Cognopolis

Revista de educción y pedagogía

Vol. 3(2), 21-36 2025

https://doi.org/10.62574/wnvtft78

Artificial Intelligence as a tool to personalise learning in social sciences in

Ecuadorian education

Inteligencia Artificial como herramienta para personalizar el aprendizaje

en ciencias sociales en la educación ecuatoriana

Rously Eedyah Atencio-Gonzalez

reatenciog@ube.edu.ec

Universidad Bolivariana del Ecuador, Durán, Guayas, Ecuador

https://orcid.org/0000-0001-6845-1631

Marco Vinicio Calderón-Yánez

marco.calderon@quito.gob.ec

Secretaría de Educación Recreación y Deporte del DMQ, UEM Rafael Alvarado, Quito, Pichincha,

Ecuador

https://orcid.org/0009-0007-1823-7849

Elvia Marina Sangucho-Leines

sanguchoelvia@yahoo.com

Secretaría de Educación Recreación y Deporte del DMQ, UEM Rafael Alvarado, Quito, Pichincha,

Ecuador

https://orcid.org/0009-0001-0089-9293

Gladys Monserrate Zamora-Encalada

gladysmon60@hotmail.com

Secretaría de Educación Recreación y Deporte del DMQ, UEM Rafael Alvarado, Quito, Pichincha,

Ecuador

https://orcid.org/0009-0005-8728-8450

ABSTRACT

The research objective is to generate an emerging theory on Artificial Intelligence as a tool for personalising

learning in social sciences in Ecuadorian education from a hermeneutic perspective. Methodologically, the

study was based on contemporary educational hermeneutics. Three central categories emerged: i)

curriculum adaptation, ii) equitable access to knowledge, and iii) pedagogical transformation. The

hermeneutic analysis of the twenty-nine studies examined shows that artificial intelligence, when critically

articulated with teaching practice and inclusion policies, operates as a systemic catalyst that reconfigures

the teaching of social sciences in Ecuador. The emerging PACTE theory demonstrates that personalised

learning only makes full sense if algorithms maintain flexible curriculum adaptation, guarantee equitable

access to knowledge, and promote pedagogical transformation oriented towards critical thinking and Good

Living.

Descriptors: artificial intelligence; educational technology; educational policy. (Source: UNESCO

Thesaurus).

RESUMEN

Se estructura como objetivo de investigación generar una teoría emergente sobre Inteligencia Artificial como

herramienta para personalizar el aprendizaje en ciencias sociales en la educación ecuatoriana desde una

mirada hermenéutica. Metodológicamente se trabajó desde la hermenéutica educativa contemporánea.

Emergieron tres categorías centrales: i) adaptación curricular, ii) acceso equitativo al conocimiento y iii)

transformación pedagógica. El análisis hermenéutico de los veintinueve estudios examinados evidencia que

la inteligencia artificial, cuando se articula críticamente con la praxis docente y las políticas de inclusión,

opera como un catalizador sistémico que reconfigura la enseñanza de las ciencias sociales en Ecuador; la

teoría emergente PACTE demuestra que la personalización del aprendizaje solo cobra pleno sentido si los

algoritmos mantienen una adaptación curricular flexible, garantizan un acceso equitativo al conocimiento y

fomentan una transformación pedagógica orientada al pensamiento crítico y al Buen Vivir.

Descriptores: inteligencia artificial; tecnología educacional; política educacional. (Fuente: Tesauro

UNESCO).

Received: 02/03/2025. Revised: 11/03/2025. Approved: 01/04/2025. Published: 03/05/2025.

articles

Cognopolis

Revista de educción y pedagogía

Vol. 3(2), 21-36, 2025

Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

ecuatoriana

Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

INTRODUCTION

The growing convergence between artificial intelligence (AI) and social science

teaching poses epistemological challenges and unprecedented opportunities for

Ecuadorian education; in this sense, AI-assisted personalisation transcends mere

technological adaptation and is configured as a hermeneutic process where

students and teachers reinterpret social knowledge based on their cultural

contexts. Thus, didactic innovation requires a comprehensive understanding that

goes beyond traditional instrumental approaches (Alejandro-Cortés, 2024).

As a result of the above, in terms of pedagogical practice, AI has shown its

capacity to dynamise classroom experiences mediated by visual resources and

interactive narratives, which favours the critical construction of historical and civic

knowledge (Coronado-Martín, 2022; Ordoñez-Ocampo et al., 2021). However,

there are gaps when transferring these advances to Ecuadorian environments

characterised by inequalities of access and sociolinguistic diversity (Bernal-

Párraga et al., 2024; López et al., 2021), therefore, such a gap emphasises the

urgency of an interpretative model that recognises territorial particularities and

the aspirations of Buen Vivir.

