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Evaluación cuantitati= va y cualitativa del impacto de la inteligencia artificial en la satisfacción, eficacia, gestión del tiempo y reducción del estrés laboral en la jornada laboral docente ecuatoriana presencialmente o fuera del plantel =

Quantitative and qualitative evaluation of the impact of artificial intelligence on satisfaction, efficiency, time management, and reduction of work-related stress in the on-site and off-site workday of ecuadorian teachers

1

Nancy Orlheni Nacimba Rivera

https://orcid.org/0009-0007-7623-2421

 

 

Docente en Unidad Educativa Aloasi, Aloasi-Ecuad= or

nancy.nacimba@educacion.gob.ec =

2

Gladys Mercedes Trávez Osorio<= /span>

https://orcid.org/0009-0007-9382-2853

 

 

Docente en Unidad Educativa Juan José Flores, Sigchos-Ecuador

gladys.travez@educacion.gob.e c  

3

Alex Santiago Moreno Corrales<= /span>

 

https://orcid.org/0009-0002-2284-3052

 

 

Docente en Unidad Educativa Jean Piaget, Latacun= ga-Ecuador

asmoreno354@gmail.com 

4

Braulio Antonio Jiménez Zambrano                        https://orcid.org/0009-0003-3266-8398

Docente en Unidad Educativa Digna Maria Beatriz Cerda Neto, Pujil-Ecuador

braulioantonio95@gmail.com

 

 

 

 <= /p>

Artículo de Investigación Científica y Tecnológica

Enviado: 11/04/2024

Revisado: 12/05/2024

Aceptado: 10/06/2024

Publicado:05/07/2024

DOI: https://doi.org/10.33262/= exploradordigital.v8i3.3082 =                              

=  

 

<= o:p> 

Cítese:

 

&nb= sp;

Nacimba Rivera, N. O., Trávez Osorio, G. M., Moreno Corrales, A. S., & Jiménez Zambrano, B. A. (2024). Evaluación cuantitativa y cualitativa del impacto= de la inteligencia artificial en la satisfacción, eficacia, gestión del tiem= po y reducción del estrés laboral en la jornada laboral docente ecuatoriana presencialmente o fuera del plantel . Explorador Digital, 8(3), 101-122. = https://doi.org/10.33262/exploradordigital.v8i3.3= 082

 

 

3Deditorial1.png<= !--[if gte vml 1]>

 <= /b>

 

EXPLORADOR DIGITAL, e= s una Revista electrónica, Trimestral, que se publicará en sop= orte electrónico tiene como misión contribuir a la   formació= n de profesionales competentes con visión humanística y crítica que sean capac= es de exponer sus resultados investigativos y científicos en la misma medida= que se promueva mediante su intervención cambios positivos en la sociedad.&nb= sp;https://ex= ploradordigital.org

La revista es editada por la Editorial Ciencia Digital (Editorial de prestigio registrada en la Cámara Ecuatoriana de Libro con No de Afiliaci= ón 663) www.celibr= o.org.ec

 

 

 

 <= /b>

Esta revista está protegida bajo una licenc= ia Creative Commons en la 4.0 International. Copia de la licencia: http://creativecommons.org/licenses/by-nc-nd/4.0/.

 

Palabras claves: docencia, jornada laboral, presencial, fue= ra del plantel, inteligencia artificial, ANOVA.

&nb= sp;

&nb= sp;

Resumen

= Introducción: Este estudio revela el impacto= de la inteligencia artificial (IA) en cada una de las actividades de la jorn= ada laboral docente presencialmente o fuera del plantel en función de mejora = la satisfacción, eficiencia y tiempo, calidad de trabajo y reduce el estrés laboral en docentes. Revelando resultados favorables para la asistencia de las IAs en comparación a la forma habitual de hacer dicha jornada laboral. Este estudio destaca la relevancia de la IA en la educación, alineándose = con la legislación educativa ecuatoriana. Metodología: Es un estudio utiliza encuestas y análisis estadísticos para evaluar la efectividad de métodos tradicionales y asistidos por la IA en cada una de las actividade= s de la jornada laboral docente presencialmente o fuera del plantel en Ecuador= . Se usaron análisis con ANOVA y Tukey, aná= lisis estadístico basado en los porcentajes y análisis cualitativo en función de las respuestas obtenidas en el cuestionario. Las plataformas de AI educativas MagicSchool AI y Megaprofe fueron fundamentales en este anális= is. Desarrollo: La jornada laboral docente en Ecuador regulada por la LOEI se divide en actividades dentro y fuera del plantel. Este estudio analiza cuantitativa= y cualitativamente cada actividad de la segunda sección. Se utilizó un enfo= que ANOVA y Tukey para comparar métodos tradicionales y asistidos por IA, revelando mejoras en nivel se satisfacción, eficiencia, calidad del traba= jo y reducción de estrés con IA. La muestra incluye 20 docentes de diversas regiones e instituciones educativas del Ecuador, asegurando una representación objetiva de su realidad laboral. Resultados y análisis<= /b>: La asistencia de las AIs educativas MagicSchool A= I y Megaprofe fue estadísticamente significativa para cada una de las activid= ades de la jornada laboral docente presencialmente o fuera del plante en térmi= nos de, satisfacción, eficiencia, calidad del trabajo y cualitativamente desd= e la perspectiva docente hay reducción de estrés usando las IAs. Conclusion= es: La asistencia de las AIs educativas mejora significativamente la satisfacción, eficiencia y calidad del trabajo docente, de la jornada lab= oral fuera del plantel. Además, cualitativamente, los docentes perciben una notable reducción del estrés al utilizar estas herramientas. <= /span>

