On the Relation Between Open Project-Based Learning in

Undergraduate Computer Science Education and Contemporary

Technological Trends

Ruben Tous

, Felix Freitag

and Josep Lluis Berral

Universitat Politecnica de Catalunya, Barcelona, Spain

Keywords:

Project Based Learning, Information Technology, Professional Skills, Curriculum Adaptation.

Abstract:

Amidst rapid and constant technological change, keeping IT higher education curricula up to date is becom-

ing increasingly challenging. For a decade, the course ”Project on Information Technologies” within the

undergraduate computer science studies offered by a major technical university has been pursuing an effort

of continuous curriculum adaptation and active learning practices based on an open project-based learning

(PBL) methodology. This article researches the implications of employing an open-ended PBL approach, with

a speciﬁc focus on the alignment of acquired skills with the trends in the professional landscape. Our analysis

has identiﬁed a strong correlation between the technologies utilized in the projects and the contemporary tech-

nological trends in the areas of global technological focus, programming languages, server-side technologies,

database management systems, and DevOps-related tools. For the study, we analyzed empirical data gathered

from over 100 projects involving more than 400 students who enrolled in this reference course, belonging to

the last year of the IT higher education programme in the last 10 years. The results suggest the open project-

based design as a teaching means in the student’s study plan for fostering the student the learning of prevailing

current practical technologies.

1 INTRODUCTION

The skills and competencies essential for future pro-

fessionals are a pivotal consideration in shaping any

educational strategy. A signiﬁcant challenge within

the university system is showcasing its ability to adapt

to the rapid pace of change in contemporary soci-

ety. This challenge is particularly difﬁcult in the IT

domain, where the pace of technological change has

been immensely accelerated.

For the past ten years, the course ”Project on In-

formation Technologies” (PIT) within the undergrad-

uate computer science studies offered by a major tech-

nical university has pursued continuous curriculum

adaptation through the utilization of an open project-

based learning methodology. Today, project-based

learning (PBL) plays a fundamental role in the curric-

ula of students pursuing bachelor’s and master’s de-

grees in Information Technology (IT) and related dis-

ciplines (Giannakos et al., 2017; Sindre et al., 2018;

https://orcid.org/0000-0002-1409-5843

https://orcid.org/0000-0001-5438-479X

https://orcid.org/0000-0003-3037-3580

Fioravanti et al., 2018; Hulls et al., 2015). The de-

gree of openness in the project statement and solu-

tion stands out as one of the most relevant parameters

in the design of a course based on PBL (Hulls et al.,

2015).

Different from a traditional PBL approach, where

instructors deﬁne speciﬁc project goals and restrict

potential solutions and which fosters a consistent skill

development (Vasilevskaya et al., 2015), allowing stu-

dents to determine project objectives and technol-

ogy choices offers the advantage of naturally aligning

the speciﬁc skills they desire to acquire through the

course with trends in key IT technological domains

(Sindre et al., 2018; Suseno et al., 2023). The course

under examination employs this latter open-statement

and open-solution approach in which, with the feed-

back from the instructor, the students are encouraged

to drive the project deﬁnition.

To delve deeper into the implications of the open

project choice, we examined the historical evolution

of the technologies addressed in the projects devel-

oped in the course. For this, we analyzed empir-

ical data drawn from over 100 projects undertaken

by more than 400 students in the course during ten

Tous, R., Freitag, F. and Berral, J.

On the Relation Between Open Project-Based Learning in Undergraduate Computer Science Education and Contemporary Technological Trends.

DOI: 10.5220/0012650600003693

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

In Proceedings of the 16th International Conference on Computer Supported Education (CSEDU 2024) - Volume 2, pages 397-404

ISBN: 978-989-758-697-2; ISSN: 2184-5026

397

academic years, from 2012/2013 to 2022/2023. The

resulting ﬁndings and conclusions, particularly those

related to the alignment of acquired skills with con-

temporary trends in IT’s technological domains, are

presented in this study.

2 BACKGROUND

2.1 Course Description

The research undertaken in this paper was carried

out within the framework of the semester-long course

”Project on Information Technologies”, of 6 ECTS

credits (around 150 hours), and from the last year

of the Bachelor of Computer Science offered by the

School of Informatics at a major technical univer-

sity. The study comprises ten academic years, from

2012/2013 to 2022/2023.