Continuing with the above, from the perspective of personalised learning, AI is

offered as a catalyst for unique training trajectories that cater to individual

cognitive styles, rhythms and motivations (Fernández-Jiménez, 2024; Yépez-

Álvarez et al., 2024). However, their effective implementation requires a

theoretical scaffolding capable of articulating the algorithmic dimension with the

critical aims of the social sciences, that is, the training of reflective subjects

committed to social transformation (Pallo-Buse et al., 2024). Along these lines, it

is essential to equip teachers with the skills to orchestrate processes of

interpretation and dialogue with intelligent systems (Guacán-Tandayamo et al.,

2023).

Cognopolis

Revista de educción y pedagogía

Vol. 3(2), 21-36, 2025

Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

ecuatoriana

Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

Based on the above, is structured as a research objective to generate an

emerging theory on Artificial Intelligence as a tool for personalising learning in the

social sciences in Ecuadorian education from a hermeneutic perspective.

Theoretical entry points

The personalisation of learning through artificial intelligence (AI) has been

configured as one of the most promising vectors for revitalising the teaching of

social sciences in Ecuador, a context characterised by socio-cultural

heterogeneity and inequalities of access. Firstly, the contributions of Acosta-

Faneite & Finol-de-Franco (2024) show that AI, conceived as an academic

management system, enables curricular decisions based on predictive analytics,

increasing the relevance of university training itineraries. This thesis of intelligent

management converges with the proposal of Alejandro-Cortés (2024), who

highlights that institutional creativity expands when AI is aligned with knowledge

management models oriented towards pedagogical innovation.

In this context, from contextual didactics, Amado Angulo (2024) shows that the

situated reinterpretation of historical phenomena is enhanced when the adaptive

system recommends resources linked to the immediate reality of the students.

Similarly, Cevallos-Cedeño & Aguilar-Oña (2024) document in higher basic

education the effectiveness of recommendation algorithms to adjust conceptual

complexity and multimodal supports according to the sociolectual profile of each

student.

On the other hand, the Ecuadorian landscape offers important empirical evidence

on the adoption of AI, in this sense, Aparicio-Izurieta (2024) portrays the

favourable perceptions of university teachers, while Taipicaña-Vergara et al.

(2024) identify factors such as infrastructure, training and policies that condition

its integration. Complementarily, Ayala-Chauvin, Avilés-Castillo & Buele (2023)

confirm that the analysis of educational data in Ecuador is moving from mere

descriptive statistics towards predictive models that support personalisation.

Cognopolis

Revista de educción y pedagogía

Vol. 3(2), 21-36, 2025

Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

While in the particular field of social sciences, Bernal-Párraga et al. (2024)

present experiences of AI as a mediator in social studies projects, highlighting the

transition from the role of teacher to that of dialogic facilitator; a proposal that

harmonises with the systematic review by Bolaño-García & Duarte-Acosta

(2024), which highlights that personalisation increases active participation and

critical thinking. Precisely, Borja-Ramos et al. (2024) show that AI-guided projects

foster critical skills by articulating historical data with local issues.

In this context, Dave & Patel (2023) draw parallels between education and health,

positing that AI is legitimised by improving the accuracy of pedagogical

diagnoses. This inclusive perspective is reinforced by Guacán-Tandayamo et al.

(2023), who describe AI as a compensatory resource for students with academic

lags, while Jadán-Guerrero et al. (2024) mention its potential in special education

through adaptive environments.

Likewise, the need for an ethical-critical framework is emphasised, as Fernández-

Jiménez (2024) warns that algorithms must avoid biases that perpetuate

inequalities, while González-Torres et al. (2024) suggest academic transparency

protocols. In addition, Guerrero-Quiñonez et al. (2023) stress the urgency of data

governance policies in Latin American higher education.

From a didactic perspective, Coronado-Martín (2022) and Ordoñez-Ocampo et

al. (2021) argue that AI can enrich historical narratives through artistic

visualisation and heuristic strategies, while López, Cabrera & Ocampo (2021)

insist that the social meaning of the discipline is preserved if technologies

promote the problematisation of reality. Along the same lines, Miralles Martínez,

Campillo Ferrer & Prats Cuevas (2023) postulate that AI contributes to dealing

with times of uncertainty by providing dynamic socio-historical simulations.

