Diseño de un manual de capacitación en inteligencia
artificial para la elaboración de la planificación curricular en docentes d=
e educación
general básica
Design of an a=
rtificial
intelligence training manual for curriculum planning for general basic educ=
ation
teachers
1
Laura Josefina Vernaza Corozo<=
span
style=3D'color:black'>
https://orcid.org/0009-0004-74=
64-3815
Universidad
Bolivariana del Ecuador (UBE), Duran, Ecuador.
Maestría en Educac=
ión
l jvernazac<=
/span>@ube.edu.ec
2
Rosa Delfina Gómez Castro
https://orcid.org/0009-0007-17=
12-6100
Universidad
Bolivariana del Ecuador (UBE), Duran, Ecuador.
Maestría en Educac=
ión
rdgomezc @ube.edu.ec
3
Efraín Velastegui López
https://orcid.org/0000-0002-73=
53-5853
Universidad
Bolivariana del Ecuador (UBE), Duran, Ecuador.
evelasteguil @ube.e=
du.ec
4
Giceya Maqueira
Caraballo
https://orcid.org/0000-0001-62=
82-3027
Universidad
Bolivariana del Ecuador (UBE), Duran, Ecuador.
gdmaqueirac@ube.edu.ec
Artículo de Investigación Científica y Tecnológi=
ca
Enviado: 13/08/2026
Revisado: 11/09/2026
Aceptado: 05/10/2026
Publicado: 19/10/2026
DOI: https://doi.org/10.33262/ap.v8i4.722 <=
/span>
=
C=
ítese: <=
/o:p>
Vernaza Corozo, L. J., Gómez Castro, R. D.,
Velastegui López, E., & Maqueira Caraballo, G. (2026). Diseño de un
manual de capacitación en inteligencia artificial para la elaboración de =
la
planificación curricular en docentes de educación general básica. AlfaPublicaciones , 8(4), 115–139. https://doi.org/10.33262/ap=
.v8i4.722
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Copia de la licencia: http://creativecommons.org/l=
icenses/by-nc-sa/4.0/ <=
/o:p>
Pal=
abras
claves:
Diseño,
capacitación, inteligencia artificial, planificación curricular, profesor=
es.
Resumen
Introducción.
La
incorporación de Inteligencia Artificial (IA) en la educación, presenta
diferentes oportunidades de optimización dentro de la planificación
curricular y el proceso de enseñanza-aprendizaje. En épocas contemporánea=
s,
docentes en educación general básica exhiben limitaciones en el uso
pedagógico de herramientas IA por insuficiencia de información y capacida=
des
de aplicación. Objetivos. La investigación tiene por objetivo dise=
ñar
un manual de capacitación en IA, para fortalecer la elaboración de la
planificación curricular en docentes de educación general básica, mediant=
e la
integración de contenidos, recursos y ejercicios desarrollados con Genially . Metodología. Metodológicamente, el
estudio adoptó un enfoque mixto con diseño no experimental de corte
transversal y de alcance descriptivo-propositivo. La población fue confor=
mada
por 35 docentes perteneciente a la Unidad Educativa Aurelia Becerra,
aplicando como instrumentos de recolección: cuestionario de 12 ítems
categorizados mediante escala Likert, y entrevista semiestructurada
implementada a las autoridades educativas. Resultados. La
investigación presenta una estructura de tres fases conformada por:
diagnóstico (pretest), diseño del manual de capacitación (propuesta) y
evaluación de resultados (postest ), estableci=
endo
como resultados la presencia de competencias básicas y actitud favorable =
de
uso de herramientas IA por parte de la población, con limitaciones en
formación específica en su aplicación pedagógica. Conclusiones. Co=
ncluyendo,
el diseño e implementación del manual de capacitación en IA constituye una
alternativa pertinente en el fortalecimiento de las competencias docentes,
impulsando prácticas educativas innovadoras, éticas y contextualizadas. <=
b>Área
de estudio general: Educación. Área de estudio específica: Tec=
nología
e innovación educativas. Tipo de estudio: Artículos originales.
Keywords:
Design,
training, artificial intelligence, curriculum planning, teacher.
Abstract
Introduction.
The
incorporation of Artificial Intelligence (AI) in education presents diffe=
rent
opportunities for optimization within curricular planning and the
teaching-learning process. In contemporary times, teachers in basic gener=
al
education exhibit limitations in the pedagogical use of AI tools due to
insufficient information and application capacities. Objectives. T=
he
objective of this research is to design an AI training manual to strength=
en
the development of curriculum planning for basic general education teache=
rs,
through the integration of contents, resources, and exercises developed w=
ith
Genially. Methodology. Methodologically, the study adopted a mixed
approach with a non-experimental cross-sectional design and a
descriptive-propositional scope. The population was made up of 35 teachers
belonging to the Aurelia Becerra Educational Unit, applying as collection
instruments: a questionnaire of 12 items categorized by Likert scale, and=
a
semi-structured interview implemented with the educational authorities. <=
b>Results.
The research presents a structure of three phases made up of: diagnos=
is
(pretest), design of the training manual (proposal) and evaluation of res=
ults
(posttest), establishing as results the presence of basic competencies an=
d a
favorable attitude of use of AI tools by the population, with limitations=
in
specific training in their pedagogical application. Conclusions. In
conclusion, the design and implementation of the AI training manual
constitutes a pertinent alternative in the strengthening of teaching
competencies, promoting innovative, ethical, and contextualized education=
al
practices. General area of study: Education. Specific area of
study: Educational technology and innovation. Type of study:
Original articles.
1. Introducción <=
/b>
El diseño de un manual de
capacitación en Inteligencia Artificial (IA ) para docentes de EGB se
justifica por la necesidad de responder a los desafíos educativos de la
sociedad digital, caracterizada por el uso intensivo de tecnologías emergen=
tes
y por la demanda de competencias del siglo XXI. La integración de la IA en =
la
planificación curricular permite optimizar la organización de contenidos,
automatizar tareas administrativas y personalizar los procesos de
enseñanza-aprendizaje, favoreciendo una educación más inclusiva y centrada =
en
el estudiante, siendo que, la formación docente en IA no constituye únicame=
nte
una innovación tecnológica, sino una estrategia pedagógica orientada a mejo=
rar
la calidad educativa ( Merino-Campos , 2025).
