Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
https://doi.org/10.62574/r06dpy41
94
Generative artificial intelligence in Ecuadorian education: Pedagogical
transformation and cognitive development
Inteligencia artificial generativa en educación ecuatoriana:
Transformación pedagógica y desarrollo cognitivo
Jorge Hamilton Leal-Cevallos
jorgelealcev@hotmail.com
Ministerio de Educación-Zona 4-Distrito 13D01-Portoviejo, Manabí, Ecuador
https://orcid.org/0000-0001-9836-9356
Luby Claudia Ramírez-Álava
lubyramirez@hotmail.com
Ministerio de Educación-Zona 4-Distrito 13D01-Portoviejo, Manabí, Ecuador
https://orcid.org/0009-0004-9871-0277
Estrella del Rosario Loor-Burgos
estrellarosloor@hotmail.com
Ministerio de Educación - Zona 4- Distrito 13D02- Manta-Montecristi-Jaramijó, Ecuador
https://orcid.org/0009-0002-3954-258X
Cecilia del Rocío Álava-Cevallos
cecilia.alava@yahoo.es
Red de Investigación Koinonia, Portoviejo, Manabí, Ecuador
https://orcid.org/0009-0005-6304-1330
ABSTRACT
The integration of generative artificial intelligence into the Ecuadorian education system represents an
opportunity to revolutionise teaching methodologies and enhance student cognitive development. Through
a systematic review of specialist literature published between 2023 and 2025, this study examines the
potential impact of these emerging technologies, analysing the opportunities, challenges and implications of
their implementation. The results show that generative AI can personalise learning experiences, stimulate
critical thinking and facilitate student-centred pedagogical approaches. However, risks associated with
excessive technological dependence and the need for appropriate regulatory frameworks are identified. The
METE-IAG model (Ecuadorian Model for Educational Transformation through Generative Artificial
Intelligence) is proposed, structured around five interrelated dimensions: pedagogical, technological,
cognitive, organisational, and ethical. This framework suggests a gradual implementation that combines
teacher training, adequate technological infrastructure, and coherent educational policies to maximise
benefits while minimising potential risks.
Descriptors: pedagogical transformation; cognitive development; educational technology. (Source:
UNESCO Thesaurus).
RESUMEN
La integración de inteligencia artificial generativa en el sistema educativo ecuatoriano constituye una
oportunidad para revolucionar las metodologías pedagógicas y potenciar el desarrollo cognitivo estudiantil.
Mediante una revisión sistemática de literatura especializada publicada entre 2023 y 2025, este estudio
examina el impacto potencial de estas tecnologías emergentes, analizando oportunidades, desafíos e
implicaciones de su implementación. Los resultados demuestran que la IA generativa puede personalizar
experiencias de aprendizaje, estimular el pensamiento crítico y facilitar enfoques pedagógicos centrados en
el estudiante. No obstante, se identifican riesgos asociados con la dependencia tecnológica excesiva y la
necesidad de marcos regulatorios apropiados. Se propone el modelo METE-IAG (Modelo Ecuatoriano de
Transformación Educativa mediante Inteligencia Artificial Generativa), estructurado en cinco dimensiones
interrelacionadas: pedagógica, tecnológica, cognitiva, organizacional y ética. Este marco sugiere una
implementación gradual que combine capacitación docente, infraestructura tecnológica adecuada y
políticas educativas coherentes para maximizar beneficios mientras se minimizan riesgos potenciales.
Descriptores: transformación pedagógica; desarrollo cognitivo; tecnología educativa. (Fuente: Tesauro
UNESCO).
Received: 09/07/2025. Reviewed: 14/07/2025. Approved: 19/08/2025. Published: 08/09/2025.
Research articles
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
95
INTRODUCTION
The global educational landscape is undergoing an unprecedented technological
revolution, with generative artificial intelligence emerging as a disruptive force
capable of redefining traditional teaching and learning paradigms. In the
Ecuadorian context, characterised by particular challenges in terms of
educational equity, access to technological resources and teacher training, the
strategic adoption of these tools represents both an extraordinary opportunity and
a complex challenge that demands rigorous analysis and careful planning.
Over the last few decades, Ecuador has undergone significant transformations in
its education system, driven by public policies aimed at improving educational
quality and reducing socio-economic gaps. However, structural challenges
remain that limit student learning potential, including predominantly traditional
teaching methodologies, limited educational resources, and disparities in access
to emerging technologies between different regions of the country.