&nb= sp;

 

Keywords: teaching, workday, on-site, off-site, artificial intelligence<= /b>

 

Abstract

Introduc= tion: This s= tudy reveals the impact of artificial intelligence (AI) on each activity of the teaching workday, both in-person and remotely, in terms of improving satisfaction, efficiency, time management, work quality, and reducing teachers' work-related stress. The results show favorable outcomes for AI assistance compared to traditional methods. This study highlights the significance of AI in education, aligning with Ecuadorian educational legislation. Methodology: This study uses surveys and statistical analyses to evaluate the effectiveness of traditional and AI-assisted met= hods for each activity in the teaching workday, both in-person and remotely, in Ecuador. ANOVA and Tukey tests were used, along with statistical analysis based on percentages and qualitative analysis of the questionnaire respon= ses. The educational AI platforms MagicSchool AI and Megaprofe were fundamenta= l to this analysis. Development: The teaching workday in Ecuador, regul= ated by the LOEI, is divided into activities inside and outside the school. Th= is study quantitatively and qualitatively analyzes each activity in the seco= nd section. An ANOVA and Tukey approach was used to compare traditional and AI-assisted methods, revealing improvements in satisfaction, efficiency, = work quality, and stress reduction with AI. The sample includes 20 teachers fr= om various regions and educational institutions in Ecuador, ensuring an objective representation of their work reality. Results and Analysis: The assistance of educational AIs, MagicSchool AI and Megaprofe, was statistically significant for each activity in the teaching workday, both in-person and remotely, in terms of satisfaction, efficiency, work qualit= y, and qualitatively from the teachers' perspective, indicating a reduction = in stress using AIs. Conclusions: The assistance of educational AIs significantly improves the satisfaction, efficiency, and work quality of teachers' workdays outside the school. Additionally, qualitatively, teach= ers perceive a notable reduction in stress when using these tools.=

 

 

 

Introducción

En el contexto educativo contemporáneo alrededor del mundo, la integración de la inteligencia artificial (IA) se e= stá posicionando como una herramienta transformadora que promete mejorar el tra= bajo de los docentes en su jornada laboral. El presente estudio se centra en analizar el impacto cuantitativo y cualitativo de las herramientas de las I= As exclusivas de educación, en la jornada laboral docente presencialmente o fu= era del plantel. La investigación abarca un espectro de actividades reguladas p= or el Ministerio de Educación de Ecuador que incluyen activid= ades como actualización pedagógica, preparación de clases, material didáctico y ambientes de aprendizaje, revisión y calificación, elaboración de informes, preparación de actividades de recuperación de aprendizajes, investigación y publicaciones académicas, y participación estudiantil.

El objetivo principal de este estudio = es evaluar, mediante análisis estadísticos y cualitativos, las diferencias significativas en la realización de estas actividades con y sin la asistenc= ia de las IAs presentadas es este estudio. Se utilizó el análisis ANOVA y la prueba de comparación de métodos de Tukey para determinar la significancia estadística, respaldando los hallazgos con los correspondientes datos resultantes y diagramas de análisis de los mismo. Adicionalmente, se recopi= ló información cualitativa para comprender el impacto de la IA en la reducción= del estrés laboral docente y la percepción de calidad del trabajo realizado.

Los resultados preliminares indican qu= e la integración de IA en las actividades educativas no solo ahorra tiempo, sino= que también mejora la calidad percibida del trabajo y reduce significativamente= el estrés laboral de los docentes. Estos hallazgos se alinean con estudios pre= vios que sugieren que la IA puede desempeñar un papel crucial en la modernizació= n de los procesos educativos, permitiendo a los docentes concentrarse en tareas = más creativas y pedagógicamente valiosas.

La relevancia de este estudio radica e= n su capacidad para ofrecer una comprensión detallada y cuantificable de los beneficios de la IA en el entorno educativo ecuatoriano. Con un enfoque en = la mejora continua y la innovación educativa de acorde a lo estipulado en el articulo 2= 9, articulo 36 literal h, articulo 347 literal 8 de la Ley Orgánica de Educaci= ón Intercultural vigente a la fecha en Ecuador, los resultados obtenidos proporcionan una base sólida para la implementación más amplia de herramientas de IA en las instituciones educat= ivas, promoviendo una educación más eficaz, satisfactoria y menos estresante para= los docentes.