The course curriculum encompasses technical

skills pertinent to information technologies, computer

networks, and distributed applications. Additionally,

it covers non-technical cross-disciplinary competen-

cies such as teamwork, project conceptualization, and

administration, as well as verbal and written com-

munication. The primary aim of the course revolves

around the collaborative development of a project by

groups of typically 4 students. The project spans 15

weeks, equivalent to half an academic year.

2.2 Related Work

Numerous studies have advocated for project-based

learning as a suitable methodology to attain effec-

tive competency-based education (Chinowsky et al.,

2006; Gijselaers, 1996; A. Johnson, 1999; Gijse-

laers, 1996; Padmanabhan and Katti, 2002; Veselov

et al., 2019; Anggraeni et al., 2023; Suseno et al.,

2023). Several works have analyzed its effectiveness

in higher education, particularly focusing on engi-

neering disciplines (De los R

ıos et al., 2010; Ruikar

and Demian, 2013; Stewart, 2007; Gibbes and Car-

son, 2014; Requies et al., 2018). In the study of

De los R

ıos et al. (De los R

ıos et al., 2010), the

authors chronicle two decades of employing project-

based learning within higher education engineering

in the context of the ﬁnal years of the undergradu-

ate programme of the Technical University of Madrid,

Spain. One of the ﬁndings drawn from this study

is that project-based learning signiﬁcantly enhances

the connection between university education and the

practical professional sphere. The work of Ruikar et

al. (Ruikar and Demian, 2013) delves into the asso-

ciations between project-based learning and engage-

ment with the industry. The study of Stewart (Stew-

art, 2007) puts the focus towards the correlation be-

tween self-directed learning readiness and the results

of project-based learning. Gibbes and Carson(Gibbes

and Carson, 2014) applied activity theory analysis to

investigate project-based learning. The authors docu-

ment mixed results in learning outcomes due to con-

tradictions identiﬁed within the activity system (such

as uneven distribution of tasks or perceived time con-

straints stemming from community commitments).

Numerous other studies also document particular ex-

periences of project-based learning in higher educa-

tion (e.g. (Rush et al., 2007; Hassan et al., 2008; Fer-

nandes et al., 2013; Pereira et al., 2017; Requies et al.,

2018)). The majority of these studies rely on qual-

itative evaluations of students’ actions and achieve-

ments, which do not consistently enable to establish a

direct cause-and-effect relationship between project-

based learning instruction and positive student out-

comes. Numerous works delve into the precise im-

plementation of project-based learning within higher

education in the ﬁeld of IT. In the work of Sindre et

al. (Sindre et al., 2018), the authors assess the ap-

propriateness of project-based learning within the IT

context in general, and with respect to the curriculum

guidelines from the ACM/IEEE Task Force on Com-

puting Curricula in particular. This study concludes

that this approach effectively adjusts to the swiftly

evolving skill requirements for upcoming IT profes-

sionals. Fioravanti et al. (Fioravanti et al., 2018) re-

port an experience that integrates project-based learn-

ing and project management in a Software Engineer-

ing course.

There exists a limited number of works focusing

on the extent of project statement and solution open-

ness within project-based learning. Hulls et al. (Hulls

et al., 2015) detail the transformation of (a portion of)

a traditional C++ programming course (ﬁrst-year of

Mechanical and Mechatronics Engineering students

at the University of Waterloo, Canada) into an open-

ended project-based learning course. The research

centered on motivational factors and concludes that

this approach led to a substantial upsurge in student

enthusiasm. An interesting facet of this study is the

students’ choice between predeﬁned projects (such as

a Roomba-like robot, an elusive alarm clock, or a

maze-solving robot) or their individual project pro-

posals. The authors report how the prevalence of stu-

dents opting for their own concepts escalated over

time, eventually constituting the majority.

CSEDU 2024 - 16th International Conference on Computer Supported Education

398

3 MATERIALS AND METHODS

3.1 Data Acquisition and Analysis

To conduct this study, an analysis of the ﬁnal deliver-

ables from projects completed by attendees of the PIT

course was necessary. The analysis covered a span

of ten academic years, ranging from 2012/2013 to

2022/2023. A total of 125 projects, engaging over 400

students, underwent scrutiny. Data processing was fa-

cilitated through the utilization of project descriptions

that students contributed to a Wiki platform as part of

their concluding assignments.