The emergence of generative artificial intelligence in the global education sector
has demonstrated significant transformative capabilities, from personalising
learning to automating complex administrative processes. According to research
by Bobula (2024), these technologies offer unique opportunities to address
persistent educational challenges, but they also present risks that require careful
consideration. Similarly, the work of Farrelly and Baker (2023) highlights that the
successful implementation of generative AI in higher education requires holistic
approaches that consider both pedagogical opportunities and ethical and
practical implications.
The relevance of this research lies in the urgent need to develop conceptual
frameworks and implementation strategies that enable the Ecuadorian education
system to capitalise on the transformative potential of generative AI, while
navigating the challenges inherent in its adoption. In particular, the study by
Chaparro-Banegas et al. (2024) emphasises that the integration of these
technologies requires a rethinking of traditional approaches to critical thinking and
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
96
educational assessment. Complementarily, Vieriu and Petrea (2025) stress that
the impact of AI on student academic development depends significantly on how
educational interventions are designed and implemented.
Furthermore, Bustard and Ghisoiu (2025) propose that the educational revolution
through generative AI requires asynchronous approaches and innovative
methodologies that transcend the limitations of conventional pedagogical models.
This perspective is particularly relevant to the Ecuadorian context, where
geographical and sociocultural diversity demands flexible and adaptable
educational solutions.
Study objectives
The main objective of this study is to analyse the potential of generative artificial
intelligence as a tool for pedagogical transformation in the Ecuadorian education
system, identifying viable strategies for its effective implementation and
evaluating its potential impact on student cognitive development. Specifically, it
seeks to examine the opportunities and challenges associated with the
integration of these technologies, develop a conceptual framework for their
strategic adoption, and propose practical recommendations to maximise their
positive educational impact.
Theoretical framework
The theoretical basis of this study is supported by a body of contemporary
research that examines the intersections between generative artificial intelligence
and education from multiple disciplinary perspectives. This conceptual framework
integrates contributions from digital pedagogy, cognitive psychology, educational
technology, and educational sciences, providing a solid foundation for critical
analysis of the transformative implications of AI in educational contexts.
Bobula's (2024) research provides a comprehensive perspective on the
challenges and opportunities presented by generative AI in higher education,
identifying specific areas where these technologies can generate significant
added value. His analysis reveals that successful implementation requires careful
consideration of technical, pedagogical, and ethical factors, setting important
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
97
precedents for developing educational contexts such as Ecuador's. The research
particularly highlights the need to develop digital teaching skills and appropriate
regulatory frameworks to maximise potential benefits.
From an innovative pedagogical perspective, Bustard and Ghisoiu (2025) explore
how the integration of generative AI can revolutionise education through
asynchronous approaches that transcend traditional temporal and spatial
limitations. Their work demonstrates that these technologies enable
unprecedented personalisation of learning experiences, facilitating adaptation to
different cognitive styles and learning rhythms. This perspective is particularly
relevant for education systems with limited resources, where efficiency and
scalability are priority considerations.
The work of Chaparro-Banegas et al. (2024) adds a critical dimension by
examining how generative AI challenges traditional paradigms of critical thinking
in education. Their research suggests that, far from replacing human cognitive
abilities, these technologies can serve as catalysts for developing more
sophisticated forms of analysis and critical reflection. This perspective refutes
common concerns about technological dependence, proposing instead models
of cognitive complementarity that enhance natural human capabilities.
In the specific field of marketing and business education, Ding et al. (2024)
demonstrate practical applications of generative AI that can be extrapolated to
other academic disciplines. Their work illustrates how these tools can transform
traditional teaching methodologies, facilitating more interactive and contextually
relevant learning experiences. The implications of their research extend beyond
specific disciplines, suggesting general principles for the effective integration of
AI in various academic fields.
In this vein, Farrelly and Baker (2023) contribute a holistic perspective that
examines the systemic implications of generative AI in higher education, focusing
on practical considerations for educational institutions. Their analysis ranges from
technological infrastructure to required organisational changes, providing a
valuable frame of reference for institutions considering the adoption of these
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
98
technologies. Particularly relevant is their focus on change management and
academic staff training.
On the other hand, Gerlich (2025) brings an important sociological dimension by
examining the impact of AI tools on the development of critical thinking and
cognitive offloading. His work raises fundamental questions about how these
technologies may affect human cognitive abilities in the long term, suggesting the
need for balanced approaches that preserve and enhance essential cognitive
skills while taking advantage of available technological benefits.
In this way, Gonsalves (2024) delves into the specific impact of generative AI on
critical thinking, revisiting Bloom's taxonomy from a contemporary perspective.
