STUDIES OF REGIONAL,
NATIONAL AND INTERNATIONAL NEEDS OF THE SYSTEMS ENGINEERING PROGRAM OF THE CORPORACIÓN
UNIVERSITARIA AMERICANA
Sebastián CARDONA-ACEVEDO[1]
Luisa YEPES OSPINA[2]
Jhon Edisson COLORADO FLÓREZ[3]
Arturo ARENAS-FERNÁNDEZ[4]
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Received
Approved |
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07/09/2026 |
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01/10/2026 |
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Published |
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13/10/2026 |
ABSTRACT: This study analyzes the regional, national,
and international relevance of the Systems Engineering program at Corporación Universitaria
Americana in the context of rapid digital transformation and increasing demand
for advanced technological competencies. The study adopted a mixed-methods
approach, combining documentary analysis, secondary data review, international
benchmarking, and curricular gap analysis to assess alignment between the
current curriculum and requirements from public policies, the productive
sector, technological trends, and international frameworks for computing
education. The findings indicate heterogeneous curricular relevance across the
three levels of analysis. The program demonstrates strengths in software
development, computational thinking, project-based learning, and
interdisciplinary problem-solving. However, gaps remain in the systematic,
transversal integration of artificial intelligence, cloud computing,
cybersecurity, advanced data analytics, software architecture, and intelligent
systems. The analysis also identifies limited structural articulation with
regional innovation ecosystems and industry, as well as opportunities to
strengthen curricular flexibility and specialization pathways in response to
evolving labor market demands. These findings suggest that the main challenge
is not the absence of emerging technologies in the curriculum, but their
predominantly incremental and insufficiently integrated incorporation.
Accordingly, the study proposes a competency-based curricular redesign focused
on the transversal integration of emerging technologies, continuous curriculum
updating, stronger university–industry collaboration, interdisciplinary
learning, and flexible specialization pathways. This framework can strengthen
graduate employability, institutional competitiveness, and the continuing
relevance of Systems Engineering education in a rapidly changing digital
environment.
Keywords: Artificial intelligence, curriculum relevance, digital transformation,
higher education, systems engineering.
Distribution license declared as open
access: CC BY
INTRODUCTION
The relevance of higher
education programs is a fundamental criterion for ensuring their capacity to
respond to social, productive, scientific, and technological transformations in
their surrounding environment. Within this context, the Systems Engineering
program at Corporación Universitaria
Americana is structured according to the regulatory framework established by
the accreditation granted through Resolution 023029 of November 30, 2021,
issued by the Ministry of National Education. Although this recognition
establishes formal quality standards and provides a foundation for the
educational proposal, its validity should not be treated as static, given the
rapid transformation of the educational, technological, and labor environment.
In particular, processes associated with digital transformation, automation,
and the data-driven economy have substantially altered the characteristics and
competencies required in the world of work (World Bank, 2019; OECD, 2020).
Therefore, accreditation should be regarded as a baseline subject to continuous
evaluation and updating in response to emerging environmental dynamics.
From this
perspective, the National Accreditation Council's guidelines identify relevance
as an essential component of quality, understood as the capacity of academic
programs to respond coherently and proactively to the needs of the social,
productive, and scientific environment. However, transformations in the
information and communications technology ecosystem reveal a growing demand for
professional profiles whose competencies extend beyond traditional training in
programming and infrastructure management. Labor market analyses and
international projections point to a need for hybrid professional profiles that
integrate technical, analytical, and strategic knowledge, particularly in
advanced analytics, artificial intelligence, cybersecurity, and digital
solutions architecture (World Economic Forum, 2023). This transformation aligns
with international frameworks for computing education, which promote
integrative, competency-based approaches (Association for Computing Machinery (ACM) & IEEE
Computer Society (IEEE-CS), 2020).
Consequently,
a tension emerges between curricula grounded in traditional disciplinary
structures and an environment that requires transversal and interdisciplinary
capabilities to address complex problems. International organizations have
recognized this situation in their analyses of the challenges digital
transformation poses to education and employment (CEPAL, 2022; UNESCO, 2021).
The potential misalignment between academic training and environmental demands
may affect both graduate employability and academic programs' capacity to
participate in regional and national innovation dynamics. In the Colombian
context, this need becomes particularly relevant because of the articulation
between state policies on digital transformation, such as those established by
the Departamento Nacional de Planeación
(2019) through CONPES 3975, and the commitments established by the Departamento Nacional de Planeación
(2023) in the National Development Plan 2022–2026.
Despite the growing importance of curricular
relevance, evaluation often relies on isolated indicators, regulatory
compliance exercises, graduate employability measures, or comparisons with
labor-market needs. These approaches may provide valuable information, but they
do not necessarily integrate, within a single analytical framework, the
relationships among public policy, productive-sector demands, and the
discipline's future evolution. This limitation is particularly significant in
Systems Engineering, where technological change can rapidly alter the
knowledge, skills, and professional roles expected of graduates. Therefore, a
more comprehensive evaluation is needed to determine not only whether a
curriculum currently responds to its environment, but also whether it is
positioned to anticipate emerging transformations.