Student project descriptions were manually pro-

cessed and, for each project, a machine-readable

project summary was generated in JSON format.

Summaries included project focus (eg ”mobile app”),

programming languages, technologies involved, and

all tools of project management involved. However,

because the information in the student project descrip-

tions is of heterogeneous quality, in many cases, it

was necessary to manually process the project deliv-

erables one by one.

A Python-based tool was created to collate all the

JSON summaries and perform automated computa-

tions on the evolving frequency of distinct technolog-

ical components over time. Relative frequencies were

adopted (e.g., ”50% of projects in the ﬁrst semester of

2012/2013 employed Java”) instead of absolute val-

ues due to variations in project counts across differ-

ent courses. The resultant numerical data points were

saved in a collection of gnuplot-formatted data ﬁles

and are presented as line charts to track the shifts in

technologies across the years.

Furthermore, for a comprehensive analysis of the

correlation between these shifts and real-world trends,

a tool wase created (also with Python) to extract nu-

merical information from Google Trends (Google,

2024).

4 RESULTS AND DISCUSSION

In the upcoming sections, we present the ﬁndings

of the study. A line chart is provided for each

project aspect, illustrating the changing frequencies

of various student choices over time. Since PTI

spans a full semester, each time period corresponds

to one semester (20xx-1 represents the initial autumn

semester, while 20xx-2 corresponds to the subsequent

spring semester).

Figure 1: Line chart showing the evolution of the overall

technological focus of the projects.

4.1 Technological Project Scope

Although the projects involve multiple components,

they usually revolve around a main technology (e.g.

blockchain). Figure 1 shows the evolution of the

four most common global technological focus of the

projects:

• web-app: projects whose main workload is dedi-

cated to web application development. Typically,

this kind of projects involves client-side web tech-

nologies (e.g. HTML, Angular, etc.) and server-

side web technologies (HTTP servers, application

servers, etc.).

• mobile-app: projects whose main workload is

dedicated to mobile application development.

Typically, this kind of projects involves client-side

mobile technologies (Android SDK, iOS SDK,

Unity, React Native, etc.) and server-side tech-

nologies such as Web APIs.

• iot: projects whose main workload is dedicated to

Internet of Things (IoT) related technologies (e.g.

Raspberry Pi, Arduino, webcam, sensors or actu-

ators).

• blockchain: projects whose main workload is

dedicated to blockchain related technologies (e.g.

Ethereum, Solidity, MetaMask, etc.).

Comparing the students’ choices with the real tech-

nology trends in Figure 2, it can be seen that they

closely correspond.

In a preceding period (spanning the 2000s decade)

without accessible numerical data, the technological

landscape of typical projects transitioned from non-

HTTP distributed applications (such as CORBA or

Java RMI) to projects primarily centered around web-

based technologies, referred to as the web-app focus.

Towards the end of that decade, the project emphasis

On the Relation Between Open Project-Based Learning in Undergraduate Computer Science Education and Contemporary Technological

Trends

399

Figure 2: Google Trends interest score (related to search

frequency) in the range 0-100 for the topics ”web de-

velopment”, ”android software development”, ”internet of

things” and ”blockchain” (Google, 2024).

shifted to the creation of mobile applications (mobile-

app).

As the study commences in the academic year

2012/2013, mobile applications continued to domi-

nate, yet a nascent trend, the Internet of Things (IoT),

had already begun capturing student interest. The

mid-2010s saw a prevalence of IoT projects, peaking

during the ﬁrst semester of the 2016/2017 academic

year. Simultaneously, another technological wave

emerged, the blockchain. This innovation swiftly

grasped student attention, although its trajectory has

been stabilizing in more recent times.

The approaches referenced are not exhaustive, but

they do represent the most prevalent ones. Over recent

semesters, certain projects have integrated elements

linked to artiﬁcial intelligence. However, this aspect

lies outside the primary course objectives and remains

relatively uncommon within the scope of this study.