His work suggests that these technologies require a reconceptualisation of
traditional cognitive levels, proposing updated frameworks that reflect the new
realities of AI-assisted learning. This contribution is particularly valuable for the
design of curricula and assessment strategies in modern educational contexts.
The contributions of Grewal et al. (2025) and Guha et al. (2023) examine specific
applications of generative AI in higher education, providing empirical evidence on
its effectiveness in different academic contexts. Their research demonstrates
tangible benefits in terms of student engagement, learning personalisation, and
teaching efficiency, setting important precedents for future implementations in
diverse educational contexts.
Kshetri et al. (2024) offer a comprehensive perspective on the applications,
opportunities, and challenges of generative AI, developing a comprehensive
research agenda that encompasses multiple dimensions of analysis. Their work
provides a robust conceptual framework for assessing the transformative
potential of these technologies, including economic, social, and ethical
considerations that are particularly relevant to developing contexts.
The research by Narang et al. (2025) explores the multifaceted role of generative
AI in education, highlighting its versatility and adaptability to different pedagogical
contexts. Their work demonstrates how these technologies can take on multiple
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
99
roles within the educational ecosystem, from teaching assistants to assessment
tools, suggesting flexible approaches for their effective implementation.
Similarly, Patil (2024) contributes specialised perspectives on personalisation
and optimisation of educational strategies through generative AI, providing
valuable insights into how these technologies can be adapted to individual
learning needs. Their research suggests concrete methodologies for
implementing adaptive learning systems that respond dynamically to student
needs.
Similarly, Singh and Huang (2025) examine the intersection between AI and
creativity in educational contexts, demonstrating how these technologies can
enhance creative abilities rather than limit them. Their work refutes common
concerns about the standardisation of thinking, proposing instead models that
use AI as a catalyst for innovation and creative expression.
Consequently, Vieriu and Petrea (2025) provide empirical evidence on the impact
of AI on student academic development, offering quantitative data that supports
hypotheses about the educational benefits of these technologies. Their research
demonstrates measurable improvements in various indicators of academic
performance, establishing a solid evidence base for arguments in favour of
implementing AI in education.
Meanwhile, Zhai et al. (2024) contribute an important critical perspective through
their systematic review of the effects of over-reliance on AI systems on student
cognitive abilities. Their work identifies potential risks associated with the
inappropriate use of these technologies, proposing strategies to maximise
benefits while minimising negative consequences.
METHOD
A qualitative systematic review design oriented towards narrative synthesis was
implemented, appropriate for examining complex and multidimensional
phenomena such as the integration of generative AI in education. This approach
allows for the analysis of diverse theoretical and empirical contributions,
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
100
facilitating the construction of a comprehensive understanding of the
transformative implications of these technologies.
The methodological selection is justified by the emerging nature of the field of
research, where limited empirical evidence requires approaches that allow for the
integration of theoretical perspectives with preliminary results from experimental
implementations. This design facilitates the identification of general principles
applicable to the specific Ecuadorian context, considering the country's socio-
economic, cultural, and technological particularities.
The study population comprises the body of contemporary academic research
examining the intersection between generative artificial intelligence and
education, published between 2023 and 2025. This time frame ensures the
relevance of the results, considering the rapid evolution of AI technologies and
their educational applications.
The sample analysed includes fifteen (15) specialised publications selected using
specific criteria of theoretical and methodological relevance. The selected studies
cover various disciplinary perspectives, including digital pedagogy, educational
psychology, educational technology and applied computer science, providing a
comprehensive basis for analysis.
The inclusion criteria considered: (1) direct thematic relevance to generative AI
applications in education, (2) methodological quality demonstrated through peer
review, (3) significant theoretical or empirical contributions to the field, (4)
publication in indexed journals of recognised academic prestige, and (5)
accessibility of the full text for detailed analysis.
The systematic review was conducted following established ethical principles for
academic research, including appropriate recognition of intellectual contributions
through accurate citation and faithful interpretation of original arguments.
Analytical objectivity was maintained by avoiding confirmation bias and ensuring
equitable representation of diverse perspectives.
Although this research does not directly involve human participants, ethical
implications related to the proposed recommendations were considered,
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
101
particularly in terms of educational equity, technological access, and student
privacy. These considerations informed both the analysis and the
recommendations of the study.
RESULTS
Proposal for a comprehensive framework for the implementation of
generative AI
Based on a systematic analysis of the specialised literature, a comprehensive
framework called the ‘Ecuadorian Model of Educational Transformation through
Generative Artificial Intelligence’ (METE-IAG) is proposed. This model is
structured around five interrelated dimensions that address the technical,
pedagogical, organisational, and social aspects necessary for successful and
sustainable implementation.