Desde el apartado pedagó=
gico,
Chiu (2026) considera que la capacitación en IA fortalece y promueve prácti=
cas
educativas del profesorado, añadiendo perspectivas innovadoras en su
planificación curricular e incorporando el uso de recursos tecnológicos que
favorecen el análisis de datos. El autor menciona que, docentes que reciben
formación en tecnología incrementa su creatividad didáctica, confianza de u=
so,
planificación curricular contextualizada y dinámica, derivando positivament=
e en
la motivación y participación del estudiantado, elementos principales para =
un
aprendizaje significativo.
La propuesta desde la
perspectiva educativa y social se justifica debido la reducción de la brecha
digital y acceso igualitario de herramientas tecnológicas, derivado de la
capacitación al cuerpo docente. Según Aguilar-Cruz &
Salas-Pilco
(2025) en contextos latinoamericanos se presentan desigualdades en formació=
n e
infraestructura educativos, por tanto, el fortalecimiento de competencias
digitales docentes constituye un favor clave en el cumplimiento de las
funciones del docente, sin reemplazar los criterios pedagógicos o su función
formativa.
Esta investigación se
justifica por su aporte práctico, al proponer el desarrollo de un manual de
capacitación que incluya ejercicios y herramientas como Genially para la
elaboración de planificaciones curriculares. Este recurso facilitará la
integración progresiva de la IA en el trabajo docente, optimizando el tiemp=
o de
planificación y fortaleciendo el proceso pedagógico, en consecuencia, el
estudio contribuye a la innovación educativa, desarrollo profesional docent=
e y
mejora de la calidad del sistema educativo.
1.1. <=
/b>Inteligencia artificial
aplicada a la educación básica
Acorde con Zawacki-Richter et al. (2019) la
inteligencia artificial presenta un rol relevante dentro del ámbito educati=
vo
debido la capacidad de generación de contenidos educativos adaptativos,
análisis de datos y automatización de tareas, a través de una revisión
sistemática sus funcionalidades se establecen sistemas de tutoría inteligen=
te,
apoyo automatizado en procesos educativos y analítica del aprendizaje,
destacando su potencialidad en la transformación de las prácticas pedagógic=
as
tradicionales.
En este sentido, Chiu (2=
026)
explica que la inteligencia artificial en educación puede mejorar
significativamente los procesos de enseñanza y aprendizaje al automatizar
tareas pedagógicas, analizar patrones de aprendizaje y generar recursos
educativos personalizados que responden a las necesidades específicas de los
estudiantes, por lo tanto, estas herramientas tecnológicas amplían las
posibilidades de una mejora educativa.
La inteligencia artifici=
al
también contribuye a la construcción de entornos de aprendizaje más adaptat=
ivos
y centrados en el estudiante, siendo que, estas tecnologías permiten analiz=
ar
grandes volúmenes de datos educativos para identificar patrones de
comportamiento, dificultades de aprendizaje y niveles de progreso académico=
. Chen
et al. (2020) consideran que la implementación de IA facilita la
personalización del aprendizaje, favoreciendo marcos pedagógicos efectivos
basado en el análisis del rendimiento del estudiantado. <=
/p>
1.2. <=
/b>Capacitación docente en
competencias digitales e inteligencia artificial
Redecker & Punie (20=
17)
proponen acorde el marco europeo de competencia digital, el desarrollo de
habilidades pedagógicos acorde con la utilización de tecnologías
contemporáneas, buscando el fortalecimiento de recursos educativos e
implementación de estrategias innovadoras de enseñanza-aprendizaje.
En este contexto, la
integración efectiva de estas herramientas requiere la formación docente en
competencias pedagógicas dentro del proceso educativo. Por lo tanto, las
competencias tecnológicas y digitales dentro del profesorado se convirtiero=
n en
un requerimiento en el contexto escolar actual, siendo que Guillén-Gámez et al. (2022) establece=
n la
consolidación integral de estas herramientas, promoviendo metodologías
pedagógicas participativas y dinámicas.
La formación del profeso=
rado
en IA tendrá que abordar conocimientos técnicos e implicaciones pedagógicas=
y
éticas del proceso educativo, en este sentido Chiu (2026) considera que la
capacitación del profesorado en IA mejora la capacidad de integración tecno=
lógica
en la planificación curricular, facilitando la evaluación del aprendizaje,
organización de contenidos y generación de actividades.
1.3. <=
/b>Uso de herramientas
digitales interactivas en la planificación curricular
Cabero (2020) sostiene q=
ue
la incorporación de herramientas digitales en el marco educativo contribuye=
en
la mejora de la participación estudiantil, basado en la integración de
metodologías interactivas que interesen al estudiantado y sus necesidades
actuales. Producto del progreso tecnológico, el requerimiento del cuerpo
docente dentro de la planificación curricular precisa integrar recursos que
faciliten la comprensión de los contenidos, implementando elementos visuale=
s y
didácticos.
Las tecnologías digitales
facilitan la estructuración y organización de elementos que conforman la
planificación curricular, destinado al cumplimiento de los objetivos de
aprendizaje. En concordancia, Area & Adell (2009) destacan la necesidad=
de
modelos pedagógicos innovadores, enfocado en el aprendizaje activo del estu=
diantado.
Bond et al. (2020)
determinan la factibilidad de integrar herramientas digitales interactivas,
cuya conclusión se centra en su contribución con la interacción
estudiante-contenido, creando entornos participativos dentro del procesos
enseñanza. Plataformas digitales interactivas son consideradas como
instrumentos de creación de experiencias dinámicas y visuales, derivando en=
el
fortalecimiento del compromiso y motivación.
El objetivo general de la
investigación pretende diseñar un manual de capacitación en inteligencia
artificial para fortalecer la elaboración de la planificación curricular en
docentes de educación general básica, mediante la integración de contenidos,
recursos y ejercicios interactivos desarrollados con Genially. Se plantean =
como
objetivos específicos: (1) establecer fundamentos teóricos y prácticos de la
inteligencia artificial y su integración en la planificación curricular den=
tro
del proceso enseñanza-aprendizaje en educación general básica; (2) diseñar =
un
manual de capacitación en inteligencia artificial respecto la planificación
curricular que faciliten la estructuración de contenidos, actividades, recu=
rsos
y evaluaciones; (3) analizar la factibilidad del uso de herramientas digita=
les
de inteligencia artificial en la planificación curricular y fortalecimiento=
del
proceso enseñanza-aprendizaje.
<=
span
style=3D'font-size:12.0pt;line-height:115%;font-family:"Times New Roman",se=
rif;
mso-fareast-font-family:"Times New Roman";color:#767171;mso-themecolor:back=
ground2;
mso-themeshade:128'>2.