In this
context, the curricular relevance of the Systems Engineering program can be
examined through a multidimensional perspective that moves beyond an
exclusively descriptive approach and links curricular structure to
environmental dynamics. For this purpose, three complementary dimensions are
considered: vertical, horizontal, and prospective relevance. Vertical relevance
examines the program's correspondence with public policies and national
priorities concerning education, development, and digital transformation. At
this level, the Departamento Nacional de Planeación (2023) establishes digitalization as a
cross-cutting axis for competitiveness and equity, while the Departamento Nacional de Planeación
(2019), through CONPES 3975, provides guidelines for developing human capital
associated with emerging technologies, particularly in areas such as artificial
intelligence and the digital economy. This orientation also relates to the
Sustainable Development Goals, particularly SDGs 4, 8, and 9, which link quality
education with decent work and innovation. Nevertheless, international evidence
indicates that traditional Systems Engineering curricula may incorporate these
orientations only marginally, thereby creating a gap between public policy
objectives and their effective translation into professional competencies (UNESCO,
2021).
Horizontal
relevance, in turn, makes it possible to assess the alignment between academic
training and the productive sector's dynamics. The evolution of labor demand
toward hybrid technological profiles highlights the need for professionals who
can operate in environments where digital technologies, organizational
processes, and new business models converge (World Bank, 2019; World Economic
Forum, 2023). Insufficient articulation with the productive sector may lead to
predominantly reactive curricular processes, limiting the capacity to
anticipate market needs and affecting both graduate employability and the
program's contribution to regional innovation processes.
Finally,
prospective relevance incorporates technological trends and future disciplinary
transformations as references for curricular updating. Frameworks developed by
the Association for Computing Machinery and the Institute of Electrical and
Electronics Engineers show Systems Engineering expanding into areas such as
data science, cloud computing, cybersecurity, and artificial intelligence,
implying changes in both educational content and training methods (ACM & IEEE-CS,
2020). In this regard, one of the main challenges is updating curricula quickly
enough to keep pace with technological evolution, which may create a gap
between the competencies developed during academic training and those required
in emerging professional contexts.
Thus, the
research problem focuses on the potential dissonance between the current
educational structure of the Systems Engineering program at Corporación
Universitaria Americana and the current and future
demands of the digital, productive, and regulatory environment. Identifying
this potential gap requires assessing not only compliance with regulatory
standards but also the curriculum's capacity to respond to technological
transformations, public policies, productive-sector needs, and international
disciplinary trends. Consequently, the program needs an evidence-based
curricular evaluation process that identifies opportunities to update content,
methodologies, and competencies, while strengthening articulation with the
productive and technological environment. This approach is essential to
ensuring the program's academic sustainability and relevance in the medium and
long term, in accordance with international
standards for computing education (ACM & IEEE-CS, 2020).
The main contribution of this study lies in proposing
and applying an integrated analytical perspective that simultaneously examines
three dimensions of curricular relevance: vertical relevance, associated with
public policies and national development priorities; horizontal relevance,
related to the requirements of the productive and labor environment; and
prospective relevance, focused on technological and disciplinary trends that
may shape future professional practice. Rather than limiting the analysis to
regulatory compliance or a descriptive review of the curriculum, this approach enables
identification of convergences, gaps, and curricular tensions across multiple
sources of environmental demand. In practical terms, the findings can provide
evidence to support curriculum updating, competency development, academic
planning, and stronger articulation between the university, the productive
sector, and public policy. Methodologically, the proposed multidimensional
framework also offers a potentially transferable approach for evaluating
curricular relevance in other engineering- and technology-oriented higher
education programs operating in contexts of accelerated technological change.
Accordingly, the objective of this study is to analyze
the curricular relevance of the Systems Engineering program at Corporación
Universitaria Americana in relation to the current
and future demands of the educational, productive, technological, and
regulatory environment, through a multidimensional analytical model based on vertical, horizontal, and
prospective relevance, to identify curricular gaps and opportunities for
updating and improvement.
Accordingly, the guiding research question is: To what
extent does the Systems Engineering program at Corporación
Universitaria Americana respond to the current and
future demands of the educational, productive, technological, and regulatory
environment, ¿and what curricular gaps and opportunities for improvement can be
identified?
METHODOLOGY
The study methodology uses a
mixed-methods design focused on evidence triangulation, aiming to
systematically compare the Systems Engineering program's curriculum with the
dynamics of the regulatory, productive, and technological environment. This
methodological approach moves beyond unidimensional frameworks, enabling
relational analysis in which curricular decisions are evaluated for coherence
across multiple sources of evidence. This approach mitigates the risk of biases
arising from partial diagnoses.
The methodological approach centers
on a tripartite integration of document analysis, secondary data, and
international benchmarking, establishing a cross-validation framework. The documentation
analysis identifies explicit priorities in public policies and regulatory
frameworks, while secondary data analysis reveals trends in labor demand and
the evolution of the ICT sector. Benchmarking, for its part, provides a
comparative reference point that allows evaluation of the program's positioning
against international standards, particularly in curriculum updates and the
development of emerging competencies. This methodological approach responds to
the need to interpret the curriculum not as an autonomous construct, but as an open system conditioned by multiple
levels of influence.
The documentary corpus comprised 25 documents selected for their direct
relevance to curricular development, digital transformation, ICT-sector
requirements, technological trends, professional competencies, and
international frameworks for computing and Systems Engineering education. The corpus
included institutional and curricular documents, national public-policy and
regulatory documents, sectoral and labor-market reports, and international
guidelines and reports related to technological and professional trends.