4.2 Programming Languages

Figure 3 displays the evolution of students’ choices of

programming languages over time. When comparing

these results with the popularity of programming lan-

guages according to Google Trends (Figure 4), it can

be observed that the programming languages used in

the projects not only align with current trends but also

have the potential to predict them.

The authors have noted that students tend to ex-

hibit a natural inclination toward experimenting with

new languages, which is inversely proportional to

their willingness to use languages they perceive as

outdated. IT professionals do not have the same free-

dom, neither the same disposition probably, and the

adoption of new programming languages in the pro-

fessional ﬁeld is slower.

Figure 3: Line chart showing the relative frequencies of the

students choice of programming languages over time.

Figure 4: Popularity of programming languages according

to Google Trends (Google, 2024).

Another conclusion drawn is that the students’

preferences for using programming languages in their

projects do not appear to align with the program-

ming languages they have learned during their career

(mainly C++ and Java). Through the last years, it has

been observed how Node.js (JavaScript) and Python

have been gaining share until they have become the

most widely used languages, both in the client and

the server side. JavaScript outperforms Python in our

data, inversely to what is observed in Google Trends.

The authors attribute this to the fact that Python is

massively used by data science related tasks, which

are generally out of the scope of the course.

4.3 Server-Side Technologies

Figure 5 illustrates the progression of server-side

technologies employed in the projects. In the initial

reporting period, students frequently opted for Java

Servlet (e.g., the Apache Tomcat open-source Java

Servlet Container) for the backend of their client-

CSEDU 2024 - 16th International Conference on Computer Supported Education

400

Figure 5: Line chart showing the relative frequencies of the

students choice of server-side technologies over time.

Figure 6: Line chart showing the relative frequencies of the

students choice of database technologies over time.

server applications. This choice was likely inﬂuenced

by its use in introductory labs within the course. An-

other common alternative during this period was the

Apache HTTP server paired with PHP CGIs, a choice

typically made by students with some professional

experience (a circumstance less common at the be-

ginning of the decade but now widespread). While

the use of CGIs has dwindled, HTTP servers continue

to feature prominently in many projects, with Apache

gradually giving way to NGINX. In parallel with the

rise of Node.js, the Express web application frame-

work has seen increased adoption. Similarly, students

who favor Python tend to select the Flask micro web

framework for their backend solutions.

4.4 Database Technologies

Figure 6 illustrates the evolution of database tech-

nologies employed in the projects, revealing three

distinct periods. Prior to 2015, the majority of

projects favored object-relational database manage-

ment systems, primarily centered around MySQL

Community Edition, alongside options like Post-

greSQL. The span between 2015 and 2021 witnessed

a shift in preference towards NoSQL database man-

agement systems, with MongoDB taking the lead,

accompanied by Cassandra, CouchDB, and others.

Notably, MongoDB’s impressive success, constitut-

ing about 90% of NoSQL database instances dur-

ing that timeframe, can be attributed to its scala-

bility and seamless integration with Node.js. This

era also introduced the emergence of blockchain-

related technologies. Despite not mirroring the func-

tionalities of traditional databases precisely, numer-

ous students adopted blockchain to store all the data

(although such instances often lacked rationale and

have been rectiﬁed over time). From 2021 on-

Figure 7: Google Trends interest score (related to search

frequency) in the range 0-100 for the topics ”MySQL” and

”PostgreSQL” (Google, 2024).

Figure 8: Google Trends interest score (related to search

frequency) in the range 0-100 for the topics ”MongoDB”

and ”MariaDB” (Google, 2024).

ward, dynamics have evolved. The previously as-

cending trajectory of NoSQL databases has tapered,

On the Relation Between Open Project-Based Learning in Undergraduate Computer Science Education and Contemporary Technological

Trends

401

allowing object-relational databases to regain some

prominence. However, there have been shifts in spe-

ciﬁc product preferences. Among object-relational

database management systems, MySQL’s predomi-

nant position has waned, making room for alternatives

such as MariaDB and PostgreSQL (see ﬁgures 7 and

8). In the realm of NoSQL databases, MongoDB re-

tains a strong presence in many projects, though cer-

tain students are exploring substitutes like CouchDB

or RethinkDB. The momentum behind blockchain

has also dwindled, with its application becoming

more targeted, typically in conjunction with tradi-

tional database utilization.