Este estudio contribuye al creciente cuerpo de literatura sobre la integración de la tecnología en la educación, ofreciendo evidencia empírica sobre las ventajas tangibles de utilizar IA e= n la práctica docente diaria. A medida que la tecnología continúa avanzando, es esencial explorar y comprender cómo estas herramientas pueden ser utilizadas para mejorar la calidad educativa y el bienestar de los educadores. Cabe recalcar que este estudio es consecuente a la obra “Evaluación de la asiste= ncia de inteligencia artificial en la labor docente en la Unidad Educativa Digna María Beatriz Cerda Neto, Pujilí-Ecuador” , en el cual se aborda la evaluac= ión de las IAs en la jordana laboral docente en la Institución educativa. =

Metodología

La metodología de este estudio es cuantitativo comparativo y cualitativo, combinando la aplicación de un formulario de evaluación y el análisis estadístico (Finol de Franco y Vera Solórzano, 2020), ya que este estudio se= basa en aplicación de encuestas y el análisis cualitativo y estadístico de los datos obtenidos, ya que se ha evalua= do la efectividad de dos métodos de ejecución de las actividades de la jornada laboral docente presencialmente o fuera del plantel, uno de forma tradicion= al y otro asistido con inteligencia artificial (AI), se diseñó un estudio que combinó análisis estadístico y encuestas a los participantes.

 El criterio de inclusión de la muestra, = en referencia a los docentes participantes se basó en la disposición y disponibilidad inmediata de participación en el estudio, ya que el presente análisis engloba a docentes de diferentes instituciones localizadas en dive= rsas regiones del Ecuador, dichos maestros que realizaron las actividades de la = jornada laboral docente presencialmente o fuera del plantel (Ministerio de Educación, 2024) de forma tradicion= al, posterior a ello realizaron lo mismo pero utilizaron un sistema asistido con AI. Posteriormente, se les realizó una encuesta a los docentes para evaluar= su experiencia en ambos métodos. La encuesta incluyó preguntas sobre la satisf= acción, eficacia y tiempo, calidad del trabajo y reducción de estrés laboral. Los resultados de la encuesta se analizaron utilizando estadísticas descriptiva= s y de inferencia, como la media, la desviación estándar y el análisis de varia= nza (ANOVA). Además, se utilizó un análisis de regresión lineal para identificar las variables que influyeron significativamente en la satisfacción y la productividad de los docentes para este tipo de jornada laboral docente.  

Método 1: Ejecución de actividades de la jornada laboral docente, presencialmente o fuera del plan= tel, asistida por inteligencia artificial.

 Según (Jiménez Zambrano et al., 2024) han demostrado que el uso de la Inteligencia Artificial en la labor docente en = la institución puede mejorar la eficiencia, satisfacción y productividad de los docentes al ejecutar tareas de esta área de la jornada laboral como registr= o de notas, planificación, reuniones, coordinación con otras áreas incluso supervisión y control. Además, la implementación de estas tecnologías ha mostrado potencial para reducir el burnout y mejorar la calidad de vida de = los docentes (Hashem et al., 2024).

Selección de Intelige= ncia artificial exclusiva para docentes

Debido a que (Magic School AI, 2024) es una plataforma de inteligencia artificial diseñada para asistir en la educa= ción pensada para asistir docentes alrededor del mundo, con el fin de la reducci= ón de su carga laboral para desenvolverse mejor con sus alumnos, centrarse más= en la enseñanza y el apoyo directo a los estudiantes y reducir el estrés labor= al (World Economic Forum, 2024).

Esta plataforma es ampliamente utiliza= da y apreciada por más de dos millones de educadores en todo el mundo, lo que sugiere una validación robusta de su eficacia​ en la asistencia a docentes (Magic School AI, 2024). <= /span>Además, ofrece una amplia gama de alrededor de 60 herramientas de IA que se aplicó = al cumplimiento de las actividades de la jornada laboral docente, presencialme= nte o fuera del plantel.

En el proyecto (Megaprofe, 2024), desarrollado por José Antonio Tamayo y Vicenç Yll Escot, se busca maximizar= el potencial de las tecnologías de inteligencia artificial (IA) en el entorno educativo, animando a los profesores y estudiantes a aprovechar plenamente estas herramientas en su proceso de aprendizaje. El objetivo es proporcionar recursos y herramientas que capaciten a los educadores y fomenten un entorno educativo enriquecedor y estimulante adaptado a las necesidades individuale= s de cada estudiante. Este proyecto cuenta con más de 13 herramientas de IA enfocadas al trabajo docente, blogs y multimedia, entre otros recursos y es= por lo que se la seleccionó para ser parte de este estudio. 

Mé= todo 2: Ejecución de las actividades de la jornada laboral docente presencialmen= te o fuera del plantel, de forma tradicional

El método tradicion= al de hacer las cosas se remonta años atrás y lamentablemente en zonas remotas= de difícil acceso a la fecha aún ocurre, donde mayormente es limitado el uso l= as TICs, fuera de la institución educativa, en especial en sitios remotos dond= e la presencia de energía eléctrica y o señal de Wify es fluctuante limita la eficacia, gestión del tiempo y satisfacción docente en dichas actividades, = se apoya mayormente en herramientas básicas como la interacción uno a uno o llamadas telefónicas, uso de ordenadores con los paquetes básicos de escrit= orio y similares. De modo que, este enfoque requiere una gestión cuidadosa del tiempo y depende en gran medida de las capacidades y herramientas inmediatas disponibles para docente.