Metodología
La
investigación presenta un enfoque mixto en concordancia con información
cuantitativa y cualitativa, adoptada debido su naturaleza integral respecto=
las
percepciones, prácticas pedagógicas y competencias digitales del cuerpo doc=
ente
en relación con el uso de IA en la planificación curricular. Este enfoque p=
ermitió
el análisis de las variables, proporcionando información que fundamentó el
diseño de un manual de capacitación contextualizado y acorde los requerimie=
ntos
identificados en la población (Creswell & Clark, 2017).
Desde
su alcance, la investigación es descriptivo–propositivo, ya que busca
diagnosticar las causas que limitan el uso de la IA en la planificación
curricular y, posteriormente, proponer un manual de capacitación que incluya
ejercicios prácticos desarrollados mediante la herramienta Genially. Carchi=
pulla-Fajardo
et al. (2024) indican que este tipo de diseño es apropiado cuando se preten=
de
comprender una problemática educativa y generar soluciones aplicables al
contexto real.
El
diseño de estudio es no experimental de corte transversal, manteniendo una
observación sistemática del fenómeno con la preservación de las condiciones
propias del entorno, y la recolección de información durante un único momen=
to (Quevedo
et al., 2022), permitiendo el análisis del objeto de estudio en su contexto
real, con la privación de manipulación, control o intervención de las
variables.
La
población se constituyó por 35 docentes pertenecientes a la Educación
General Básica (EGB) de la Unidad Educativa Aurelia Becerra, por
considerarse una población pequeña se decidió trabajar con la totalidad de
individuos, eliminando el error muestral y fortaleciendo la validez de los
resultados obtenidos, por lo que no fue necesario aplicar un procedimiento
adicional de selección de muestra (Alcoba, 2024).
La
investigación emplea el método teórico en la fundamentación conceptual del
estudio mediante la revisión, análisis e interpretación crítica de literatu=
ra
científica, además se considera, el método empírico en la obtención de
información directa del contexto educativo a través de la aplicación de
instrumentos de recolección de datos dirigidos a docentes de EGB, también, =
se
incorpora el método estadístico descriptivo para la organización, tabulació=
n e
interpretación de los datos, siendo que, Ordoñez-Pacheco (2025) establece la
favorabilidad del método para la conversión de datos cuantitativos recolect=
ados
en información significativa para la comprensión del comportamiento de las
variables objeto de estudio.
El
estudio incorpora el cuestionario como técnica de recolección de datos
cuantitativos, descrito por Duarte & Guerrero (2024) como un instrument=
o de
recopilación de información de manera sistemática, organizada y objetiva so=
bre
las variables de estudio. El cuestionario tiene por objetivo identificar las
percepciones, conocimientos, competencias digitales y nivel de disposición =
de
los docentes respecto al uso de la inteligencia artificial en la elaboració=
n de
la planificación curricular. El instrumento se conformó por 12 ítems diseña=
dos
en función de los objetivos del estudio y organizados mediante una escala t=
ipo
Likert de cinco niveles de respuesta: totalmente en desacuerdo (1), en
desacuerdo (2), ni de acuerdo ni en desacuerdo (3), de acuerdo (4) y totalm=
ente
de acuerdo (5), permitiendo medir el grado de aceptación, percepción y
valoración de los participantes frente al fenómeno estudiado (Machuca et al=
.,
2023).
Desde
el componente cualitativo, se aplicó una entrevista semiestructurada dirigi=
da a
las autoridades (rector, vicerrector e inspector) de EGB pertenecientes a la
institución educativa, con el propósito de profundizar en sus percepciones,
experiencias y criterios respecto al uso de la inteligencia artificial en la
planificación curricular y procesos de formación docente. La entrevista
semiestructurada permita la combinación de interrogantes definidas previame=
nte,
pero con la flexibilidad necesaria para indagar aspectos relevantes que pue=
den
emerger durante el diálogo, favoreciendo la obtención de información
contextualizada y extensa respecto el fenómeno de estudio. En este contexto=
González
et al. (2022) refieren al instrumento como indicado para la comprensión de
significados atribuidos, experiencias y opiniones del participante, consist=
ente
para el análisis de la realidad educativa actual, por lo tanto, la informac=
ión
recolectada permitió la identificación de percepciones sobre el potencial
pedagógico de IA, necesidades formativas e institucionales para su
implementación, y, expectativas relacionadas con procesos de capacitación
docente orientado al fortalecimiento de la planificación curricular. <=
/o:p>
El
desarrollo de la investigación se estructuró en tres etapas metodológicas,
orientado a fundamentar, diagnosticar y desarrollar una propuesta de
capacitación en IA aplicada a la planificación curricular docente.
Fase
1 pretest (diagnóstico) : permitió identificar el nivel de
conocimientos, competencias digitales, percepciones y uso de herramientas d=
e IA
del profesorado de educación general básica, mediante la aplicación de
cuestionario estructurado de 12 preguntas valorado por escala Likert
implementado a docentes, y, entrevista semiestructurada dirigido a las
autoridades. Se obtuvo información de carácter cuantitativo y cualitativo
respecto las necesidades formativas, experiencias y expectativas relacionad=
as a
la integración de IA en la práctica del profesorado y su planificación
curricular.
Fase
2 (Propuesta) : en base a los resultados obtenidos e=
n la
primera fase, se diseñó una propuesta de capacitación orientada al
fortalecimiento de competencias digitales del docente para la incorporación=
de
herramientas de IA en la planificación curricular, validándose por expertos
para determinar su aplicabilidad, pertinencia y coherencia. La propuesta co=
nsistió
en la formación de un manual de capacitación a través de la herramienta
Genially, compuesto por contenidos teóricos, orientaciones metodológicas,
ejercicios prácticos y recursos digitales destinado a fomentar el uso
pedagógico, contextualizado y ético de IA en educación general básica.
Fase
3 postest (análisis pretest y postest) : tras realizada la
propuesta de capacitación, se implementó el cuestionario utilizado en el
pretest con el propósito de identificar los cambios producidos en los
conocimientos, competencias digitales y percepciones docentes respecto al u=
so
de la inteligencia artificial en la planificación curricular. Los resultados
obtenidos fueron comparados con los datos iniciales para determinar las mej=
oras
alcanzadas tras la intervención, empleando la prueba estadística de rangos =
con
signo de Wilcoxon para muestras relacionadas, con la finalidad de comprobar=
la
existencia de diferencias estadísticamente significativas entre los resulta=
dos
del pretest y postest.
En
constancia de la confiabilidad del instrumento se empleó el coeficiente Alf=
a de
Cronbach. Toro et al. (2022) indican que este coeficiente permite medir la
confiabilidad de un instrumento a partir de la varianza de los ítems
individuales y la suma de los ítems de cada participante, por lo tanto,
permitió evaluar la homogeneidad y consistencia interna de los ítems que
integran el cuestionario, verificando el grado en que estos miden de manera
coherente las dimensiones establecidas.