4.5 DevOps

Figure 9 illustrates the progression of several

DevOps-related tools employed within the projects.

Technologies and practices associated with the De-

vOps methodology have experienced substantial

growth in student projects, mirroring developments in

the professional sphere (see Figure 10). The initial

technology in this domain was Docker, which under-

went rapid expansion. Presently, almost all projects

integrate Docker containers for diverse software com-

ponents. Subsequently, Kubernetes, the container or-

chestration system, emerged. While highly regarded

by students, its complexity and limited beneﬁts for

prototype development lead many to shy away from

its use. More recently, tools related to continuous

integration and continuous delivery (CI/CD), such

as Jenkins, have surged in popularity. Jenkins is a

preferred choice among students, yet many also opt

for the integrated features offered by GitHub or Git-

Lab. A multitude of other tools in this ﬁeld have sur-

faced in projects, including Ansible, Chef, Terraform,

Prometheus, Grafana, ArgoCD, and numerous others.

While not essential for prototype development, their

prevalence in the professional realm motivates stu-

dents to capitalize on the opportunity to acquire pro-

ﬁciency in their usage.

5 CONCLUSIONS

This study reviewed the evolution of technology

choices in projects during a decade of an IT-related

course with an open project-based learning method-

ology. Relevant conclusions are derived with respect

to changes of the used technologies and the adaptation

of the skills learned to the trends of the main IT tech-

nology domains. A systematic analysis of the data,

with a special emphasis on the open-statement and

open-solution methodology, aims to pave the way to-

Figure 9: Line chart showing the relative frequencies of

different DevOps related components found in the projects

over time.

Figure 10: Google Trends interest score (related to search

frequency) in the range 0-100 for the topics ”Docker”, ”Ku-

bernetes”, ”Ansible” and ”CI/CD” (Google, 2024).

wards guiding future IT higher education courses de-

sign.

The analysis centered around ﬁve distinct facets:

the global technological focus, the utilized program-

ming languages, server-side technologies, database

management systems, and DevOps-related tools. Our

analysis demonstrated noteworthy shifts in these ﬁve

dimensions as they were implemented in the course

projects, occurring within relatively short timeframes

and closely mirroring technological trends. Addi-

tionally, our results reveal the shrinking lifecycles of

technological trends and the swift proliferation of po-

tential solutions for each problem. This remarkably

dynamic environment, which poses a deﬁnite chal-

lenge for IT educators, appears to be a non-issue for

students. They have demonstrated an adeptness at

aligning their project’s learning content with prevail-

ing technological trends, a ﬂexibility facilitated by the

open-ended project framework.

CSEDU 2024 - 16th International Conference on Computer Supported Education

402

It is worth mentioning that some students opt for

projects of a more fundamental nature, but they are

very few and do not appear in the graphs. This is

unsurprising, given that the course is taken by stu-

dents in their ﬁnal year, who are preparing to enter

the professional realm. This can also be attributed

to the fact that students have already acquired funda-

mental techniques and methodologies through a range

of other courses throughout their academic journey.

In fact, the synergy between courses, like the PBL-

based course concentrating on current technologies,

and other courses dedicated to fundamental meth-

ods and techniques, appears advantageous. This ap-

proach equips students with the capacity to engage

with present technologies for immediate industrial ap-

plicability, while their fundamental knowledge em-

powers them to adeptly navigate the swift shifts in

technological landscapes.

A question that remains is to determine if the num-

ber of students participating a the group project inﬂu-

ences the observed relation between the open project-

based methodology and technological trends. In fu-

ture work it could be interesting to analyze whether

small groups of 2-3 students are more likely to align

their project with current technologies than bigger

groups of 4-5 students, and become able to recom-

mend an optimal project group size.

ACKNOWLEDGEMENTS

This work is partially supported by the Span-

ish Ministry of Science under contracts

PID2019-107255GB, PID2019-106774RB-C21,

PID2021-126248OB-I00 (MCIN/AEI/10.13039/

501100011033/FEDER), PDC2023-145809-I00

(PDC/AEI/10.13039/501100011033), the Recovery

and Resilience Facility of the European Union,

and by the SGR programme of the Catalan Gov-

ernment under contracts 2021-SGR-00478 and

2021-SGR-01059.

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