The documentary search was conducted through official repositories and
institutional websites of national and international organizations relevant to
the study, including governmental and educational entities, as well as
organizations such as the OECD, UNESCO, World Bank, World Economic Forum, ACM,
IEEE, and INCOSE. The search was guided by combinations of terms related to
“Systems Engineering,” “computing education,” “curriculum,” “digital
transformation,” “ICT skills,” “professional competencies,” “artificial
intelligence,” “data science,” “cybersecurity,” and “cloud computing.” The
search prioritized documents directly related to the regional, national,
international, and prospective dimensions examined in the study.
Documents were included when they provided explicit evidence regarding
at least one of the following aspects: public-policy priorities associated with
education and digital transformation; ICT-sector and labor-market requirements;
technological and professional competency trends; curricular guidelines for
computing or Systems Engineering education; or international standards relevant
to the future development of the discipline. The study excluded documents that
did not provide information directly applicable to the study's analytical
dimensions, duplicated information already represented in the corpus, or lacked
sufficient content for curricular comparison.
The study uses content
analysis, a qualitative research method that systematically examines textual
materials to identify patterns or themes (Esmaeili et
al., 2025). In this case, the analysis focuses on strategic documents,
including development plans, digital transformation policies, sector
guidelines, international frameworks, and specialized reports, to identify
analytical categories related to competencies, priority areas, technological domains, and training approaches.
After selecting the documents, the evidence was classified according to
the analytical dimensions established for the study. Vertical relevance
included information on public policies, regulatory frameworks, and national
development priorities; horizontal relevance incorporated evidence on
productive-sector requirements, labor-market dynamics, and professional
competencies; and prospective relevance included technological trends,
international disciplinary frameworks, and emerging areas of professional practice.
Competencies, technological areas, training approaches, and environmental
demands then organized the information extracted from each document.
This process is complemented by a gap analysis that compares the current
curriculum structure with the competencies required by the environment, helping
identify specific
misalignments in areas such as data analytics, artificial intelligence,
cybersecurity, cloud computing, and software architecture. Furthermore, a
technology monitoring exercise, based on a review of scientific literature and
specialized reports, identifies emerging trends and evaluates the program's
capacity to respond to future professional and technological scenarios.
The units of analysis are
defined in a manner consistent with the study's purpose. First, the program's
curriculum serves as the internal reference point and is analyzed in terms of
content, competencies, and training structure. Second, labor-market and
productive-sector demands are examined using secondary information from
national and sectoral sources, including information on labor-market
integration, occupational profiles, technological requirements, and skills
gaps. Third, global technological and disciplinary trends are addressed through
reports and frameworks from national and international organizations, whose
evidence is used to contextualize the evolution of Systems Engineering and related computing disciplines.
The analytical procedure involved four stages. First, the relevant
documentary and secondary sources were identified and selected according to the
established criteria. Second, the information contained in these sources was
classified according to the vertical, horizontal, and prospective dimensions of
relevance. Third, the competencies and technological areas identified in the
external environment were mapped against the Systems Engineering program's
subjects, competencies, and training structure. Finally, the resulting
correspondences and discrepancies were synthesized through curricular alignment
and gap-analysis matrices, allowing the identification of strengths, partial
alignments, structural gaps, and opportunities for curricular improvement.
The analytical process is operationalized
through tools that facilitate information integration. Curriculum alignment
matrices map correspondence between subjects and essential competencies, while
policy-curriculum correspondence matrices make explicit the relationship
between regulatory guidelines and the program's educational structure. These
tools support systematic information organization, enabling identification of
structural gaps, redundancies, and opportunities for curriculum innovation.
The study triangulated evidence by comparing findings across sources
rather than interpreting each document independently. The study contrasted
public-policy priorities, productive-sector and labor-market demands,
international frameworks, and technological trends with the curriculum to
identify areas where multiple sources converged. This procedure strengthened
the consistency of the curricular diagnosis and supported the assessment of the
program from regional, national, international, and prospective perspectives.
Thus, the methodology is not
confined to describing the program's current state; rather, it generates
evidence to support curricular decision-making. Integrating documentary
analysis, secondary data, international benchmarking, curricular mapping, and
gap analysis makes it possible to evaluate curricular relevance as a dynamic
condition shaped by technological evolution, productive-sector demands, public
policy, and changes in professional competencies.
RESULTS
A relevance analysis of the
Systems Engineering program reveals a heterogeneous mix of alignments and gaps at
the regional, national, and international levels. This analysis identifies
structural tensions that directly affect curricular decision-making.
At the regional level,
particularly in Antioquia, the productive ecosystem is becoming increasingly
complex as technology clusters consolidate and business demand for advanced
digital solutions grows. Departmental plans and chambers of commerce have
prioritized competitiveness agendas in areas such as data analytics,
specialized software development, and digital business transformation. However,
a thoroughgoing analysis of the curriculum reveals only partial coverage of
these areas, with an overwhelming emphasis on conventional programming
fundamentals and infrastructure. This creates a digital talent gap, evident in
the challenges companies face in identifying suitable candidates and the
program's limited capacity to engage regional innovation networks meaningfully.
The relationship with ICT clusters is an underutilized opportunity, as the
current articulation does not translate into structural curricular adjustments
or the co-creation of training pathways geared toward the specific needs of the
business sector.