La
validez de contenido del cuestionario y entrevista semiestructurada fue
establecida mediante juicio de expertos, evaluando aspectos relacionados con
coherencia, claridad, pertinencia y relevancia de ítems respecto los objeti=
vos
y variables del estudio, mostrando garantía que los instrumentos midan
correctamente el fenómeno de la investigación.
La
dimensión ética del estudio garantió el respecto del principio de
voluntariedad, confidencialidad y anonimato de participantes, solicitando el
consentimiento con exposición previa respecto los objetivos, procedimiento y
tratamiento de la información, sosteniendo el uso responsable y ético de los
datos obtenidos.
3.&n=
bsp;
Resultados
A
continuación, se presentan los resultados obtenidos a partir del diagnóstico
realizado a la población docente en el área de estudio, considerando las di=
mensiones
tecnológicas, capacitación, uso de IA, y planificación curricular. Los
resultados permiten identificar los conocimientos, competencias y percepcio=
nes
del profesorado respecto a la incorporación de herramientas de IA en la
planificación curricular, como los cambios evidenciados posterior la
implementación de la propuesta de capacitación.
=
3.1. Fase
1 pretest (diagnóstico)
Previo
al análisis de los datos recopilados, se procedió a evaluar la consistencia
interna del cuestionario aplicado a los 35 docentes de educación general bá=
sica,
donde el instrumento estuvo conformado por 12 ítems distribuidos en cuatro
dimensiones: tecnológica, capacitación, uso de inteligencia artificial y
planificación curricular, diseñados para identificar las percepciones,
conocimientos y prácticas docentes relacionadas con la integración de la
inteligencia artificial en la planificación curricular.
La fiabilidad del instrumento se determi=
nó
mediante el coeficiente Alfa de Cronbach, permitiendo valorar el grado de
consistencia interna existente entre los ítems que conforman una escala de
medición, estableciendo un coeficiente de α =3D 0,91 que evidencia una
consistencia óptima entre los elementos que integran el cuestionario, siendo
que, valores superiores a 0,90 se consideran una fiabilidad excelente. Acor=
de a
lo expuesto, se establece que el instrumento presenta una solidez metodológ=
ica
necesaria para garantizar la confiabilidad de los datos obtenidos, consisti=
endo
que los resultados pretest y postest sean considerados válidos, coherentes y
reproducibles para el desarrollo investigativo.
La
Tabla 1
<=
/span> SEQ Tabla=
\*
ARABIC 1
Distribución
porcentual de las respuestas por ítem
Dimensiones
Preguntas
1
2
3
4
5
Interpretación
Tecnológica
1.Me
considero competente en el uso de herramientas digitales en mi labor doce=
nte.
14,3
%
5,7
%
17,1
%
37,1
%
25,7
%
El
62,8 % de los docentes manifiesta una percepción favorable respecto a sus=
competencias
digitales, aunque persisten brechas en un grupo minoritario de participan=
tes.
2.Poseo
conocimientos básicos sobre inteligencia artificial aplicada a la educaci=
ón.
8,6
%
11,4
%
17,1
%
51,4
%
11,4
%
El
62,8 % de los docentes considera poseer conocimientos básicos sobre
inteligencia artificial aplicada a la educación, sin embargo, aún se
identifican vacíos conceptuales que requieren fortalecimiento.
3.
El uso de herramientas tecnológicas me permite ahorrar tiempo en la
planificación docente.
14,3
%
5,7
%
5,7
%
31,4
%
42,9
%
El
74,3 % de los participantes reconoce que las herramientas tecnológicas
contribuyen al ahorro de tiempo en los procesos de planificación docente,
favoreciendo una gestión más eficiente de las actividades académicas.
Tabla 1
Distribución
porcentual de las respuestas por ítem (continuación)
Dimensiones
Preguntas
1
2
3
4
5
Interpretación
Capacitación
4.
He recibido capacitación sobre el uso de inteligencia artificial aplicada=
a
la planificación curricular
28,6
%
25,7
%
11,4
%
20,0
%
14,3
%
El
54,3 % indica no haber recibido formación suficiente en esta temática,
evidenciando la necesidad de fortalecer los procesos de capacitación doce=
nte
para favorecer una integración efectiva de la inteligencia artificial en =
la
planificación curricular.
5.
Estoy dispuesto(a) a participar en programas de capacitación sobre
inteligencia artificial.
17,1
%
0
%
8,6
%
17,1
%
57,1
%
El
74,2 % de los participantes expresa disposición para participar en progra=
mas
de capacitación sobre inteligencia artificial, reflejando interés por
fortalecer sus competencias profesionales en esta área. =
6.
La falta de capacitación limita el uso de inteligencia artificial en mi
práctica docente.
11,4
%
8,6
%
11,4
%
28,6
%
40
%
El
68,6 % de los docentes considera que la insuficiente capacitación constit=
uye
una limitante para integrar la inteligencia artificial en su práctica
educativa,
Uso de inteligencia artificial =
7.
Comprendo los aspectos éticos del uso de la inteligencia artificial en
educación.
17,1
%
17,1
%
8,6
%
31,4
%
25,7
%
El
57,1 % de los participantes manifiesta comprender los aspectos éticos
relacionados con el uso de la inteligencia artificial en educación
Tabla 1
Distribución
porcentual de las respuestas por ítem (continuación)
Dimensiones
Preguntas
1
2
3
4
5
Interpretación
8.
Utilizo herramientas digitales o inteligencia artificial para elaborar
planificaciones curriculares.
17,1
%
11,4
%
11,4
%
31,4
%
28,6
%
El
60 % de los docentes afirma utilizar herramientas digitales o de intelige=
ncia
artificial para elaborar planificaciones curriculares. <=
/p>
9.
La inteligencia artificial facilita la organización de contenidos en la
planificación curricular.
14,3
%
2,9
%
11,4
%
28,6
%
42,9
%
El
71,5 % de los docentes considera que la inteligencia artificial facilita =
la
organización y estructuración de contenidos en la planificación curricula=
r.
Planificación curricular
10.
Mis planificaciones curriculares integran recursos digitales de manera
efectiva.
11,4
%
5,7
%
8,6
%
57,1
%
17,1
%
El
74,2 % de los participantes considera que integra recursos digitales de
manera efectiva en sus planificaciones curriculares.
11.
Adapto mis planificaciones curriculares a las necesidades de los estudian=
tes.