Transformative pedagogical dimension
The first dimension of the METE-IAG model focuses on the reconceptualisation
of traditional pedagogical practices through the strategic integration of generative
AI tools. This dimension proposes a hybrid approach that combines human
teaching experience with the adaptive capabilities of artificial intelligence,
creating dynamic and personalised learning ecosystems.
The proposed pedagogical model is based on three structural pillars: adaptive
personalisation, which allows content and methodologies to be tailored to the
individual needs of each student; cognitive facilitation, which uses AI as a
scaffolding tool to develop complex thinking skills; and continuous formative
assessment, which provides immediate and specific feedback to optimise the
learning process.
The implementation of this dimension requires the development of specific
teaching skills that enable the effective use of generative AI tools as a
complement to, rather than a replacement for, traditional pedagogical expertise.
This includes skills for designing effective educational prompts, interpreting AI
outputs in pedagogical contexts, and maintaining the essential human dimension
of the educational process.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
102
Within the Ecuadorian context, this dimension must consider the country's
cultural and linguistic diversity, developing AI applications that recognise and
value different regional educational traditions. The proposal includes the creation
of repositories of culturally appropriate content and the development of
multilingual interfaces that facilitate equitable access to these technologies.
Technological and infrastructural dimension
The second dimension addresses the technical and infrastructural requirements
necessary to support the effective implementation of generative AI in the
Ecuadorian education system. This dimension recognises budgetary constraints
and regional disparities in access to technology, proposing scalable and
financially sustainable solutions.
The technological strategy is structured around three levels of implementation:
basic level, which includes access to generative AI tools through low-cost web
platforms and mobile applications; intermediate level, which incorporates learning
management systems integrated with AI capabilities; and advanced level, which
includes the development of customised solutions for specific educational needs.
The proposal emphasises the use of open-source technologies and collaborative
platforms that reduce licensing costs and allow for local customisation. This
includes the implementation of regional educational servers that provide AI
services in a decentralised manner, reducing dependence on external providers
and ensuring service continuity.
The technological dimension also considers aspects of data security and student
privacy, proposing specific protocols for handling sensitive educational
information. These protocols must comply with national and international
regulations while facilitating the effective use of AI technologies for legitimate
educational purposes.
Cognitive development and skills dimension
The third dimension focuses specifically on how generative AI can enhance
student cognitive development and the acquisition of skills relevant to the 21st
century. This dimension goes beyond the mere automation of educational tasks,
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
103
proposing approaches that use AI as a catalyst for developing critical thinking,
creativity, and complex problem-solving skills.
The proposed framework identifies five priority competency areas: analytical and
synthetic thinking, which is developed through structured interaction with AI
systems that require the formulation of complex questions; augmented creativity,
which combines human innovation capabilities with AI tools to explore expanded
creative possibilities; critical digital competence, which includes the ability to
evaluate and effectively utilise AI outputs; hybrid collaboration, which prepares
students to work effectively in teams that include both humans and AI systems;
and meta-learning, which develops the ability to reflect on and optimise one's own
learning processes.
The implementation of this dimension requires the design of specific educational
activities that leverage the unique strengths of generative AI while developing
complementary human capabilities. This includes AI-assisted research projects,
collaborative creative writing exercises with generative systems, and complex
simulations that require critical analysis of automated outputs.
Within the Ecuadorian context, this dimension must consider the specific needs
of the national and regional labour market, ensuring that the skills developed are
relevant to local economic opportunities while preparing students to participate in
the global digital economy.
Organisational and institutional dimension
The fourth dimension addresses the organisational and institutional changes
necessary to support educational transformation through generative AI. This
dimension recognises that the successful adoption of these technologies requires
substantial modifications to administrative structures, decision-making
processes, and institutional cultures.
The organisational proposal is structured around four levels of intervention: the
ministerial level, which includes the development of appropriate national policies
and regulatory frameworks; the district level, which covers regional coordination
and the distribution of technological resources; the institutional level, which
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
104
contemplates changes in the administrative and academic structures of schools
and universities; and the classroom level, which focuses on the transformation of
everyday teaching-learning dynamics.
The model proposes the creation of multidisciplinary teams for educational digital
transformation at each organisational level, including specialists in educational
technology, educators, administrators, and representatives of the educational
community. These teams would be responsible for planning, implementing, and
evaluating generative AI initiatives in a coordinated and sustainable manner.