At the national level, the program's
relevance is contested by strategic priorities set out in instruments such as
CONPES 3975 of 2019, which establishes clear guidelines for developing
capabilities in artificial intelligence and digital transformation. The
structural deficit of ICT talent has been identified as an obstacle to the
country's competitiveness by both the Ministry of National Education and the
Ministry of Information and Communications Technologies. This has put direct
pressure on training programs to accelerate curriculum updates. However, the
evidence indicates that incorporating these areas into the analyzed program
reflects more of an incremental approach than a profound transformation of the
graduate profile. This gap between the training offered and the profiles
required in the labor market creates career paths that, while functional, do
not necessarily align with the highest value-added segments of the ICT sector.
The fundamental tension lies in the speed of institutional responses to a national
environment that requires sophisticated skills within increasingly constrained
timeframes.
On an international and forward-looking
level, a discrepancy becomes increasingly apparent when the program is compared
with global trends identified by organizations such as the World Economic Forum
and technical standards promoted by the IEEE. The consolidation of emerging
technologies, including but not limited to artificial intelligence, cloud
computing, cybersecurity, and data science, has significantly redefined professional
profiles in systems engineering. This redefined profile reflects a shift in emphasis
from operational skills to analytical, design, and complex systems integration
capabilities. In this context, benchmarking against international programs
reveals greater curricular flexibility, cross-cutting integration of these
technologies, and an orientation toward project-based learning and real-world
problems. The primary deficit identified is the program's limited capacity to
integrate these transformations systematically, which impedes its academic
competitiveness and its graduates' international mobility.
The analysis indicates that
the program's relevance depends on balancing curricular stability with
environmental dynamism. The disparities identified at the three levels analyzed
point to the need for structural reconfiguration. Consequently, there is an
urgent need to transition to a flexible curricular model, aligned with the
productive sector and global trends. In this model, content updates, the
integration of emerging competencies, and links with innovation ecosystems
become central pillars to guarantee the program's relevance and sustainability.
Table 1
Analytical matrix of alignment
between competencies of the Systems Engineering program of the American
University Corporation and demands of the environment
|
Program competencies |
Skills demanded by the environment |
Source of demand |
Alignment level |
Evidence |
Gap identified |
|
Software programming and development |
Modern Software
Engineering and Agile Development |
Mercado TIC, World
Economic Forum |
Medium-High |
High performance
(92%) in software development |
Partial integration
of DevOps, automated testing, and modern architecture |
|
Development of technological solutions |
Software
Architecture and Scalable Systems |
Association for
Computing Machinery |
Medium |
Integrated projects
applied to real-world problems |
Lack of explicit
focus on architecture and scalability at the curricular level |
|
Databases and information management |
Data Science and
Advanced Analytics |
OECD |
Medium-High |
Inclusion of Data
Analytics and high performance (90%) |
Limited
cross-curricular integration with other areas of the curriculum |
|
Technological infrastructure |
Cloud Computing and
Distributed Systems |
IEEE |
Low-Medium |
Syllabus
adjustments and curriculum updates |
Absence of a
structured approach to cloud computing |
|
Computer security |
Advanced Cybersecurity |
World Economic
Forum |
Medium |
Inclusion of Advanced Cybersecurity |
Coverage still
localized, without cross-curricular integration |
|
Artificial intelligence |
Automation, Machine
Learning, and Intelligent Systems |
Departamento Nacional de
Planeación |
Medium |
Inclusion of AI and
Machine Learning |
Lack of
consolidation as a structural axis of the curriculum |
|
Technological project management |
Agile Methodologies
and Digital Transformation |
World Bank |
Medium |
Incorporation of
Agile methodologies into the syllabus |
Need for greater
practical depth in real-world environments |
|
Computational thinking and problem-solving |
Solving Complex
Problems in Interdisciplinary Environments |
UNESCO |
High |
80% in complex
problem-solving |
Lack of
systematization of interdisciplinary experiences |
|
Interdisciplinary work |
Knowledge
Integration in Innovation Ecosystems |
Clústeres, entorno regional |
Medium-High |
Interdisciplinary
projects with social impact |
Limited formal
articulation with clusters and the productive sector |
|
Flexible training |
Personalized
Learning Pathways and Adaptive Learning |
Tendencias globales |
High |
Elimination of
prerequisites and increased electives |
Lack of strategic
guidance in specialization pathways |
|
Internationalization |
Global Competencies
and Academic Mobility |
OCDE, mercado global |
Medium |
International
mobility and credit recognition |
Low level of
external mobility |
|
Integration of theory and practice |
Project-Based
Learning |
Association for
Computing Machinery |
High |
Projects with
social and technological impact |
Need for greater
engagement with companies |
The findings provide evidence
of a heterogeneous level of curricular relevance in the Systems Engineering
program, reflecting both strengths in established competencies and gaps in
responding to emerging technological and productive demands. The discussion
therefore interprets these results in relation to previous research on
engineering education, competency development, technological transformation,
and university–industry alignment, with particular attention to the regional,
national, and international dimensions considered in the study.
Analysis of Results
The results show that a
heterogeneous pattern of alignment across regional, national, and international
levels characterizes the Systems Engineering program's curricular relevance.
Rather than showing a general lack of relevance, the findings indicate that the
program has incorporated several competencies demanded by the contemporary
technological environment. However, their integration remains largely
incremental and insufficiently systemic. This is particularly evident in the
shift from conventional technical competencies to emerging capabilities in
artificial intelligence, data science, cloud computing, cybersecurity, software
architecture, and complex systems integration.