Por otro lado, este estilo de hacer docencia, dependiendo del caso aun con buen acceso a las TICs podría genera= en la mayoría de los casos estrés laboral debido a= la naturaleza demandante de esta profesión (Cuchipe Reinoso et al., 2020), como el síndrome del Edificio Enfermo (SEE) el cual afecta mayormente a mujeres o dada dicha susceptibilidad del docente es pos= ible también contraer el síndrome de burnout (Trávez Osorio et al., 2024).

Formulario de evaluac= ión de las AIs versus el método tradicional en la ejecución de las actividades = de la jornada docente presencialmente o fuera del plantel

El presente cuestionario de evaluación está diseñado para evaluar los dos métodos de hacer las actividades, de la siguiente forma, se seleccionó el nivel de acuerdo con cada afirmación utilizando una escala del 1 al 5, donde 1 =3D Insatisfecho y 5 =3D Totalmente de Satisfecho, para cada una de las actividades que según (= Ministerio de Educación, 2024) están designada a realizarse presencialmente o fuera de= la institución educativa, en la siguiente tabla se detalla cómo se lo realizo.=

Tabla 1

Estructura del cuestionario de evaluación de las herramientas de las AIs MagicSchool y MEGAPRODE en las actividades de la Jornada laboral docente presencialmente o fuera del plantel versus el método tradicional de ejecución de estas

Sección =

Descripción 

Objetivo

1

       Antes de EMPESAR      

Paso 1:<= /span>

Tenga en cuenta sus actividades docentes, como lo muestra el gráfico de nombre "Jornada laboral docente"

Paso 2:<= /span>

Use las herramienta= s de la inteligencia artificia (IA) mostradas, en cada una de las actividades = del gráfico de nombre "Jornada laboral docente presencialmente o fu= era del plantel “

" Las IAs bien utilizadas realizan alrededor del 80% de trabajo, el restante 20% compete= al docente". Vicenç Yll Escot creador de MEGAPROFE.

·     &nbs= p;   Magic Tools - MagicSchool.ai

·     &nbs= p;   Home Área docente - MEGAPROFE

Paso 3:<= /span>

Evalué la IA con relación a como realiza su labor docente habitualmente sin asistencia de = la inteligencia artificial

Instruir a los doce= ntes participantes acerca de lo que deben hacer antes de proceder con la evaluación.

2

️ Después de hacer lo antes mencionado en el gráfico, evalué la Inteligenci= a en 👉 Jornada laboral docente PRESENCIALMENTE O FUERA DEL PLANTEL

Saber cuál de las dos opciones de plataformas de AI en educación es la mejor para Jornada laboral docente PRESENCIALMENTE O FUERA DEL PLANTEL

Tabla 1

Estructura del cuestionario de evaluación de las herramientas de las AIs MagicSchool y MEGAPRODE en las actividades de la Jornada laboral docente presencialmente o fuera del plantel versus el método tradicional de ejecución de estas (continuación)

Sección

Descripción

Objetivo

3

Evaluación de Inteligencia Artificial

Por favor, indique = su nivel de acuerdo con cada afirmación utilizando una escala del 1 al 5, do= nde 1 =3D Insatisfecho y 5 =3D Totalmente de Satisfecho

Se evalúa la asiste= ncia de las AIs en cada una de las actividades correspondientes a la jornada laboral docente PRESENCIALMENTE O FUERA DEL PLANTEL según lo estipul= ado por el (Ministerio de Educación, 2024) del Ecuador y regulado por la LOEI, en relacion a hacer la misma actividad sin asistenc= ia de las AIs.

4

Evaluación general de Inteligencia Artificial  

Evalué las IA; MEGAPROFE y Magic Too= ls - MagicSchool.ai de forma indistinta 

Evaluar integralmente la asistencia = de las AIs al docente de función de:   

·     &nbs= p;   Eficiencia y tiempo<= /span>

·     &nbs= p;   Calidad del trabajo<= /span>

·     &nbs= p;   Estrés laboral

Desarrollo 

Según (Ministerio de Educación, 2024) la jornada laboral docente consta de  diviciones importantes que son; En la intitucion educativa y la otra Presencialmente o fuera del plantel. Este estudio esta basado en las actividades que engloba la seguna seccion, como = se muestra en la figura siguiente. No obstante el estudio de (Jiménez Zambrano et al., 2024), tituladoEvaluación de la asistencia de inteligencia artificial en la labor docente en la Unidad Educativa Digna María Beatriz Cerda Neto, Pujilí-Ecuador” llevo acabo = el analisis de la primera divición, por ende, el presente analisis  es concecutivo al mensionado.

