were asked to follow.

Open-ended question

Q8: Briefly justify your

previous answers. All

comments, reflections, and

perceptions must be recorded

in this section.

Open-ended question

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5 FINDINGS AND RESULTS

We present our findings and results based on the data

acquired with the instruments described in section 4,

focusing our analysis on each of the data acquisition

categories previously described.

5.1 Data Analysis: Evaluation

Looking at Table 2, we can observe that the scores of

the quantitative evaluations, given by the instructors

(80% of the final score) and peers (20% of the final

score), were generally positive. Each group got an

average score higher than 4.0 in a 0.0 to 5.0 scale.

Each group's score was given based on their

submission and the process they reported. For the

inter-curricular project—first project, scores were

normally distributed (Shapiro-Wilk, w=0.95, p

>0.05): 47% of students were scored higher than 4.0

(n=17), 50% of students were scored lower than 4.0

and higher than 3.0 (n=18), and 3% of students were

scored lower than 3.0 (n=1). For the inter-curricular

project—second project, scores were not normally

distributed (Shapiro-Wilk, w=0.89, p < 0.01). This,

due to students’ performance on the inter-curricular

project: 56% of students were scored higher than 4.0

(n=20), and 44% of students scored lower than 4.0

and higher than 3.0 (n=16).

We had positive results for both projects and

methods. Moreover, based on the scores’

distributions mentioned above and the descriptive

statistics presented in Table 2, we can suggest that the

inter-curricular design helped students to get better

scores. However, further research should be

conducted to validate that claim.

Table 2: Descriptive Statistics on Students’ Scores.

Project

Course

Mean

Median

Project #1

– intra-

curricular

SE1

3.87

0.62

3.81

SE2

4.10

0.62

4.33

Project #2

– inter-

curricular

SE1

4.02

0.42

4.14

SE2

4.02

0.42

4,14

SE1 & SE2

4.02

0.42

4.14

5.2 Data Analysis: Perceptions

We did an analysis on the Likert scales (1-5) (Joshi et

al., 2015) used to gather students’ perceptions (see

Table 1). This analysis is represented as a divergent

stacked-bar graph (Tufte & Graves-Morris, 1983),

and it helped us to identify how effective did students

perceive the proposed inter-curricular project and its

methodology (Fig. 1). Additionally, with natural

language processing techniques (NLP) of students’

comments—Naïve Bayes classification technique

(Jurafsky & Martin, 2014), we were able to analyze

text sentiment on their input, and to create word

clouds based on their responses to questions 6, 7, and

8 (see Table 1)—i.e., most highly mentioned words.

This analysis guided us to reflect on the positive

aspects and difficulties perceived by our students,

helping us in the identification of elements to improve

for our inter-curricular strategy.

As presented in Figure 1, students from both

courses (SE1 and SE2) generally considered the inter-

curricular strategy “Satisfactory” (n=9) or “Very

Satisfactory” (n=22). Our findings suggest that SE1

students benefitted the most from our strategy due to

the interaction they had with SE2 students, as also due

to the introduction of upcoming SE2 topics. However,

SE2 students’ responses differed on Q2 and Q4 (see

Figure 1). We believe that it is due to the difficulty

SE2 students found when they assigned

responsibilities according to SE1 peers’ skills at the

beginning of the project. However, further research is

required to understand those perceptions.

We conducted a sentiment analysis using

semantic NLP on our students' comments—Naïve

Bayes classifier (Jurafsky & Martin, 2014) with

TextBlob (Loria, 2018). We distributed our

utterances in three categories: Positive, Neutral, and

Negative. Table 3 presents the performance of the

Naïve Bayes model's accuracy. For this, we used a

N=44 training set.

Table 3: Naïve Bayes Model on Sentiment Classification.