The organisational dimension also considers aspects of change management,
recognising that the adoption of generative AI may generate resistance or anxiety
among teachers and administrators. The proposal includes communication,
training and support strategies designed to facilitate smooth transitions and
maximise institutional acceptance.
Ethical dimension and social sustainability
The fifth dimension addresses ethical, equity, and social sustainability
considerations associated with the implementation of generative AI in education.
This dimension recognises that these technologies can both amplify and reduce
existing educational inequalities, depending on how interventions are designed
and implemented.
The proposed ethical framework is based on principles of educational equity,
algorithmic transparency, respect for cultural diversity, and protection of student
rights. These principles are operationalised through specific protocols for auditing
AI systems, mechanisms for community participation in technological decisions,
and safeguards to prevent discriminatory biases.
The proposal includes the creation of regional ethical observatories responsible
for monitoring the social impact of generative AI in education, identifying
emerging problems, and proposing appropriate solutions. These observatories
would include representatives from different sectors of civil society, ensuring
diverse perspectives in the evaluation of technological impacts.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
105
The social sustainability dimension also considers aspects of preservation and
valorisation of Ecuadorian cultural heritage, proposing that generative AI
applications incorporate and promote traditional knowledge and local cultural
practices rather than homogenising educational experiences according to
external models.
Contextualised implementation strategies
The implementation of the METE-IAG model requires differentiated strategies
that take into account the regional, institutional and socio-cultural particularities
of Ecuador. A phased implementation approach is proposed, allowing for
progressive adaptation and continuous institutional learning.
Awareness-raising and institutional preparation phase
The first phase of implementation focuses on raising awareness of the
transformative potential of generative AI and preparing the institutional conditions
necessary for its successful adoption. This phase includes awareness-raising
activities targeting different actors in the education system, from ministerial
authorities to classroom teachers.
Proposed activities include introductory seminars on generative AI for educational
administrators, practical workshops for teachers demonstrating concrete
applications of these technologies, and informational sessions for parents
addressing common benefits and concerns. These activities should be designed
considering different levels of technological familiarity and using cases
contextualised to the Ecuadorian environment.
The preparation phase also includes institutional capacity assessments that
identify the specific strengths and limitations of each educational institution.
These assessments cover technological, pedagogical, organisational, and
financial aspects, providing a solid foundation for individualised implementation
planning.
During this phase, the technical and pedagogical support infrastructure
necessary for subsequent phases is also established, including the formation of
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
106
local technical teams and the creation of support networks among educational
institutions.
This ensures that institutions do not face technological transformation in isolation.
Pilot and controlled experimentation phase
The second phase implements pilot projects in selected educational institutions,
allowing for controlled experimentation and evidence-based learning prior to
systemic expansion. These pilots are designed to test different aspects of the
METE-IAG model in real-world conditions, generating empirical data on
effectiveness and implementation challenges.
The pilot projects are structured into three categories: pedagogical pilots, which
test specific applications of generative AI in different subjects and educational
levels; organisational pilots, which experiment with new administrative structures
and decision-making processes; and technological pilots, which evaluate
different AI platforms and tools in real educational contexts.
Each pilot project includes rigorous monitoring and evaluation protocols that
capture both quantitative results and qualitative experiences of participants. This
includes measurements of academic performance, student engagement
indicators, teacher satisfaction evaluations, and organisational impact analyses.
The lessons learned from the pilot projects are systematically documented and
shared with the entire educational community through accessible reports,
detailed case studies, and experience-sharing sessions. This collective learning
process informs adjustments to the METE-IAG model and paves the way for
further expansion.
Progressive scaling phase
The third phase expands implementation in a gradual and sustainable manner,
incorporating lessons learned from previous phases and adapting strategies
according to the specific characteristics of different regions and types of
institutions. This phase uses organic scaling approaches that respect natural
institutional rhythms.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
107
Scaling is structured geographically, taking into account regional disparities in
technological infrastructure and institutional capacities. Regions with greater
technological preparedness serve as centres for advanced experimentation,
while regions with limitations receive additional support and implementation
tailored to their specific conditions.
During this phase, inter-institutional support networks are consolidated to
facilitate the exchange of experiences, resources, and best practices among
educational institutions. These networks include both face-to-face and virtual
components, maximising access to specialised knowledge regardless of
geographic location.
The scaling phase also includes the development of local capacities for technical
and pedagogical support, reducing dependence on external expertise and
ensuring long-term sustainability. This includes certification programmes for
educational AI specialists and the creation of regional educational innovation
centres.