=  

=  

=  

= Figura 1

<= span style=3D'font-size:12.0pt;line-height:115%;font-family:"Times New Roman",se= rif'>Jornada laboral docente presencialmente o fuera del plantel

Fuente: (Ministerio de Educación, 2024)

El cumplimiento de la jornada laboral docente está regulado por= el Acuerdo Ministerial No. MINEDUC-MINEDUC-2023-00005-A (Ministerio de Educación, 2023), que establece que esta jornada debe ser de estricto cumplimiento para todos los docentes de las instituciones educativas fiscales del sistema ecuatoriano de educación, de = modo que la jornada laboral docente presencialmente o fuera del plantel, idealmente debe ser de 2 horas diarias durante los días laborables, dando un total de 10 ho= ras semanales, dichas actividades son:

·         Actualización pedagógica

·         Preparación de clases material didáctico y ambientes de aprendizaje

·         Revisión y calificación

·         Elaboración de informes

·         Preparación de actividades de recuperación de aprendizajes

·         Investigación y publicaciones académicas

·         Preparación estudiantil

La muestra analizada constan de 20 docentes de unid= ades educativas de Aloasi, Sigchos, Latacunga, El Tingo la Esperanza Pujilí, tod= as cuidades de Ecuador, con lo que, se analizo distintas realidades del trabajo docente presencialmente o fuerea de la institucion, acercandose de una forma mucho mas objetiva a la realidad docente en Ecuador.

Este estudio justifica su relevancia al debelar la importancia en cuanto a; eficiencia y tiempo, calidad del traba= jo, desafíos y soluciones, formación y capacitación proporcionadas por  la asistencia de las AIs al docente en c= ada una de las actividades que forman la jornada laboral docente presencialment= e o fuera del plantel versus en metodo tradicional de hacer las cosas, t= odo ello alineándose con el articulo 29, articulo 36 literal h, articulo 347 literal 8 de la LOEI del Ecuador (Asamblea Nacional del Ecuador, 2011) en los cuales se hace mencion a la buena calidad e= ducativa y participacion en tecnologías educativas del Sistema Nacional de Educación, de modo que, la implementación = de IA de acorde a la LOEI mejoraria la calidad educativa y entorno de trabajo docente, respaldando así la pertinencia de implantacion de innovaciones tecnológicas en contextos educativos ecuatorianos.

El análisis de varianza (ANOVA) de un factor es un método estadístico que permite evaluar las diferencias significativas en las medias de tres o más grupos, permitiendo identificar patrones y tendencias = en los datos. Para determinar si existen diferencias significativas entre el metodo 1 y metodo 2 de hacer las actividades de la jornada laboral docente presencialmente o fuera del plantel, se utilizará el enfoque estadís= tico ANOVA, según (Cortina y Nouri ,2000).

Para recopilar información sobre el uso de estos dos métodos, se diseñó un cuestionario que abarcaba la jornada laboral <= span style=3D'font-size:12.0pt;line-height:115%;font-family:"Times New Roman",se= rif'>presencialmente o fuera del plantel con asistencia de IA y la realización de actividad= es de manera tradicional. Posteriormente, se realizó un análisis ANOVA en Mini= tab 18 para determinar si existe una diferencia significativa con un 95 % de confianza entre la utilización de IA en tareas educativas y los métodos tra= dicionales. Se renombro las actividades con nombres de variables para ser colocados en = Minitab 18, lo= s cuales se presentan en la siguiente tabla.

Tabla = 2

Nombre de variables p= ara Minitab.18 en base a las actividades evaluadas

Actividades evaluadas

Nombre de variables para minitab.18

Actualización pedagógica con asistencia de inteligencia artificial

APIA

Actualización pedagógica de forma habitual

AP

Preparación de clases material didáctico y ambientes de aprendizaje con asistencia de inteligencia artificial

PMAAIA

Preparación de clases material didáctico y ambientes de aprendizaje de forma habitual=

PMAA

 

Tabla 2

Nombre de variables p= ara Minitab.18 en base a las actividades evaluadas (continuación)=

Actividades evaluadas

Nombre de variables para minitab.18

Revisión y calificación con asistencia de inteligencia artificial

RCIA

Revisión y calificación de forma habitual

RC

Elaboración de informes con asistencia de inteligencia artificial

EIIA

Elaboración de informes de forma habitual

EI

Preparación de actividades de recuperación de aprendizajes con asistencia de intelige= ncia artificial

PARAIA

Preparación de actividades de recuperación de aprendizajes de forma habitual<= /o:p>

PARA

Investigación y publicaciones académicas con asistencia de inteligencia artificial=

IPAIA

Investigación y publicaciones académicas de forma habitual

IPA

Participación estudiantil con asistencia de inteligencia artificial

PEIA

Participación estudiantil de forma habitual

PE

Los parámetros del análisis de ANOVA determinarán si existe una diferencia significativa entre las labores docentes presencialmente o fuera del plantel con asistencia de inteligencia artificial (AI) y de forma tradicional. Para esto, se requiere un valor promedio alto en el análisis de las medias, ya q= ue los docentes evaluaron el nivel de satisfacción según cada afirmación utilizando una escala del 1 al 5, donde 1 representa insatisfacción y 5 representa total satisfacción, el valor promedio alto es el más adecuado pa= ra este estudio.