At the regional level, the
main challenge is the gap between the productive ecosystem's technological
dynamism and the curriculum’s capacity to respond structurally to these
transformations. Although the program includes software development, data
analytics, and technological solution development, their articulation with
regional productive demands remains limited. The medium and medium-high
alignment observed for these competencies indicates a strong curricular
foundation; however, limited connections with innovation networks and
technology clusters restrict the development of specialized, context-responsive
learning pathways. This finding is consistent with Orosco
and Mejía (2022), who emphasize the importance of correspondence between
university training, national development priorities, and business-sector
requirements. Consequently, curricular relevance should not be understood
merely as the presence of technological subjects, but as the capacity to
translate environmental demands into competencies, learning experiences, and
professional profiles.
The most significant regional
gaps therefore lie not necessarily in the absence of technological topics, but
in their depth and transversal integration. Data analytics, artificial
intelligence, and cybersecurity are incorporated into the program, but they do
not consistently function as structural axes across the curriculum. This
distinction is relevant because technological relevance increasingly depends on
knowledge integration rather than the isolated addition of new subjects. Cameron
et al. (2019) argue that growing technological and
systemic complexity requires educational structures that integrate knowledge
and develop competencies appropriate to complex professional environments.
Similarly, research on competency-based Systems Engineering education
emphasizes the importance of systematically identifying competencies through
academic and industry perspectives. Thus, curricular updating should move
beyond adding courses and instead promote stronger connections among learning
outcomes, pedagogical strategies, projects, and competencies.
At the national level, the
incorporation of artificial intelligence, machine learning, agile
methodologies, and other emerging areas demonstrates institutional recognition
of technological priorities. Nevertheless, these developments have occurred
progressively without a corresponding transformation of the graduate profile.
The central challenge is therefore curricular responsiveness: technological and
labor-market demands are evolving faster than formal curricular structures can
be modified. This tension between curricular stability and environmental
dynamism helps explain why several competencies achieve only moderate alignment
despite the existence of relevant subjects and activities.
This issue is particularly
important in Systems Engineering because professional practice increasingly
requires the capacity to understand, design, integrate, and manage complex
technological systems rather than merely execute operational or programming
tasks. Buede and Miller (2024) emphasize the systemic
nature of engineering design, in which requirements, architecture, components,
stakeholders, and system-level objectives must be considered as an integrated
whole. Jazebizadeh et al. (2010) similarly demonstrate
the usefulness of a systems engineering approach for structuring academic programs
around complex technological environments. Therefore, the present findings
suggest that curricular relevance would be strengthened by adopting a more
explicit systems perspective in organizing and integrating competencies.
The international and
prospective dimension presents the most pronounced structural challenge. The
low-medium alignment identified for cloud computing and distributed systems, along
with the medium alignment observed for artificial intelligence and advanced
cybersecurity, indicates that technologies shaping contemporary engineering
practice have not yet been sufficiently integrated into the curriculum. Current
engineering education research similarly highlights disparities between
university curricula and industry requirements, particularly regarding emerging
technologies, practical competencies, adaptability, analytical thinking, and
systems thinking. The issue is therefore not simply whether a technology is
taught, but whether students develop the capacity to integrate technologies and
apply them to complex, uncertain, and interdisciplinary problems.
Internationalization also
represents an important area for improvement. Although the program provides
mechanisms for electives, credit recognition, and academic mobility, external
mobility remains limited. The international dimension of engineering education
extends beyond mobility and includes competencies that enable graduates to
operate effectively in culturally and technologically diverse environments. Bourn
and Neal (2008) emphasize the importance of global competencies in engineering
education, while Marnewick and Handley (2022)
identify cultural awareness, communication, ethics, teamwork, and other
international competencies as relevant components of Systems Engineering
education. Thus, the program could strengthen internationalization by
incorporating global competencies into curricular outcomes, projects,
collaborative activities, and professional experiences.
Despite these gaps, the program
demonstrates important strengths. The strong alignment of computational
thinking, problem-solving, flexible training, and project-based learning
provides a solid foundation for curricular transformation. The 80% performance
in complex problem-solving and the strong alignment of project-based learning
indicate that the program already has pedagogical mechanisms that can support
technological and interdisciplinary integration. These strengths should
therefore be used as platforms for incorporating emerging technologies rather
than being replaced by an entirely new curricular structure. This approach is
consistent with international perspectives that emphasize practical, real-world
experiences, interdisciplinary competencies, and continuous adaptation in
Systems Engineering education.
The incorporation of
intelligent technologies also deserves particular attention. Reyes García et
al. (2024) illustrate the growing potential of intelligent systems within
Systems Engineering education. Likewise, recent research indicates that
artificial intelligence can contribute to technical, methodological, social,
and personal competencies such as programming, data analytics, problem-solving,
teamwork, adaptability, communication, ethics, and continuous learning. In this
case, including artificial intelligence and machine learning represents
progress toward technological relevance. However, their medium alignment
indicates they have not yet acquired the transversal role required to reshape
the professional profile.