Impact and evaluation indicators
The METE-IAG model includes a comprehensive monitoring and evaluation
system designed to capture multiple dimensions of impact and facilitate
continuous improvement. This system combines traditional quantitative indicators
with innovative metrics specific to AI-assisted learning contexts.
Academic performance indicators
Traditional academic performance indicators remain a central component of the
evaluation system, but are complemented by specific metrics that capture the
unique benefits of generative AI. These include improvements in AI-assisted
writing skills, development of digital research competencies, increases in
creativity and originality of student projects, and advances in complex problem-
solving that require human-AI collaboration.
Proposed metrics include longitudinal analyses of student progress comparing
pre- and post-implementation periods, learning transfer assessments that
measure the application of developed competencies in new contexts, and critical
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
108
thinking assessments that evaluate the ability to reflectively analyse and evaluate
AI outputs.
Of particular importance is the development of assessment tools that distinguish
between genuine improvements in learning and excessive dependence on AI
tools. This requires careful design of assessment tasks that capture deep
understanding and independent application skills, differentiating them from
superficial technological utilisation skills.
Cognitive development indicators
The assessment system includes specialised metrics to capture impacts on
student cognitive development, recognising that generative AI can influence
fundamental thinking and learning processes. These indicators are designed to
detect both potential benefits and risks associated with the use of these
technologies.
Cognitive development metrics include metacognition assessments that measure
students' abilities to reflect on their own learning processes, cognitive flexibility
assessments that evaluate mental adaptability to changing situations, and
synthesis ability measurements that analyse skills for integrating information from
multiple sources, including AI outputs.
Of particular relevance is the monitoring of question-formulation abilities,
recognising that effective interaction with generative AI requires sophisticated
interrogation and requirement specification skills. Assessments include analysis
of the quality of student-generated prompts and the effectiveness of iterative
refinement strategies.
The system also includes early warning indicators to identify potential over-
reliance or the development of counterproductive cognitive habits. These
indicators allow for timely interventions to maintain healthy balances between
technological assistance and the development of autonomous capabilities.
Equity and access indicators
Considering the socio-economic inequalities that exist in the Ecuadorian context,
the evaluation system includes specific metrics to monitor impacts on educational
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Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
109
equity and access to learning opportunities. These indicators ensure that the
implementation of generative AI reduces rather than amplifies existing
educational gaps.
Equity indicators include analysis of the geographical distribution of benefits,
comparisons of impact between different socioeconomic groups, assessments of
differential access to AI technologies, and measurements of the digital divide in
the effective use of generative tools. These analyses consider multiple
dimensions of diversity, including geographic location, socioeconomic status,
gender, ethnicity, and special educational needs.
Particularly important is the monitoring of unintended effects that could
disadvantage specific groups, such as algorithmic biases in AI tools or
technological requirements that exclude students with limited resources. The
system includes protocols for early identification and correction of these
problems. The metrics also include assessments of community participation in
decisions about technology implementation, ensuring that different sectors of
Ecuadorian society have a voice in shaping future educational policies that
directly affect them.
DISCUSSION
The systematic review of specialised literature reveals an emerging consensus
on the transformative potential of generative artificial intelligence in educational
contexts, but also identifies significant challenges that require careful attention
during implementation processes. The results suggest that these technologies
can function as catalysts for pedagogical innovation, but their effectiveness
critically depends on specific contextual and implementation factors.
Consistent with the approaches presented by Bobula (2024), the results indicate
that generative AI offers unprecedented opportunities for educational
personalisation and learning process optimisation. However, realising this
potential requires comprehensive implementation frameworks that
simultaneously address technical, pedagogical, organisational, and ethical
dimensions. This multidimensional perspective is particularly relevant to the
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
110
Ecuadorian context, where resource constraints and regional disparities demand
carefully planned strategic approaches.
Consistent with the observations documented by Farrelly and Baker (2023), the
results emphasise the importance of practical and institutional considerations in
the adoption of generative AI. The reviewed literature suggests that the success
of these implementations depends on both technical factors and organisational
capacities to manage change and maintain focus on fundamental educational
objectives.
Particularly relevant is the convergence among multiple studies on the need to
maintain appropriate balances between technological assistance and the
development of autonomous human capacities. The contributions made by
Chaparro-Banegas et al. (2024) and Gonsalves (2024) reinforce the perspective
that generative AI should complement, not replace, the development of critical
thinking and analytical skills in students.