Para evaluar la eficacia, el tiempo y la calidad del trabajo de manera general en las actividades de la jornada laboral docente, presencialmente o fuera del plan= tel, con el uso de inteligencia artificial (IA), se realizó un análisis estadíst= ico basado en los porcentajes de las respuestas obtenidas en el cuestionario. D= ado que las preguntas contaban con opciones cerradas de respuesta, este enfoque permitió una cuantificación objetiva de los resultados, sin requerir un análisis estadístico tan complejo como el análisis de varianza (ANOVA) utilizado para evaluar cada una de las actividades de la jornada laboral docente presencialmente de manera individual.

El análisis de reducción de estrés lab= oral se llevó a cabo mediante un enfoque cualitativo, basado en las respuestas de los docentes a una pregunta de respuesta abierta. Se les preguntó: "¿C= ree usted que el uso de IA reduce el estrés en la jornada laboral y mejoraría la calidad de vida laboral del docente?" Las respuestas de los docentes permitieron un análisis detallado y profundo de sus percepciones y experien= cias sobre el impacto del uso de IA en su estrés laboral y calidad de vida labor= al.

Finalmente, como limitación de este estudio, se encontró que, en la mayoría de las unidades educativas ubicadas= en zonas rurales del Ecuador, donde los servicios de internet, energía eléctri= ca o telefonía celular son intermitentes, impide el uso de las IAs en la jornada laboral docente presencialmente o fuera del plantel.

Resultados y análisis

Análisis cuantitativo en función de satisfacción en la realización de la jornada lab= oral docente presencialmente o fuera del plantel

Análisis ANOVA para cada una de las actividades la jornada laboral docente presencialmente o fuera del plantel,= en todos los casos se asumió varianzas iguales, con un 95% de confianza y nive= l de significancia de 0,05.

Actualización pedagógica

Para saber si el nivel de satisfacción de la asistencia de las AIs = en la ejecución de actualización pedagógica es la misma que dicha ejecución realizada de manera habit= ual, se realizo Análisis ANOVA unidireccional y análisis Tukey.

Tabla = 3

ANOVA de un solo fact= or: Actualización pedagógica con asistencia de= las IAs, comparada con el Actualización pedagógica de forma habitual

Hipótesis

Descripción

Hipó= tesis nula

Todas las medias son iguales

Hipó= tesis alterna

No t= odas las medias son iguales

Nive= l de significancia

^= 5; =3D 0,05

NOTA: Se presupuso igualdad de varianzas para el análisis.

 

 

 

 

Tabla = 4

Análisis de Varianza = para Actualización pedagógica con asistencia de las IAs, comparada con el Actualización pedagógica de forma habitual

Fuent= e

GL

SC Aj= ust.

MC Aj= ust.

Valor= F

Valor= p

Factor

1

8,100

8,1000

23,14

0,001

Error

8

2,800

0,3500

 

 

Total

9

10,900

 

 

 

 

De acuerdo con el Valor p reflejado en la tabla número 4 de 0,001 ex= iste estadísticamente una diferencia significativa entre lo que indica que se rechaza la hipótesis nula y se acepta la hipótesis alternativa; es decir co= n el 95% de confianza hay diferencia significativa entre la realización de actualizaciones pedagógicas con asistencia de las IAs, comparada con la ejecución de actualizaciones pedagógicas de forma habitual.

Preparación de clases, materiales didáctico y ambientes de aprendizaje

Para el análisis estadístico entre Preparación de clases, materiales didáctico y ambientes de aprendizaje con Inteligencia Artificial (PMAAIA), comparado mediante ANOVA, con la ejecución de preparación de clases, materiales didác= tico y ambientes de aprendizaje de forma habitual (PMAA), el resultado del análi= sis de varianza arroja un Valor P de 0,001 (tabla 4) lo cual resulta que hay una diferencia significativa con el 95% de confianza entre PMAAIA y PMAA. =

Además, los resultados de la comparación de Tukey con el 95% de confianza en la compara= ción entre la diferencia de las medias de PMAAIA y PMAA. Por otro lado, las gráf= icas de caja del análisis estadístico entre dichos métodos que la mediana de PMA= AIA es similar al de APIA, dando a entender que el nivel más alto de satisfacci= ón para los docentes es realizar la actividad asistida con las IAs; es decir PMAAIA= .

 

 

 

 

 

 

Figura = 2

Gráfica de caja para comparación de APIA; AP; PMAAIA y PMAA

Revisión y calificación

Según el análisis estadístico ANOVA, calculado con el 95% de confianza y según el Valor p de 0.001, si existe estadísticamente una diferencia significativa entre la realización de Revis= ión y Calificación asistido con herramientas de Inteligencia y la misma activid= ad sin ella, además esto se evidencia en el siguiente grafico de intervalos. 

Tabla = 5

Análisis de Varianza = para significativa entre la realización de Revisión y Calificación asistido con herramientas de Inteligencia y la misma actividad sin ella

Fuente

GL

SC Ajust.

MC Ajust.