11,4
%
5,7
%
8,6
%
28,6
%
45,7
%
El
74,3 % de los docentes manifiesta adaptar sus planificaciones curriculare=
s a
las necesidades de los estudiantes, reflejando una orientación hacia
prácticas pedagógicas centradas en el aprendizaje y la diversidad
estudiantil.
12.
La capacitación en inteligencia artificial mejoraría la calidad de mis
planificaciones.
11,4
%
2,9
%
5,7
%
34,3
%
45,7
%
El
80 % de los participantes considera que la capacitación en inteligencia
artificial es necesaria, destacando la importancia de la
Tabla
1
Distribución
porcentual de las respuestas por ítem (continuación)
Dimensiones
Preguntas
1
2
3
4
5
Interpretación
formación
especializada para fortalecer la práctica docente.
Nota: Escala de Likert: 1 =3D Totalmente en
desacuerdo; 2 =3D En desacuerdo; 3 =3D Ni de acuerdo ni en desacuerdo; 4 =
=3D De
acuerdo; 5 =3D Totalmente de acuerdo.
Los
resultados diagnóstico evidencian que el cuerpo docente posee competencias
digitales básicas, con percepción favorable al uso de recursos tecnológicos=
y
con conocimiento inicial respecto a la IA implementada en educación,
reconociendo su potencial en la optimización de actividades relacionadas a =
la
planificación curricular, sin embargo, los resultados muestran la existenci=
a de
limitaciones de dominio y aplicación de herramientas IA específicas,
justificando la necesidad de fortalecer estas competencias a través de proc=
esos
formativos especializados.
Los
apartados de capacitación muestran que un porcentaje significativo de
participantes no ha recibido formación suficiente respecto el uso pedagógic=
o de
IA, correspondiendo su voluntad y disposición a participar en programas de
capacitación, evidenciando la pertinencia de la propuesta de disponer recur=
sos
orientados al desarrollo de competencias relacionadas al uso educación de I=
A,
establecida mediante el diseño de un manual interactivo. <=
/p>
Respecto
la planificación curricular, los participantes reconocen que la incorporaci=
ón
de IA puede contribuir en la mejora de procesos de planificación, elaboraci=
ón
de actividades y organización de contenidos, por tanto, se considera que la
capacitación especializada favorece prácticas pedagógicas innovadoras e
incrementa la calidad de planificación curricular, contextualizando y centr=
ando
las necesidades del estudiantado.
=
3.2. Entrevista
a los docentes
La
información obtenida mediante entrevista semiestructurada como se muestra e=
n la
Tabla 2
<=
/span> SEQ Tabla=
\*
ARABIC 2
Entrevista dirig=
ida
a docentes y resultados obtenidos
Pregunta
Resultados obtenidos
Interpretación
¿Cómo
describiría su experiencia en el uso de herramientas digitales en su prác=
tica
docente?
66,7
% media; 33,3 % alta
Predomina
un nivel intermedio de experiencia tecnológica entre los docentes.
Tabla 2
Entrevista dirig=
ida
a docentes y resultados obtenidos (continuación)
Pregunta
Resultados obtenidos
Interpretación
¿Qué
tipo de tecnologías utiliza actualmente para planificar sus clases?<=
/o:p>
100
% procesadores de texto; 66,7 % presentaciones; 33,3 % plataformas
educativas; 33,3 % herramientas de IA
Los
docentes utilizan principalmente herramientas básicas y tradicionales para
planificar.
¿Qué
entiende por inteligencia artificial en el contexto educativo?
66,7
% sistemas avanzados que personalizan el aprendizaje; 33,3 % herramientas
tecnológicas de apoyo
Existe
una comprensión general positiva sobre el potencial educativo de la IA.
¿Ha
utilizado alguna herramienta de IA? ¿Cuál y con qué finalidad?
Uso
ocasional de ChatGPT y asistentes digitales para apoyo en actividades y p=
lanificación
El
uso de IA aún es inicial y orientado principalmente al apoyo pedagógico
básico.
¿Cómo
realiza actualmente la planificación curricular?
Predomina
la planificación digital mediante procesadores de texto y recursos
tecnológicos
La
planificación curricular muestra una transición hacia entornos digitales.=
¿Qué
dificultades enfrenta al momento de planificar?
Organización
del tiempo, estructuración de contenidos y adaptación a necesidades
estudiantiles
Las
principales barreras se relacionan con la carga laboral y la diversidad
educativa.
¿Considera
que la planificación podría mejorar con el uso de tecnología?
66,7
% sí; 33,3 % tal vez
La
mayoría percibe que la tecnología puede fortalecer el proceso de
planificación curricular.
¿Cómo
cree que la inteligencia artificial puede transformar la educación básica=
?
66,7
% mejorará algunos procesos; 33,3 % transformará significativamente la
educación
Los
docentes reconocen el potencial transformador de la IA en el ámbito
educativo.
¿Qué
expectativas tiene respecto a la capacitación en inteligencia artificial?=
66,7
% altas; 33,3 % medias
Existe
una valoración positiva hacia procesos de formación en IA.
¿Estaría
dispuesto(a) a incorporar herramientas de inteligencia artificial en su
práctica docente?
100
% sí
Se
evidencia una alta disposición para integrar herramientas de IA en la
práctica pedagógica.
El
análisis de las entrevistas evidencia que los docentes poseen una experienc=
ia
tecnológica situada principalmente en un nivel intermedio, caracterizada po=
r el
uso frecuente de herramientas digitales básicas dentro de su práctica
pedagógica. Se presenta un predominio de utilización en procesadores de tex=
to y
presentaciones digitales en la planificación curricular, siendo que,
plataformas educativas y herramientas de IA son empleadas de forma limitada=
y
esporádica, existiendo familiaridad con recursos tecnológicos, pero, sin un
desarrollo sistemático en la práctica docente.
Respecto
con el conocimiento sobre IA, se evidencian que los participantes tienen una
percepción favorable sobre sus capacidades educativas, siendo asociado con
sistemas de personalización y apoyo al aprendizaje, siendo que, los docentes
manifiestan haber utilizado herramientas de IA centradas en la organización=
de
contenidos y otras actividades. Sin embargo, su utilización es reportado co=
mo
básico con orientación a tareas específicas, denotando el requerimiento de
mayor formación para lograr una integración pedagógica superior y
contextualiza.