The specific implications for the Ecuadorian education system emerge from the
analysis of convergences between international evidence and national
particularities. The proposed METE-IAG model recognises that the successful
adoption of generative AI in Ecuador requires significant adaptations that take
into account infrastructural limitations, cultural diversity and national development
objectives.
Consistent with the approaches outlined by Bustard and Ghisoiu (2025) on
asynchronous approaches in digital education, the Ecuadorian context presents
unique opportunities to implement innovative models that transcend traditional
geographical and temporal limitations. Disparities between urban and rural
regions can be addressed through technological solutions that democratise
access to high-quality educational resources, regardless of physical location.
However, the observations described by Zhai et al. (2024) on the risks of
excessive dependence are particularly relevant for contexts with limited
resources, where the temptation to use generative AI as a substitute for
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Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
111
investments in teacher training or basic educational infrastructure could have
counterproductive long-term consequences.
The contributions documented by Vieriu and Petrea (2025) on impacts on student
academic development suggest that the Ecuadorian context could benefit
significantly from carefully designed implementations, particularly in areas where
the traditional education system faces persistent challenges such as
personalisation of learning and attention to student diversity.
The analysis reveals significant convergences between results from different
geographical and educational contexts, suggesting general principles for the
effective implementation of generative AI in education. These convergences
provide a solid basis for extrapolating best practices to the specific Ecuadorian
context.
Multiple studies agree in identifying the personalisation of learning as a central
benefit of generative AI, consistent with the approaches presented by Ding et al.
(2024) and Narang et al. (2025). This convergence suggests that the adaptive
capabilities of these technologies represent genuine competitive advantages
over traditional methodologies, regardless of the specific context of
implementation.
Similarly, the contributions made by Singh and Huang (2025) on enhancing
creativity through generative AI are supported by multiple studies documenting
similar benefits in different disciplinary and geographical contexts. This
convergence is particularly promising for the Ecuadorian context, where the
development of creative economies is a strategic national priority.
Warnings about the need for ethical frameworks and equity considerations,
present in works developed by Gerlich (2025) and other authors, also show
transnational consistency, suggesting that these challenges transcend specific
contextual particularities and require universal attention.
Although the literature shows important convergences, tensions and divergences
also emerge that reflect different priorities, contexts, and disciplinary
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Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
112
perspectives. These divergences provide valuable insights into the complexities
inherent in the implementation of generative AI in education.
A central tension appears between approaches that emphasise efficiency and
scalability versus those that prioritise pedagogical depth and human
relationships. While studies such as those developed by Grewal et al. (2025)
highlight the benefits of automation and optimisation, other contributions
emphasise the irreplaceability of human dimensions in education.
Another significant divergence emerges in assessments of the appropriate timing
for implementation. Some studies suggest immediate adoption to avoid
technological lag, while others recommend more cautious approaches that allow
for the development of regulatory frameworks and institutional capacities prior to
systemic implementation.
Perspectives on the appropriate degree of integration also vary considerably,
from approaches that propose radical transformation of educational
methodologies to others that suggest gradual integration that preserves the
strengths of traditional systems.
The discussion must recognise inherent limitations in both the literature reviewed
and the proposals developed. Most of the studies analysed come from
educational contexts developed with resources superior to those available in
Ecuador, limiting the direct applicability of results and recommendations.
Additionally, the emerging nature of the field means that empirical evidence on
long-term impacts remains limited. Available studies focus predominantly on
short-term implementations, making it difficult to assess the sustainability and
lasting effects of these technological interventions.
The literature also shows limitations in terms of methodological diversity, with a
predominance of qualitative studies and case studies over rigorous experimental
research. This limitation affects the ability to establish clear causal relationships
between generative AI implementation and specific educational outcomes.
Future research directions should include longitudinal studies examining long-
term impacts, experimental research that establishes causality more clearly, and
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Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
113
studies specifically designed for resource-limited contexts such as Ecuador.
Particularly important is the development of assessment methodologies
appropriate for AI-assisted learning contexts.
This research contributes to the emerging field of educational AI by developing
an integrated conceptual framework that considers multiple dimensions of
technology implementation in specific contexts. The METE-IAG model represents
an innovative synthesis that combines contemporary theoretical perspectives
with practical considerations appropriate for developing education systems.
Theoretically, the research contributes to the conceptual evolution of the field by
proposing interrelated dimensions that transcend the one-dimensional
approaches common in preliminary literature. This multidimensional perspective
provides more comprehensive frameworks for understanding the complexities
inherent in educational transformation through emerging technologies.
Practically, the research offers specific and contextualised strategies for
implementation that can inform educational policies and institutional decisions in
Ecuador and similar contexts.