Valor F

Valor p

Facto= r

3

16,13=

5,375= 0

7,77<= o:p>

0,001=

Error=

20

13,83=

0,691= 7

 = ;

 = ;

Total=

23

29,96=

 = ;

 = ;

 = ;

Elaboración de informes

En cuanto a la elaboración de informes= de acuerdo con el Valor p de 0,001(tabla 5) del análisis ANOVA de un solo fact= or, refleja que si hay diferencia significativa entre hacer la actividad asisti= da con inteligencia artificial y sin ella. Para ello se presentó la gráfica de intervalos para RCIA; RC; EIIA Y EI.

 

Figura 3

Gráfica de intervalos para RCIA; RC; EIIA Y EI

Esta gráfica resultante de la comparación de Tukey arroja los intervalos de confianza para la media con un 95 % de confianza, mediante estadística inferencial se obtuvo los intervalos de confianza para la media= de cada método, ya que en el cuestionario los docentes seleccionaron el nivel = de satisfacción de acuerdo con cada afirmación utilizando una escala del 1 al = 5, donde 1 =3D Insatisfecho y 5 =3D Totalmente de Satisfecho, se selecciono intervalos de confianza de más alto valor, correspondientes a EL= LA con 4,833y 4,333 para RCIA, respectivamente, dichos valores se muestran en = la siguiente tabla.

Tabla 6

Agrupar información utilizando el método de Tukey y una confianza de 95%=

Factor

N

Media

Agrupación<= /span>

EIIA<= o:p>

6

4,833=

A

 = ;

 = ;

RCIA<= o:p>

6

4,333=

A

B

 = ;

RC

6

3,167=

 = ;

B

C

EI

6

2,833=

 = ;

 = ;

C

Nota: Las medias que no comparten una letra son significativamente diferentes.

Preparación de actividades de recuperación de aprendizaje e Investigación y publicacion= es académicas con asistencia de inteligencia artificial

En estadística, un valor p de cero ind= ica una probabilidad prácticamente nula de obtener los resultados observados ba= jo la hipótesis nula, sugiriendo una fuerte evidencia en su contra, lo que imp= lica diferencias estadísticamente significativas entre realizar PARA e IPA con asistencia de inteligencia artificial y sin ella. En el contexto de tu estu= dio, un valor p de 0.001 ya muestra diferencias significativas entre la revisión= y calificación asistida con herramientas de inteligencia artificial y la misma actividad sin ellas. Un valor p de cero reforzaría aún más esta conclusión, indicando que los resultados observados no se deben al azar y hay una diferencia clara entre los métodos evaluados (Box et al., 2005) (Moore et a= l., 2005). Por otro, lado valor p de cero no son exactamente cero, sino extremadamente pequeños de modo que en este caso el software estadístico Minitab pudo redondear estos valores a cero que son menores que el límite de precisión del software (Minitab, 2024).

Tabla 7

Análisis de Varianza = para PARAIA; PARA; IPAIA e IPA

Fuente

GL

SC Ajust.

MC Ajust.

Valor F

Valor p

Facto= r

3

16,83= 3

5,611= 1

11,61=

0,000=

Error=

20

9,667=

0,483= 3

 = ;

 = ;

Total=

23

26,50= 0

 = ;

 = ;

 = ;

 

Tabla 8

 Agrupar información utilizando el método= de Tukey y una confianza de 95% PARAIA; PARA; IPAIA e IPA

Factor

N

Media

Agrupación<= /span>

IPAIA=

6

4,667=

A

 = ;

PARAI= A

6

4,500=

A

 = ;

IPA

6

3,000=

 = ;

B

PARA<= o:p>

6

2,833=

 = ;

B

Nota: Las medias que no comparten una letra son significativamente diferentes.

Estadísticamente según ANOVA, con el 9= 5% de confianza con la comparación de métodos Tukey la preparación de activida= des de recuperación de aprendizaje e Investigación y publicaciones académicas c= on asistencia de inteligencia artificial presento un nivel superior de satisfacción.

Participación estudiantil

Esta gráfica resultante de la comparac= ión de Tukey muestra los intervalos de confianza para la media con un 95% de confianza. Mediante estadística inferencial, se obtuvieron los intervalos de confianza para la media de cada método. Se seleccionaron los intervalos de confianza de mayor valor, correspondiendo a PEIA con 3.833. en esta sección= los valores Investigación y publicaciones académicas con asistencia de intelige= ncia artificial siguen siendo significativamente diferentes a IPA lo cual ratifi= ca la sección anterior.

Tabla 9

Comparación de IPAIA, IPA, PEIA y PE con el método de Tukey y una confianza de 95%<= span style=3D'font-size:14.0pt;mso-bidi-font-size:13.0pt;line-height:115%;font-f= amily: "Times New Roman",serif;mso-fareast-font-family:"Times New Roman";color:#00= 4D72; mso-font-kerning:0pt;mso-ligatures:none;mso-fareast-language:ES-EC'>

Factor

N

Media

Agrupación<= /span>

IPAIA=

6

4,667=

A

 = ;

PEIA<= o:p>

6

3,833=

A

B

IPA

6

3,000=

 = ;

B

PE

6

2,833=

 = ;

B

Nota: Las medias que no comparten una letra son significativamente diferentes.