Las
entrevistas revelan que, la planificación curricular representa un desafío =
para
el profesorado consistente a factores como: estructuración de contenidos,
adaptación a las necesidades del estudiantado y organización del tiempo, cu=
ya intervención
tecnológica de IA permitirá contribuir positivamente en el fortalecimiento =
de
atención a la diversidad educativa, optimización del proceso de planificaci=
ón y
mejora de organización de recursos. En este sentido, se identificó una acti=
tud
favorable respecto la formación del docente en IA, cuya disposición para
incorporar herramientas de IA en las prácticas educativas refleja una apert=
ura
hacia la innovación y reconocimiento de la importancia de fortalecer las
competencias digitales en el contexto educativo contemporáneo.
=
3.3. Fase
2 (diseño de la propuesta)
Identificadas
las necesidades formativas del profesorado en la fase diagnóstica, se
estructuró y diseño la propuesta de capacitación, establecida como un manual
interactivo sobre IA aplicado a la planificación curricular mediante la
utilización de la plataforma Genially, como se muestra en la Figura =
1
Figura
1
Manual sobre el uso de inteligencia artificial
Link
de la propuesta: https://view.genially.com/6a2a156e9e1d49f69b1624f7
Con
el propósito de garantizar la calidad pedagógica, tecnológica y metodológic=
a de
la propuesta antes de su implementación, el manual de capacitación fue some=
tido
a un proceso de validación mediante juicio de tres expertos, seleccionados =
por
su experiencia profesional en el ámbito educativo y en el uso de Tecnolo=
gías
de la Información y Comunicación (TIC).
En
la valoración se utilizó la escala tipo Likert, presentando cinco niveles
establecidos en: totalmente en desacuerdo (1), en desacuerdo (2), ni de acu=
erdo
ni en desacuerdo (3), de acuerdo (4) y totalmente de acuerdo (5), conservan=
do
los criterios de evaluación implementados en la investigación, aplicado a
categorías de:
· =
Pertinencia:
permitió valorar la relación de contenidos acorde las necesidades de formac=
ión
docente.
· =
Coherencia:
otorgó la relación lógica respecto contenidos, actividades y propósito del
manual.
· =
Claridad:
propició establecer la comprensión y organización de la información present=
ada.
· =
Aplicabilidad:
estableció la posibilidad de utilizar el manual en el contexto de los docen=
tes
en EGB.
De
esta manera, la validación estuvo dirigida específicamente al diseño de un
manual de capacitación sobre IA para la elaboración de la planificación
curricular en profesores de EGB.
Los
resultados presentaron una valoración positiva, con puntuaciones entre de
acuerdo y totalmente de acuerdo, cuyo promedio general es de 4,58/5. Las
categorías como pertinencia muestran un valor de 4,67/5, estableciendo
correspondencia respecto el contenido de la propuesta y los requerimientos
formativos del profesorado, además, la coherencia presentó también un valor=
de
4,67/5, mostrando una relación adecuada acerca de actividades, contenidos y
propósito de la propuesta, en tanto, la claridad reconoce 4,33/5, valoración
favorable en la comprensión y organización de información presentada, y, la
categoría de aplicabilidad alcanzó 4,67/5, denotando condiciones favorables=
de
utilización en el contexto de EGB. Estos resultados respaldan la propuesta =
como
recurso de apoyo para fortalecer el uso pedagógico de IA en la planificación
curricular de los docentes. <=
/o:p>
=
3.4. Fase
3 postest (análisis pretest y postest)
La
información postest obtenida muestran una mejoría generalizada en las cuatro
dimensiones evaluadas, estableciendo que la propuesta contribuyó positivame=
nte
al fortalecimiento de competencias en los participantes. Como se evidencia =
en
la Tabla 3
Distribución
porcentual de las respuestas por ítem
Dimensión
Pregunta
1
2
3
4
5
Interpretación
Tecnológica
1.
Me considero competente en el uso de herramientas digitales en mi labor
docente.
0
%
0
%
5,7
%
28,6
%
65,7
%
El
94,3
%
de los docentes manifiesta una percepción favorable respecto a sus
competencias digitales, evidenciando una mejora significativa después de =
la
capacitación.
2.
Poseo conocimientos básicos sobre inteligencia artificial aplicada a la
educación.
0
%
0
%
2,9
%
25,7
%
71,4
%
97,1%
de participantes reconoció contar con conocimientos básicos respecto IA
implementada a la educación, evidenciando un progreso significativo en la
comprensión del tema.
3.
Uso de herramientas tecnológicas me permite ahorrar tiempo en la
planificación docente.
0
%
0
%
2,9
%
22,8
%
74,3
%
El
97,1
%
de los docentes reconoce que las herramientas tecnológicas optimizan el
tiempo destinado a la planificación docente.
Capacitación
4.
He recibido capacitación sobre el uso de inteligencia artificial aplicada=
a
la planificación curricular.
0
%
0
%
2,9
%
20,0
%
77,1
%
El
97,1
%
de los docentes señala haber recibido capacitación relacionada con
inteligencia artificial, evidenciando el efecto directo de la propuesta
aplicada.
5.
Estoy dispuesto(a) a participar en programas de capacitación sobre
inteligencia artificial.
0
%
0
%
0
%
11,4
%
88,6
%
El
100
%
de los participantes expresa disposición favorable para continuar
participando en programas de capacitación sobre inteligencia artificial.<=
o:p>
6.
La falta de capacitación limita el uso de inteligencia artificial en mi
práctica docente.
0
%
0
%
5,7
%
22,9
%
71,4
%
El
94,3
%
de los docentes reconoce que la capacitación es un factor clave para inte=
grar
adecuadamente la inteligencia artificial en la práctica educativa.
Tabla
3
Distribución
porcentual de las respuestas por ítem (continuación)
Dimensión
Pregunta
1
2
3
4
5
Interpretación
Uso
de inteligencia artificial
7.
Comprendo los aspectos éticos del uso de la inteligencia artificial en
educación.
0
%
0
%
2,9
%
25,7
%
71,4
%
El
97,1
%
de los docentes manifiesta comprender los aspectos éticos del uso de la
inteligencia artificial, mostrando una mejora significativa respecto al
diagnóstico inicial.
8.
Utilizo herramientas de inteligencia artificial para elaborar planificaci=
ones
curriculares.
0
%
0
%
2,9
%
22,8
%
74,3
%
El
97,1
%
de los participantes afirma utilizar herramientas de inteligencia artific=
ial
en la elaboración de planificaciones curriculares.
9.
La inteligencia artificial facilita la organización de contenidos en la
planificación curricular.
0
%
0
%
2,9
%
20,0
%
77,1
%
El
97,1
%
de los docentes considera que la inteligencia artificial facilita la
organización y estructuración de contenidos curriculares.