Overall, the analytical matrix
demonstrates that curricular relevance is multidimensional. The program
exhibits strong foundations in software development, computational thinking,
project-based learning, and flexible training, while showing more pronounced
gaps in cloud computing, advanced systems architecture, interdisciplinary
integration, international mobility, and the transversal consolidation of
emerging technologies. The central finding is therefore not a generalized
curricular deficiency, but an asymmetric capacity for adaptation: the program
responds more effectively to established competencies than to rapidly evolving
technological and professional requirements.
These findings point toward a
transition from a predominantly content-oriented curriculum toward a more
flexible, integrated, and ecosystem-oriented model. Such transformation should
strengthen university–industry collaboration, incorporate real-world technological
challenges, expand interdisciplinary projects, establish clearer specialization
pathways, and embed emerging technologies across multiple curricular areas.
Consequently, the relevance of the Systems Engineering program should be
understood as a dynamic condition that requires continuous monitoring of
technological, productive, and societal transformations, rather than as a fixed
characteristic of the curriculum.
Comparison with Previous
Studies
The findings of this study are
broadly consistent with previous research examining the relationship between
Systems Engineering education, technological transformation, and professional
requirements. However, the results extend existing contributions by demonstrating
that curricular alignment varies substantially across regional, national, and
international dimensions of relevance.
A major point of convergence
concerns the need to establish stronger relationships between academic
curricula and productive-sector requirements. Orosco
and Mejía (2022), in their study of the pertinence of a Systems Engineering program
in Nicaragua, emphasized the importance of relating academic training to
national development priorities and business-sector demands. A similar
situation emerges in the present study, where the program shows partial
alignment with regional requirements, particularly in advanced software
development, data analytics, digital transformation, and emerging technological
solutions. Nevertheless, the present findings indicate that the challenge
extends beyond identifying labor-market needs: the critical issue is the
institutional capacity to translate these demands into systematic curricular
transformations.
This result is also consistent
with Cameron et al. (2019), who argue that increasing technological and
systemic complexity requires educational structures capable of preparing
professionals for increasingly complex engineering environments. In the present
study, this challenge is reflected in the medium alignment identified for
software architecture, artificial intelligence, cybersecurity, and
technological project management, as well as the low-medium alignment observed
for cloud computing and distributed systems. These findings suggest that
curricular relevance cannot be sustained by periodically incorporating isolated
technological topics. Instead, it requires a comprehensive transformation of
competencies, learning experiences, and relationships among curricular
components.
The results also converge with
research addressing the gap between employer expectations and academic
curricula. Studies on Systems Engineering competency expectations identify
relatively slow feedback mechanisms among employers, students, and
universities, limiting academic programs' capacity to respond to rapid
technological and industrial transformation. This situation closely parallels
the central tension identified in the present study between curricular
stability and environmental dynamism. Consequently, medium or medium-high
alignment should not necessarily signal complete relevance; rather, it may
indicate that the curriculum responds effectively to established requirements
while struggling to anticipate emerging ones.
The comparison with Jazebizadeh et al. (2010) further reinforces the importance
of a systemic approach to curriculum design. Their work shows how Systems
Engineering principles can structure academic programs around the requirements
of complex technological fields. The present study reaches a complementary
conclusion: although several environmentally demanded competencies are already
incorporated, their articulation remains insufficient in areas such as systems
architecture, cloud computing, artificial intelligence, interdisciplinary work,
and university-industry collaboration. Thus, this research contributes not only
by identifying the presence or absence of competencies, but also by assessing
the degree to which these competencies are structurally integrated into the
curriculum.
Internationalization represents
another important point of comparison. Bourn and Neal (2008) emphasize developing
global competencies in engineering education, while Marnewick
and Handley (2022) show how Systems Engineering curricula can deliberately
incorporate international competencies through communication, teamwork,
cultural awareness, and exposure to different perspectives. These findings
align with this perspective because internationalization remains an area of
comparatively weaker alignment. Although mechanisms for mobility and credit
recognition exist, limited external mobility suggests that internationalization
has not yet become a sufficiently transversal component of the educational
experience. Accordingly, international relevance should encompass not only
mobility opportunities but also the competencies required to participate
effectively in global and culturally diverse technological environments.
The findings also converge
with international approaches to Systems Engineering curriculum development.
INCOSE (2022) emphasizes that Systems Engineering education must remain
responsive to changing technologies and practices while developing
interdisciplinary, technical, leadership, and professional competencies. This
perspective is particularly relevant because the present results demonstrate
that curricular relevance is context-dependent. The program should therefore
not simply reproduce international models, but combine internationally
recognized competencies with regional and national productive requirements. In
this context, the high alignment observed for computational thinking,
problem-solving, flexible training, and project-based learning constitutes an
important foundation for integrating emerging competencies without eliminating
existing strengths.
Another point of convergence
concerns practical and interdisciplinary learning. The present study identifies
strong alignment in integrating theory and practice and in project-based
learning, while also noting limitations in articulating these experiences with
companies and innovation ecosystems. This finding aligns with systems
engineering education models that emphasize practical, real-world experience
and multidisciplinary collaboration. INCOSE similarly highlights the importance
of broad systems competencies, cross-disciplinary collaboration, and practical
learning connected to stakeholder needs. The distinctive contribution of the
present study is to locate this challenge specifically within
university-industry articulation: project-based learning is already present,
but its potential for curricular co-creation with the productive sector remains
underdeveloped.