De acuerdo con el Valor P de 0,003 (tabla 10) se rechaza la hipótesis nula y se acepta la hipótesis alternativa; es decir, de acuerdo con el análisis ANOVA estadísticamente si hay una diferencia significativa para los docentes al realizar la Participación estudiantil asistidos con las IAs que realizarlo sin ellas. Dichos valores = se muestran a continuación en la gráfica de caja.

Tabla 10

Análisis de Varianza = para IPAIA, IPA, PEIA y PE

Fuente

GL

SC Ajust.

MC Ajust.

Valor F

Valor p

Facto= r

3

12,83=

4,277= 8

6,58<= o:p>

0,003=

Error=

20

13,00=

0,650= 0

 = ;

 = ;

Total=

23

25,83=

 = ;

 = ;

 = ;

 

 

 

 

 

 

Figura 4

Gráfica de tablas de = para IPAIA, IPA, PEIA y PE

Análisis cuantitativo en función de eficacia y tiempo en la realización de la jornada laboral docente presencialmente o fuera del plantel

De los docentes que respondieron a la pregunta: "¿Cuánto tiempo estima que ahorra utilizando inteligencia artificial en comparación con el método tradicional para cada actividad?&qu= ot;, el 50% indicó que ahorra alrededor de una hora, el 33% señaló que ahorra dos horas, y el 18% manifestó que ahorra más de dos horas en la realización de estas actividades.

Análisis cuantitativo en función de Calidad del Trabajo en la realización de la jorn= ada laboral docente presencialmente o fuera del plantel

Según las respuestas de los docentes a= la pregunta: ¿Considera que la calidad del trabajo realizado es mejor con inteligencia artificial o con el método tradicional para cada actividad? (1= =3D Mucho peor, 5 =3D Igual, 10 =3D Mucho mejor)", el 50% afirmó que la ca= lidad del trabajo es mucho mejor, el 83% indicó que es igual, y el 16% expresó qu= e es mucho peor.

Análisis cualitativo

Análisis cualitativo en función de reducción de estrés laboral

Para los docentes que participaron en = este estudio, el uso de Inteligencia Artificial (IA) en la educación es una herramienta valiosa para las actividades de la jornada laboral docente, tan= to en el aula como fuera de ella. Los educadores manifiestan que el uso de la = IA reduce significativamente las actividades monótonas y repetitivas, permitie= ndo que los profesores se enfoquen en mejorar la educación y no en tareas admin= istrativas. Además, les permite dedicar más tiempo a la realización de actividades más enriquecedoras y estimulantes. Además, los docentes destacan que la IA les permite realizar actividades de forma más dinámica y diversa, lo que se ref= leja en una reducción significativa del estrés laboral e intelectual en la ejecu= ción de las acciones mencionadas. De hecho, el 100% de los educadores participan= tes manifiestan que redujeron su estrés laboral e intelectual.

Es importante recalcar que los participantes en este estudio tienen en cuenta que siempre debe ser revisad= o lo generado por la IA para evitar volverse dependientes y asegurar que los contenidos estén acordes con los objetivos educativos planificados.

Conclusiones

·         Se concluye que para las actividades de la jornada laboral docente presencialm= ente o fuera del plantel que son, actualización pedagógica; preparación de clases material didáctico y ambientes de aprendizaje; revisión y calificación; elaboración de informes; preparación = de actividades de recuperación de aprendizajes; investigación y publicaciones académicas y preparación estudiantil, estadisticamente hay diferencia significativa con el 95% de confianza entre usar las herramientas que proporsionan las IAs en comparacion a la ejecuacion de la mismas actividade= s de forma habitual. Se hallo que en todos los casos estadisticamente es mas satisfactorio usar las IAs.

·         El análisis cuantitativo de la eficacia y el tiempo en la realización la jornada laboral docente presencialmente o fuera= del plantel revela que la m= ayoría de los docentes que participaron en este estudio han experimentado un ahorro significativo en tiempo. El 50% de los docentes indicó ahorrar aproximadame= nte una hora, mientras que el 33% señaló ahorrar dos horas y el 18% manifestó ahorrar más de dos horas en comparación con el método tradicional.En cuanto= a la calidad del trabajo, los resultados son igualmente impresionantes. Según= las respuestas de los docentes, el 50% considera que la calidad del trabajo es mucho mejor con la inteligencia artificial, mientras que el 83% indica que = es igual. Solo el 16% expresó que la calidad del trabajo mala.

·         Del Análisis cualitativo en función de reducción de estrés laboral revela que el uso de la Inteligencia Artificial (IA) en la educación ha demostrado ser una herramie= nta valiosa para los docentes, reduciendo actividades monótonas y permitiendo q= ue se enfocen en mejorar la educación. Además, les permite dedicar más tiempo a actividades enriquecedoras y estimulantes, y realizarlas de forma más dinám= ica y diversa, lo que reduce significativamente el estrés laboral e intelectual= .

Conflicto de interese= s

No existe conflicto de intereses en relación con el artículo presentado

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El artículo que se publica es de exclusiva responsabilidad de los aut= ores y no necesariamente reflejan el pensamiento de la Revista Explorador Digital.

 

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