Planificación
curricular
10.
Mis planificaciones curriculares integran recursos digitales de manera
efectiva.
0
%
0
%
2,9
%
25,7
%
71,4
%
El
97,1
%
de los docentes considera que integra recursos digitales de manera efecti=
va
en sus planificaciones curriculares.
11.
Adapto mis planificaciones curriculares a las necesidades de los estudian=
tes.
0
%
0
%
2,9
%
22,8
%
74,3
%
El
97,1
%
de los participantes manifiesta adaptar sus planificaciones curriculares a
las necesidades de los estudiantes.
12.
La capacitación en inteligencia artificial mejoraría la calidad de mis
planificaciones.
0
%
0
%
0
%
14,3
%
85,7
%
El
100
%
de los docentes considera que la capacitación en inteligencia artificial
mejora la calidad de sus planificaciones curriculares. <=
/p>
Los hallazgos del postest presentan un
fortalecimiento significativo en conocimientos y competencias del docente en
relación con la utilización de IA en la planificación curricular, siendo qu=
e,
posteriormente la implementación de la propuesta, el 94,3% de participantes
manifestó ser competente en el uso de herramientas de IA aplicadas en
educación, en tanto, 97,1% reconoce contar con conocimientos básicos sobre =
IA
comprendiendo el potencial para fortalecer procesos pedagógicos. Además, 97=
,1%
considera que estas herramientas contribuyen en la optimización de tiempo e=
n la
planificación docente, evidenciando mayor confianza en la aplicación de
recursos tecnológicos para mejorar el trabajo académico. <=
/p>
Respecto
la capacitación, la información mostró una valoración favorable acerca de l=
os
procesos formativos desarrollados, siendo que, 97,1% de participantes afirma
haber fortalecido sus conocimientos a través de capacitaciones recibidas, y,
100% expresa su disposición de participar en programas futuros de formación=
sobre
IA. En este contexto, 94,3% reconoce que la capacitación constituye un fact=
or
fundamental para conseguir una integración efectiva sobre IA en la práctica
docente, por lo tanto, se evidencia mayor conciencia sobre las necesidades =
de
formación profesional.
Como
se muestra en la Tabla 4
Comparación
pretest-postest
Dimensión
Pretest
Postest
Diferencia
Tecnológica
66,6 %
96,2 %
+29,6 %
Capacitación
71,4 %
97,1 %
+25,7 %
Uso
de Inteligencia Artificial
62,9 %
97,1 %
+34,2 %
Planificación
Curricular
76,2 %
98,0 %
+21,8 %
Los
resultados comparativos entre el pretest y postest evidencian mejoras
significativas en todas las dimensiones evaluadas, considerando que el mayor
incremento se observa en la dimensión relacionada con el uso de la intelige=
ncia
artificial de 62,9 % a 97,1 %, representando una mejora de 34,2%, por tanto,
denota que la capacitación fortaleció los conocimientos y habilidades del
profesorado.
La
dimensión tecnológica registró un crecimiento del 29,6% (66,6%-96,2%),
consistiendo en la optimización en competencias digitales de docentes,
igualmente, la dimensión capacitación incremento 25,7% (71,4%-97,1%) mostra=
ndo
una valoración elevada en procesos formativos, y, disposición favorable
respecto el desarrollo profesional en IA.
Por
su parte se evidencia en la Tabla 5
Prueba de rangos=
con
signo de Wilcoxon
Comparación
Categoría
n
Rango
promedio
Suma
de rangos
Postest
- Pretest
Rangos
negativos
1
4,00
4,00
Rangos
positivos
32
16,77
520,00
Empates
2
-
-
=
Total
35
=
=
Los
resultados de la prueba de rangos con signo de Wilcoxon evidencian un marca=
do
predominio de los rangos positivos, donde de los 35 participantes evaluados=
, 32
obtuvieron puntuaciones superiores en el postest respecto al pretest, mient=
ras
que únicamente un participante registró una disminución en sus resultados y=
dos
mantuvieron puntuaciones similares en ambas mediciones, reflejando una
tendencia general de mejora continua posterior a la implementación de la
propuesta.
Por
el contrario, el valor de significancia bilateral obtenido (p=3D0,000) resu=
lto
inferior al valor establecido (α =3D 0,05), derivando en el rechazo de
hipótesis nula y aceptando la hipótesis alternativa, determinando la existe=
ncia
de discrepancias estadísticas significativas entre resultados pretest y
postest.
El
crecimiento observado en las dimensiones valoradas respalda los hallazgos
estadísticos, destacando el incremento de 34,2% respecto la utilización de =
IA
(62,9%-97,1%), 29,6% en competencias tecnológicas (66,6%-96,2%), 25,7% en
procesos de capacitación docente (71,4%-97,1%), y, 21,8% en planificación
curricular (76,2%-98%). Estos resultados demuestran que el manual de
capacitación basado en inteligencia artificial tuvo un efecto positivo y
estadísticamente significativo en el fortalecimiento de las competencias
docentes, favoreciendo una mayor integración de herramientas de inteligencia
artificial en la planificación curricular y contribuyendo a la mejora de los
procesos pedagógicos desarrollados por los participantes. =
4.&n=
bsp;
Discusión
Los resultados evidencian que los docentes=
de
EGB de la Unidad Educativa Aurelia Becerra presentan un nivel intermedio de
competencias digitales y conocimientos relacionados con la inteligencia
artificial, situación que coincide con lo señalado por Tan et al. (2025)
afirmando que docentes exhiben interés en la integración tecnológica de IA =
en
prácticas pedagógicas, sin embargo, persisten limitaciones de dominio técni=
co
en la formación profesional. En relación, Roshan et al. (2024) identificaron
que aunque docentes cuentan con información básica respecto la utilización =
de
herramientas de IA, un porcentaje menor cuentan con confianza en su
implementación, denotando la necesidad de fortalecimiento en capacitación c=
on
orientación al desarrollo de competencias tecnológicas.
La información obtenida acerca del uso de =
IA
en la planificación curricular expone una tendencia favorable hacia la
incorporación de estas herramientas en la optimización de contenidos, respe=
cto
su organización y reducción de períodos en tareas administrativas (Chernega=
et
al., 2025). Heng et al. (2026) sostienen que la IA propicia positivamente el
diseño de planificaciones, mejorando la automatización de procesos
transformándose en dinámicos y personalizados, cubriendo las necesidades
estudiantiles mediante la adaptación pedagógica.