Artificial intelligence and
intelligent technologies constitute another relevant area of convergence. Reyes
García et al. (2024) demonstrate the feasibility of incorporating intelligent
technological solutions into Systems Engineering education. In the present
study, artificial intelligence and machine learning are already included, but
their medium alignment indicates that they have not yet been consolidated as
transversal curricular axes. This distinction demonstrates that technological
incorporation and curricular transformation are not equivalent processes. A program
may include an emerging technology without substantially transforming its
competencies, pedagogical strategies, or professional profile. Current Systems
Engineering perspectives similarly emphasize the growing importance of digital
transformation, AI, data, cybersecurity, cloud computing, and other
technologies within future professional competencies.
Overall, the comparison with
previous studies reveals convergence around four fundamental principles:
responsiveness to technological change, alignment with industry requirements,
development of interdisciplinary and international competencies, and integration
of practical learning experiences. Nevertheless, this study adds a perspective
by organizing these dimensions within a three-level framework of regional,
national, and international/prospective relevance. This approach makes it
possible to identify asymmetries that may remain hidden when curricular
relevance is evaluated from a single perspective.
The study's main contribution
is therefore not identifying entirely new challenges, but contextualizing and
integrating them. Previous research has generally focused on specific
dimensions, such as international competencies, curriculum design,
technological complexity, or university-business alignment. This analysis
brings these dimensions together to show that curricular relevance results from
their interaction.
Accordingly, the evidence
indicates that the Systems Engineering program is neither disconnected from its
environment nor fully aligned with it. Rather, it occupies an intermediate
position, with strong foundations in established competencies and more limited
responsiveness to rapidly emerging technological, productive, and international
demands. This finding reinforces the view that curricular relevance should be
treated as a continuous process of adaptation and feedback among universities,
industry, technological developments, and societal needs. This approach
provides a basis for moving from periodic curricular updates to a more dynamic,
context-sensitive model of curriculum development.
Implications
The findings of the curricular
relevance analysis have important implications for the future development of
the Systems Engineering program at Corporación Universitaria Americana. The identified gaps suggest that
curricular relevance cannot be addressed exclusively through incremental
modifications or the incorporation of isolated courses. Rather, the results
point to the need for a structural, continuous approach to curriculum
development in which emerging technological demands, professional competencies,
pedagogical strategies, and external stakeholder expectations are
systematically articulated. This implication is particularly relevant for an
institution seeking to strengthen its position in engineering education and
consolidate its contribution to regional and national digital transformation.
From a curricular perspective,
the first implication concerns the transition towards an integrative
competency-based curriculum. The analysis indicates that the main challenge is
not necessarily the absence of technological content, but how knowledge is
organized, connected, updated, and translated into learning outcomes.
Consequently, curriculum review should consider not only the sequence and
content of courses but also how competencies are articulated across the program.
This would allow traditionally separated areas, such as programming, databases,
infrastructure, cybersecurity, and technology management, to converge around
complex problems and authentic technological challenges. This approach aligns
with recent evidence that engineering education increasingly requires
integrating technical, analytical, methodological, social, and adaptive
competencies rather than isolated disciplinary knowledge.
A second implication relates
to the strategic incorporation of emerging technological domains. Artificial
intelligence, data analytics, cybersecurity, cloud computing, distributed
architectures, and intelligent systems should not be treated merely as optional
or specialized components, but progressively integrated throughout the
curriculum. This does not necessarily mean adding more courses; instead, it
requires redefining learning outcomes and identifying where these competencies
can be developed progressively across different stages of the program. Evidence
from engineering and computing education shows that emerging areas such as AI
security, cloud security, and advanced cybersecurity remain unevenly
incorporated into curricula, reinforcing the importance of systematic
curriculum alignment rather than isolated technological additions.
This transformation also has
pedagogical implications. The results support a shift from predominantly
content-oriented teaching towards learning experiences centered on
project-based learning, complex problem solving, experimentation, simulation,
and real-world technological challenges. Programming education, for example,
could increasingly incorporate data analysis, automation, intelligent
applications, and software architecture, while technology management could
integrate data-driven decision-making and digital project management. The
objective would be to enable students to apply knowledge across contexts rather
than demonstrate mastery of individual technical subjects. Recent research
similarly highlights active learning and the development of analytical,
problem-solving, decision-making, collaborative, and adaptive competencies as
important components of engineering education in the context of Industry 4.0.
A further implication concerns
the relationship between the university and the productive sector. The findings
indicate that industry engagement should move beyond conventional internship
arrangements towards more systematic forms of curricular co-creation.
Companies, technology clusters, professional organizations, and other external
stakeholders could help identify competencies, validate learning outcomes,
develop authentic projects, and periodically review emerging technological
needs. Such mechanisms would establish a continuous feedback loop between the program
and its environment, reducing the risk of curricular obsolescence. Recent
studies likewise identify industry-validated competencies, practical learning,
and sustained stakeholder relationships as mechanisms to strengthen
employability and align academic training with professional requirements.
At the institutional level,
these implications require mechanisms for continuous curricular monitoring.
Given the rapid evolution of digital technologies, curriculum relevance should
be understood as a dynamic condition rather than a characteristic achieved
permanently through periodic formal revisions. The program would therefore
benefit from systematic processes for monitoring technological trends,
labor-market requirements, graduate trajectories, employer perceptions, and
developments in professional competency frameworks. This approach could provide
evidence for timely curricular adjustments while preserving coherence with the
institutional educational model and accreditation requirements.