The proposals include detailed considerations of resources, institutional
capacities, and sociocultural factors that are often omitted in more general
frameworks.
The research also contributes to debates on digital equity in education, proposing
specific approaches to ensure that the benefits of generative AI are distributed
equitably across different social groups and geographic regions.
Considerations of sustainability and scalability emerge as determining factors for
the long-term success of generative AI implementations in Ecuadorian education.
The reviewed literature suggests that many educational technology initiatives fail
due to inadequate planning for financial, technical, and organisational
sustainability.
The METE-IAG model addresses these concerns through phased approaches
that allow for gradual institutional learning and local capacity building.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
114
This perspective recognises that sustainability requires more than initial financial
resources, demanding the development of technical, pedagogical and
organisational support ecosystems.
Of particular importance is the consideration of cultural sustainability, ensuring
that technological implementations respect and strengthen local identities rather
than imposing homogenised educational models. This perspective is essential for
the Ecuadorian context, which is characterised by significant cultural diversity.
Scalability also requires careful consideration of financing models that allow for
gradual expansion without compromising quality or equity. Proposals include
combinations of public investment, public-private partnerships, and the use of
open source technologies to maximise cost-effectiveness.
CONCLUSION
The proposed METE-IAG model represents an innovative contribution that
synthesises contemporary theoretical perspectives with practical considerations
specific to the national context. The five interrelated dimensions of the model
provide a comprehensive framework for planning, implementing, and evaluating
generative AI initiatives in education, considering Ecuador's infrastructural,
cultural, and socioeconomic particularities.
The results indicate that generative AI can effectively function as a catalyst for
educational personalisation, 21st-century skills development, and pedagogical
process optimisation. However, realising this potential critically depends on
carefully designed implementations that maintain appropriate balances between
technological assistance and the development of autonomous human capacities.
Particularly significant is the evidence on the capabilities of generative AI to
address persistent educational challenges in the Ecuadorian context, including
regional disparities in access to educational resources, limitations in learning
personalisation, and digital skills development needs. The proposed strategies
offer viable pathways to capitalise on these opportunities while minimising
associated risks.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
115
Ethical and equity considerations emerge as fundamental factors for responsible
implementation, requiring appropriate regulatory frameworks and community
participation mechanisms to ensure equitable distribution of technological
benefits. The proposal for regional ethical observatories represents an important
innovation for continuous monitoring of social impacts.
The research also highlights the critical importance of teacher training and
organisational development as prerequisites for successful adoption. The
pedagogical transformations facilitated by generative AI require new professional
skills and adapted institutional structures, demanding significant investments in
human capacity development.
The limitations identified, including limited empirical evidence on long-term
impacts and a predominance of studies in developed contexts, suggest important
directions for future research. Longitudinal studies in resource-constrained
contexts and the development of appropriate evaluation methodologies for AI-
assisted learning are particularly needed.
The practical implications of this research extend beyond the specific Ecuadorian
context, providing valuable insights for other developing education systems
considering the adoption of emerging technologies. The multidimensional and
contextualised approach can be adapted to different national and regional
realities.
Financial, technical, and cultural sustainability emerges as a fundamental
consideration that requires strategic planning from the initial stages of
implementation.
The proposed financing models and local capacity-building strategies offer viable
approaches to ensure lasting impact.
This research therefore contributes to contemporary debates on the future of
education in the digital age, proposing approaches that leverage technological
advantages while preserving fundamental educational values. The perspective of
complementarity between human and artificial capabilities offers promising
directions for responsible educational evolution.
Cognopolis
Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
116
FINANCING
Non-monetary
CONFLICT OF INTEREST
There is no conflict of interest with individuals or institutions linked to the
research.
ACKNOWLEDGEMENTS
We acknowledge the tireless work of Ecuadorian teachers who, in diverse
geographical and sociocultural contexts throughout the country, strive daily to
offer quality educational experiences despite limited resources, demonstrating
that true educational transformation lies in human commitment rather than
technological tools.
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Revista de educción y pedagogía
Vol. 3(3), 94-117, 2025
Inteligencia artificial generativa en educación ecuatoriana: Transformación pedagógica y desarrollo cognitivo
Generative artificial intelligence in Ecuadorian education: Pedagogical transformation and cognitive
development
Jorge Hamilton Leal-Cevallos
Luby Claudia Ramírez-Álava
Estrella del Rosario Loor-Burgos
Cecilia del Rocío Álava-Cevallos
117
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Copyright: 2025 By the authors. This article is open access and distributed under the terms and conditions of
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