La disposición y percepción positiva del
docente en relación con la capacitación en IA, coincide con lo establecido =
por Brandão
et al. (2024) argumentando que el desarrollo profesional docente representa=
un
factor fundamental en la adaptación de tecnologías dentro del ámbito educat=
ivo.
En este contexto, Lademann et al. (2025) consideraron que programas
estructurados para la formación en IA benefician la confianza, alfabetizaci=
ón
digital y aptitudes del docente respecto la integración tecnológica, por lo
tanto, la predisposición visualizada dentro de los participantes constituye=
un
hallazgo favorable en la implementación estratégica de IA en competencias
pedagógicas.
A su vez, las entrevistas realizadas
permitieron identificar que los participantes utilizan herramientas digital=
es
básicas, manteniendo una integración limitada de tecnologías nuevas en la
planificación curricular, siendo estos hallazgos coincidentes con Ravi et a=
l.
(2023) estableciendo que docentes presentan inicialmente una apropiación
tecnológica, empleando la IA como apoyo instrumental en cambio que una
herramienta pedagógica integral. Tadimalla & Maher (2024) resaltan que =
la
alfabetización en IA debe incorporar conocimientos técnicos, mediante la
incorporación de las dimensiones pedagógicas y éticas, permitiendo la
comprensión de estas tecnologías en el contexto educativo y social.
La información recopilada permite afirmar =
la
existencia de escenarios favorables en el diseño e implementación de recurs=
os
de formación y capacitación en IA hacia el profesorado de EGB, siendo que, =
la
disposición positiva, reconocimiento del potencial pedagógico de IA y
fortalecimiento formativo de los docentes es dependiente de factores como la
accesibilidad tecnológica, acompañamiento pedagógico y desarrollo profesion=
al
continuo, respecto a ello, la existencia de un manual de capacitación resul=
ta
pertinente para promover la implementación ética, contextualizada y pedagóg=
ica
de herramientas de IA en la planificación curricular docente. <=
/span>
5.
Conclusiones
· =
El
diagnóstico realizado al profesorado de EGB identificó la existencia de una
percepción favorable al uso de herramientas de IA, aunque con la persistenc=
ia
de limitaciones respecto conocimientos específicos de IA, y, su implementac=
ión
dentro de la planificación curricular. Los resultados del pretest evidencia=
ron
que únicamente el 62,9 % de los participantes utilizaba o reconocía la util=
idad
de la inteligencia artificial en los procesos de planificación, mientras qu=
e el
54,3 % manifestó no haber recibido formación suficiente en esta temática,
justificando la necesidad de implementar un recurso de capacitación
especializado que responda a las necesidades formativas identificadas.=
· =
La
aplicación de la propuesta de capacitación basada en inteligencia artificial
generó mejoras significativas en todas las dimensiones evaluadas, donde los
resultados del postest reflejaron incrementos importantes en las competenci=
as
tecnológicas (96,2 %), capacitación en inteligencia artificial (97,1 %), us=
o de
inteligencia artificial (97,1 %) y planificación curricular (98,0 %). Los
resultados del signo de Wilcoxon confirman la existencia de diferencias
significativas respecto el pretest y postest, determinando la efectividad d=
e la
intervención para fortalecer competencias del profesorado, y promover la
integración eficiencia de IA en los procesos educativos. <=
/p>
· =
El
manual de capacitación diseñado e implementado fortaleció las competencias
docentes entre la planificación curricular e IA, evidenciando resultados
favorables superiores al 97% entre las dimensiones analizadas, y, un 100% e=
n la
aceptación respecto la importancia de capacitación para la mejora de la cal=
idad
en planificaciones curriculares. Por lo tanto, el manual se categoriza como=
un
recurso pertinente, aplicable e innovador dentro del contexto educativo en =
EGB,
consecuente al fortalecimiento de prácticas pedagógicas contextualizadas,
eficientes y orientadas a la necesidad estudiantil.
6.&n=
bsp;
Conflicto de
intereses
Los
autores declaran que no existe conflicto de intereses en relación con el
artículo presentado.
7.
Derechos de autor (copyrigth)
Los
autores son los titulares de los derechos de autor (patrimoniales y/=
o de
explotación) de los contenidos de la revista (copyright ).
8.&n=
bsp;
Declaración de
contribución de los autores
Los autores declaran haber
participado de manera equitativa y sustancial en la realización de esta
investigación, bajo las responsabilidades según la Taxonomía
CRediT para describir
las contribuciones individuales de cada autor al trabajo.
Laura Josefina Vernaza Corozo y =
Rosa
Delfina Gómez Castro, realizaron la conceptualización de la
investigación, organización y ejecución del ensayo, recopilación y curación=
de
los datos, revisión del análisis estadístico, interpretación de los resulta=
dos,
elaboración del borrador original, preparación de tablas y figuras, revisión
crítica del contenido y aprobación de la versión final del manuscrito.=
Efraín Velastegui López & Giceya Maqueira Caraballo,
realizaron la supervisión académica y metodológica de la investigación, bri=
ndó
orientación durante el desarrollo del ensayo, revisó el análisis y la
interpretación de los resultados, efectuó la revisión crítica del manuscrit=
o,
realizó la corrección científica y académica y aprobó la versión final para=
su
publicación.
Divulgación de la
delegación a la IA generativa
Los
autores declaran que emplearon ChatGPT (OpenAI, GPT-5.5) como herramienta de
apoyo para reorganizar y reformular editorialmente el manuscrito original,
corregir el estilo, traducir el resumen al inglés y comprobar el cumplimien=
to
formal del formato de la revista. Los datos experimentales, el diseño, los
resultados estadísticos y las decisiones científicas proceden de la
investigación de los autores y no fueron generados ni modificados por la
herramienta. Los autores revisaron, contrastaron y aprobaron cada sección y
asumen la responsabilidad íntegra del contenido final. La herramienta no fi=
gura
como autor ni asume responsabilidad por los resultados.
Declaración
presentada por: Laura
Josefina Vernaza Corozo .
9.&n=
bsp;
Costos de financiamiento
La
presente investigación fue financiada en su totalidad con fondos propios de=
los
autores.
10.
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El artículo que se publica es de exclusiva
responsabilidad de los autores y no necesariamente reflejan el pensamiento =
de
la Revista Alfa Publicaciones. =
El artíc=
ulo
queda en propiedad de la revista y, por tanto, su publicación parcial y/o t=
otal
en otro medio tiene que ser autorizado por el director de la Revista Alfa Publicaciones. <=
/o:p>
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ISSN:
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Vol.
8 No. 4 pp. 115 – 139. octubre=
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diciembre 2026
Revista
multidisciplinar
Artículo
original
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Interculturalidad Científica
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