Finally, the implications
extend to graduate employability and Corporación Universitaria Americana's strategic positioning. A
curriculum that integrates emerging technologies with systems thinking,
interdisciplinary collaboration, communication, ethical decision-making, and
practical problem-solving could strengthen graduates' capacity to participate
in higher-value segments of the ICT sector. In this sense, curricular
transformation should not be understood simply as an academic response to
technological change, but as an institutional strategy for developing
professionals capable of contributing to innovation and digital transformation.
The study's main implication is the need to establish a flexible, integrative,
and externally connected curricular model in which relevance is continuously
evaluated through interaction among academic knowledge, technological
evolution, productive-sector demands, and societal needs.
Limitations
This study has some
limitations that should be considered when interpreting its findings. First,
the analysis relies primarily on documentary and curricular evidence, which may
not fully capture the perceptions of students, graduates, employers, and
faculty regarding the program’s relevance. Second, the rapidly evolving nature
of digital technologies may cause some identified gaps and trends to change
over time. Therefore, the findings should be understood as a contextual
diagnosis of the program’s current relevance rather than a definitive
assessment, highlighting the need for continuous monitoring and periodic
curricular evaluation.
Research Agenda
Future research should extend
the present curricular relevance analysis through empirical and longitudinal
approaches that allow for a more comprehensive understanding of the
relationship between Systems Engineering education and the evolving technological
and productive environment. First, future studies should incorporate the
perspectives of students, graduates, faculty members, employers, and industry
representatives to identify differences between perceived and required
competencies and to validate the curricular gaps identified in this study. This
would strengthen the feedback mechanisms between academia and the productive
sector, which are particularly relevant in contexts of rapid technological
transformation.
Second, longitudinal research
is needed to monitor the evolution of emerging competencies in areas such as
artificial intelligence, data analytics, cybersecurity, cloud computing,
digital engineering, and model-based systems engineering. Such studies could
determine which competencies become structurally relevant over time and how
quickly academic programs respond to changes in professional practice. In this
regard, future research could develop competency-mapping models that
systematically compare curricular learning outcomes with labor-market
requirements and professional competency frameworks.
Third, comparative studies of
Systems Engineering programs across universities and national contexts could
provide evidence on alternative curricular models, pedagogical strategies, and
mechanisms of university–industry collaboration. Particular attention should be
given to project-based and interdisciplinary learning, curricular co-creation
with industry, and integrating emerging technologies across the curriculum
rather than through isolated courses.
Finally, future research
should evaluate the impact of curricular transformations on measurable
outcomes, including graduate employability, technological competencies,
academic performance, innovation capacity, and employer satisfaction. This line
of research would allow the relevance model proposed in this study to evolve
from a diagnostic framework into a continuous evidence-based mechanism for
curricular improvement. This agenda would contribute not only to the ongoing
transformation of the Systems Engineering program at Corporación
Universitaria Americana, but also to the broader
discussion of how higher education institutions can maintain curricular
relevance in rapidly changing technological environments.
CONCLUSIONS
This study analyzed the
curricular relevance of the Systems Engineering program at Corporación
Universitaria Americana from regional, national,
international, and prospective perspectives, identifying the degree of
alignment between its curricular structure and the educational, technological,
productive, and regulatory demands of its environment. The findings demonstrate
that the program maintains a relevant foundation in established areas such as
software development, computational problem solving, technological solutions,
and project-based learning. However, this relevance is uneven and less
consistent when evaluated against the rapid transformation of the technological
and productive environment.
The gap analysis shows that
the main challenge is not the complete absence of emerging technological
content, but its limited and predominantly incremental incorporation into the
curriculum. Areas such as artificial intelligence, data analytics, cybersecurity,
cloud computing, software architecture, and intelligent systems require greater
integration and progression throughout the educational process. Consequently,
curricular relevance should be understood not simply as the presence of
contemporary subjects, but as the program's capacity to articulate knowledge,
competencies, methodologies, and learning outcomes around complex and changing
technological problems.
At the regional and national
levels, the findings reveal a persistent gap between the evolution of the ICT
sector and the program's curricular response. Although the curriculum addresses
several competencies demanded by the productive environment, its structure does
not yet systematically reflect the growing importance of advanced digital
technologies and high-value ICT activities. This suggests strengthening the
program's relationship with the productive ecosystem through mechanisms that
enable continuous identification and validation of emerging competency
requirements. Previous research similarly emphasizes the importance of
competency-based curricular models and systematic interaction between academic
and industry perspectives in Systems Engineering education.
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[1] School of Engineering, Corporación Universitaria
Americana, Colombia, 50010, sacevedo@americana.edu.co, ORCID: https://orcid.org/0000-0002-6192-2928
[2] Technology Administrator. School of Education,
Corporación Universitaria Americana, lyepesmed@americana.edu.co, ORCID: https://orcid.org/0009-0009-0170-7626
[3] School of Engineering, Corporación Universitaria
Americana, Colombia, 50010, coordinacioningenieriamed@americana.edu.co, ORCID: https://orcid.org/0009-0000-5561-880X
[4] Office of the Vice President for Academic Affairs,
Corporación Universitaria Americana, Colombia, 50010, aarenasf@americana.edu.co, ORCID: https://orcid.org/0000-0001-7707-5981