In an unfavourable contrast to the effective application of AI, Mena-Salcedo,

Robles-Bykbaev & Robles-Bykbaev (2025) report the perception of teachers

who, despite their enthusiasm, demand continuous training to take advantage of

Cognopolis

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Vol. 3(2), 21-36, 2025

Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

AI without diluting critical thinking. In parallel, Mora-Aristega et al. (2023) warn

about the digital divide in basic education and the need for differentiated

strategies. While the perspectives of Pallo-Buse et al. (2024) and Peñalver-

Higuera et al. (2024) emphasise that AI must be aligned with the demands of the

Fourth Industrial Revolution to avoid curricular obsolescence, while Piedra-

Castro et al. (2024) highlight the relevance of open standards that facilitate the

interoperability of resources.

In terms of equity, Rojas-Díaz (2023) shows that AI can mitigate the effects of

social crises through resilient learning pathways, while Salas-Pilco & Yang (2022)

mention the importance of redistributive infrastructure policies. Thus, Villegas-Ch,

García-Ortiz & Sánchez-Viteri's (2024) machine learning model demonstrates the

efficacy of adjusting individual cognitive styles; and Yépez-Álvarez et al. (2024)

highlight the need to assess student satisfaction as an indicator of personalisation

success.

METHOD

The research is part of contemporary educational hermeneutics, understood as

a qualitative strategy that seeks to unravel the meanings implicit in pedagogical

and technological discourses. Therefore, a hermeneutic-documentary design is

adopted that articulates the pre-compression of the research team with a dialogic

process of interpretation and reinterpretation of academic texts on artificial

intelligence (AI) and social sciences in Ecuadorian education.

A purposive corpus of twenty-nine (29) studies published between 2021 and 2024

that address personalisation of learning through AI in Ecuadorian or analogous

regional contexts was formed. The selection considered:

a) Thematic relevance: work linking AI, personalisation and social sciences.

b) Academic rigour: articles indexed in Scopus, Web of Science or Latindex,

as well as conference proceedings with a scientific committee.

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Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

c) Ecuadorian contextuality: research carried out totally or partially in

Ecuadorian institutions or that explicitly discusses its socio-educational

reality.

Interpretative procedure

The process was developed in four non-linear phases:

1) Critical pre-compression: The research team mapped beliefs and

assumptions about AI and social science in Ecuador, recognising initial

biases.

2) Structural reading: Each text was approached with dialogical analysis:

units of meaning related to curricular adaptation, equitable access and

transformation were identified.

3) Fusion of horizons: Next, codes were compared across documents and

matrices of convergence were constructed that allowed for the tensioning

of technocentric perspectives with critical visions of social justice. This

dynamic produced the interpretative triad that underpins the emerging

PACTE theory.

4) Consensual validation: A hermeneutic circle was carried out with three

external teacher-researchers familiar with the subject. They contrasted the

coherence of the categories and provided counter-examples that made it

necessary to refine definitions and relationships.

Criteria of rigour

To ensure credibility and transferability, the following criteria were applied:

a) Triangulation of sources: contrasting empirical articles, systematic reviews

and policy documents.

b) Audit trail: detailed recording of analytical decisions in a shared repository.

c) Theoretical saturation: incorporation of new texts stopped when no distinct

codes emerged during two consecutive rounds of analysis.

Cognopolis

Revista de educción y pedagogía

Vol. 3(2), 21-36, 2025

Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

Ethical considerations

Although the study was based on public sources, the guidelines of the Declaration

of Helsinki adapted to documentary educational research were respected, taking

care to ensure the correct attribution of ideas and avoiding extracts that could

compromise the originality of the authors cited. An anti-plagiarism manager was

used to check that the interpretations were unpublished and legitimate.

RESULTS

The hermeneutic analysis applied to the research on the use of artificial

intelligence (AI) in the personalisation of learning in social sciences in Ecuador is

organised into three central categories: i) curricular adaptation, ii) equitable

access to knowledge and iii) pedagogical transformation. These categories

emerge as transversal aspects to understand the potentials and challenges of AI

in the Ecuadorian educational context:

Curricular adaptation

The first category, curricular adaptation, shows that AI facilitates the

personalisation of educational content according to the needs and learning

rhythms of students. According to Cevallos-Cedeño & Aguilar-Oña (2024), the

incorporation of AI allows the design of more flexible curricula adapted to the

individual characteristics of students, which improves their motivation and

learning performance; this change in the teaching of social sciences reflects a

trend towards a more dynamic curriculum, which responds to the demands of

higher education in Ecuador (Peñalver-Higuera et al., 2024).