Category

Precision

Recall

F1-Score

Support

Positive

0.67

0.92

0.77

Neutral

0.73

Negative

1.00

0.75

0.86

Accuracy Calculations

Accuracy

0.80

Average

(Macro)

0.80

0.79

Average

(Weighted)

0.83

0.80

The accuracy of the model used to classify

students’ comments was 80% (Table 3). We can

affirm that the results obtained from the comments of

our students are reliable, based on Díaz et al.

contribution: recent studies published in the academic

community Teaching Academic Survival Skills

(TASS), present accuracy values between 63.1% and

89.3% on sentiment-based classifiers (Díaz-Galiano

et al., 2019). Table 4 presents the results obtained

from our sentiment analysis per category.

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Figure 1: Likert-Scale (1-5) visualization on open-ended questions about student’s perceptions.

Table 4: Sentiment Analysis per category.

Cat/Aspect

Pos.

Diff.

Perceptions

Pct (%)

Positive

67.6%

Neutral

12.0%

Negative

20.4%

For the inter-curricular project, students generally

responded with positive perceptions. This, since 7 out

of 10 students (67.6%) made positive comments on

Q6, Q7, and Q8 (see Table 1): 1) Positive Aspects, 2)

Difficulties, and 3) Perceptions. Moreover, responses

on Q6, Q7, and Q8 were in average positive—61% of

students. On the other hand, the percentage of

positive responses regarding the inter-curricular

project's general perception was 77%, and most of the

comments (55.56%) were positive even in terms of

those difficulties students identified.

The words most frequently used by our students

per question (Q6, Q7, and Q8) were: (1) Difficulties:

time, communication, and difficulty, (2) Perceptions:

Group work, good experience, knowledge, and (3)

Positive Aspects: Learning, knowledge, group work.

Regardless of the existing limitations, the inter-

curricular strategy had a positive general perception

for our students. We believe that students highly

appreciated the team-based design, finding our

approach as a pleasant learning experience. This

claim is based on the sentiment analysis we have

described.

6 DISCUSSION

We consider that our strategy effectively assisted in

the development of soft skills (e.g., communication,

teamwork, assignment of responsibilities, resource

management), and allowed students to understand

concepts and gain skills from topics from both

courses. This activity required us to invest additional

effort as instructors to supervise each team upon their

expected development process. Regardless of the cost

of planning meetings with the different teams to

evaluate their progress and outcomes, we find very

satisfying how our students engaged, and the

motivation they exhibited with the proposed strategy.

We found two aspects we consider were difficult

to address: (1) At the beginning, SE2 students

misinterpreted the assignment's objective. They

believed that their role was to instruct SE2 topics to

SE1 peers. As instructors, we had to clarify that the

strategy was asking them all to work as peers, as their

goal was to guarantee the best responsibilities'

assignment and distribution according to their skills.

We believe that the misinterpretation was due to the

lack of inter-curricular strategies. However, we

consider that it was not something that impacted the

later steps in our strategy. (2) Although both projects

had minimum requirements, there were some

additional features asked regarding each group and

their processes. We found easy to evaluate the

minimum requirements between groups, but we had

Collaborative Strategy for Software Engineering Courses at a South American University

271

to invest extra time to scale and grade those additional

features requested per group. We will standardize

features for upcoming iterations of our strategy.

We also find that the students’ comments on the

activity were positive and constructive, and that they

guide us to improve our strategy for future iterations.

We found that when the activity was first proposed,

students were reluctant to work with peers who did

not belong to their same course (SE1 or SE2).

However, after starting our strategy, we observed our

students committing to the software process and

engaging with their peers. This shows us that our

strategy was beneficial to foster and develop Software

Engineering skills.

As educators, we cannot ignore the opportunity to

highlight this experience and the satisfaction that our

strategy gave us. We consider that the teamwork,

attitude, assimilation, and motivation we observed in

our students were positive. Additionally, our inter-

curricular strategy fulfilled its goal, by guiding our

students to get the most out of it based on the

concepts, skills, and competences expected in our

Software Engineering courses.

ACKNOWLEDGEMENTS

The authors would like to thank the students who

actively participated in the evaluation of this strategy.

We also extend our gratitude to the Program of

Systems Engineering at Universidad El Bosque,

Colombia and our colleagues from the line of

Software Engineering and Programming.

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