Equitable access to knowledge

The second category, equitable access to knowledge, highlights how AI can level

educational opportunities by providing access to quality learning resources,

regardless of geographical or socio-economic constraints. In this order, the work

of Ayala-Chauvin, Avilés-Castillo & Buele (2023), have shown that the

Cognopolis

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Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

implementation of AI in educational institutions in Ecuador, both in rural and urban

areas, improves inclusion by offering personalised materials for students with

different needs; in complement, Aparicio-Izurieta (2024) points out that this

technology helps to overcome access barriers, promoting a more inclusive and

equitable education.

Pedagogical transformation

Therefore, the category pedagogical transformation refers to how the integration

of AI in the teaching of social sciences drives a change in pedagogical practices.

The results of the study by González-Torres et al. (2024) show that the use of AI

promotes a more student-centred teaching, where the teacher becomes a guide

and facilitator of the learning process, rather than a simple transmitter of

knowledge, which contributes to students developing critical and reflective skills

through interactive-adaptive tools (Borja-Ramos et al., 2024).

Implications of AI for Ecuadorian education

The use of AI in personalising learning offers an opportunity to improve education

in Ecuador; however, as the study by Bernal-Parraga et al. (2024) points out,

challenges related to technological infrastructure and teacher training are also

identified, which require strategic planning to ensure effective implementation at

all educational levels, indicating that AI has the potential to be a transformative

tool, but its success depends on a comprehensive approach that considers both

technical and pedagogical aspects.

Emerging theory PACTE: Personalisation with AI for curriculum adaptation,

pedagogical transformation and equity in social sciences in Ecuadorian

education.

Hermeneutical basis

The interpretative analysis of 29 studies used in the research, which cover

experiences in basic education, high school and higher education, revealed

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Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

shared meanings around the use of artificial intelligence (AI) as a vector of

personalisation of learning in social sciences in Ecuador, from three central

categories: (i) curricular adaptation, (ii) equitable access to knowledge and (iii)

pedagogical transformation; which act as hermeneutic axes that, when

intertwined, configure a triadic logic irreducible to its parts (Cevallos-Cedeño &

Aguilar-Oña, 2024; Ayala-Chauvin et al., 2023; González-Torres et al., 2024). From

this interweaving emerges the emerging PACTE theory.

Central proposition

In Ecuadorian social science environments, AI-mediated personalisation

materialises when the algorithm becomes a flexible, democratising and reflexive

curricular artefact that readjusts learning trajectories in real time and, at the same

time, reconfigures the teacher-teacher role within a situated educational ecology.

In other words, AI is not a simple technological resource, but a didactic device

that, by converging with inclusion policies and critical classroom practices, co-

produces meaningful learning, while reducing historical gaps (Peñalver-Higuera

et al., 2024; Aparicio-Izurieta, 2024).

Table 1. Constituent dimensions of PACTE

Dimension

Conceptual core

Empirical evidence

Theoretical contribution

Curricular

adaptation

Machine learning

algorithms that

recommend

personalised routes,

resources and rhythms

according to cognitive

and socio-cultural

profiles.

Systems that adjust the

difficulty of social studies in

real time (Villegas-Ch et al.,

2024); flexible curricula based

on educational analytics

(Piedra-Castro et al., 2024).

The curriculum becomes

self-regulating: it

distances itself from linear

sequences and adopts a

rhizomatic structure

capable of responding to

diversity and local

relevance.

Equitable

access to

knowledge

IA infrastructures and

platforms offering multi-

format content without

geographic or economic

restrictions.

Hybrid implementations in the

Amazon and Sierra that

reduce the urban-rural divide

(Ayala-Chauvin et al., 2023);

accessible materials for

students with disabilities

(Jadán-Guerrero et al., 2024).

AI functions as a cognitive

redistributor: it expands

opportunities and

consolidates the

constitutional principle of

good educational living.

Pedagogical

transformation

Shift of the teacher from

transmitter to designer

of experiences and of

Projects supported by

reflective chatbots that

enhance critical thinking

A dialogical epistemology

is configured: AI mediates

metacognitive processes

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Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

the student from

passive receiver to

critical agent in dialogue

with AI.

(Borja-Ramos et al., 2024);

communities of practice

supported by predictive

analytics (González-Torres et

al., 2024).

and favours the co-

construction of

contextualised

knowledge.

Source: Authors.

Systemic articulation

PACTE theory conceives of the three dimensions as interdependent subsystems:

curriculum adaptation requires equitable access frameworks to prevent

personalisation from exacerbating inequalities (Salas-Pilco & Yang, 2022); while

equitable access requires pedagogical transformation, as providing resources

without rethinking teaching roles reproduces transmissive models (Mora-Aristega

et al., 2023); and pedagogical transformation feeds back into curriculum

adaptation, refining algorithms with data generated in authentic practices (Mena-

Salcedo et al., 2025). This continuous feedback configures an autopoietic ecology

in which data, experiences and teacher reflections constantly remake the

education system (Taipicaña-Vergara et al., 2024).

Regulatory principles

a) Dynamic contextuality: all personalisation is anchored in concrete and

evolving socio-cultural realities (Amado Angulo, 2024).

b) Algorithmic fairness: AI models incorporate distributive justice and bias

mitigation criteria (Dave & Patel, 2023).

c) Augmented teaching: digital teaching competence expands into ethical

data curation and interactive narrative design (Acosta-Faneite & Finol-de-

Franco, 2024).

d) Critical reflexivity: students develop metacognition and social-historical

thinking through human-machine dialogues (Miralles Martínez et al., 2023).

Operational implications

Public policies: integrate AI infrastructure with digital inclusion plans, prioritising

marginalised areas and indigenous communities (Rojas-Díaz, 2023).

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Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

Teacher training: hybrid programmes combining social science epistemology with

applied data science (Guerrero-Quiñonez et al., 2023).

Ongoing research: longitudinal impact evaluations to measure the sustainability

of personalised outcomes (Bolaño-García & Duarte-Acosta, 2024).

Synthesis of the emerging theory PACTE

The emerging PACTE theory postulates that AI, far from being a mere technical

instrument, acts as a systemic catalyst that, by interconnecting curricular

adaptation, equitable access and pedagogical transformation, reshapes the

teaching of social sciences in Ecuador under parameters of justice, relevance

and autonomy; therefore, its successful implementation requires synergies

between technological innovation, educational policy and committed teaching

praxis.

CONCLUSION

The hermeneutic analysis of the twenty-nine studies examined shows that

artificial intelligence, when critically articulated with teaching praxis and inclusion

policies, operates as a systemic catalyst that reconfigures the teaching of social

sciences in Ecuador; the emerging PACTE theory demonstrates that the

personalisation of learning only makes full sense if algorithms maintain flexible

curricular adaptation, guarantee equitable access to knowledge and foster a

pedagogical transformation oriented towards critical thinking and Buen Vivir.

Under this triadic logic, AI ceases to be an instrumental resource and becomes a

hermeneutic device capable of reinterpreting localised knowledge, reducing

historical gaps and promoting meaningful and socially responsible educational

trajectories. However, its future effectiveness depends on the convergence of

inclusive infrastructures, teacher training programmes that integrate data science

and social epistemology, as well as regulatory frameworks that ensure algorithmic

equity and transparency in the educational use of data; only then will AI

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Inteligencia Artificial como herramienta para personalizar el aprendizaje en ciencias sociales en la educación

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Artificial Intelligence as a tool for personalising learning in social sciences in ecuadorian educationchildhood

education students

Rously Eedyah Atencio-González

Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

consolidate its promise to revitalise Ecuadorian education and form reflective

citizens committed to social transformation.

FUNDING

Non-monetary

CONFLICT OF INTEREST

There is no conflict of interest with persons or institutions involved in research.

ACKNOWLEDGEMENTS

To curriculum teachers who promote significant changes in education.

CONTRIBUTION OF THE AUTHORS

Rously Eedyah Atencio-González: Managed the planning of the

methodological approach to the research, specifically in the selection and

hermeneutic analysis of the academic texts, especially in the drafting of the

theoretical foundations and the construction of the PACTE emerging theory.

Marco Vinicio Calderón-Yánez: Worked on the literature review and the

identification of the central categories (curriculum adaptation, equitable access to

knowledge and pedagogical transformation).

Elvia Marina Sangucho-Leines: She worked on the analysis of the data and the

consensus validation through the hermeneutic circle with external teacher-

researchers, contributing to the drafting of the results.

Gladys Monserrate Zamora-Encalada: She worked on the integration of

theoretical perspectives in the hermeneutic framework, contributing to the writing

of the article, managing the coherence and compliance with the journal's ethical

standards and editorial norms.

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education students

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Marco Vinicio Calderón-Yánez

Elvia Marina Sangucho-Leines

Gladys Monserrate Zamora-Encalada

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