Adoption of AI in universities in Central America and the Dominican Republic: knowledge, attitudes, and teaching challenges
DOI:
https://doi.org/10.31637/epsir-2026-2766Keywords:
Artificial intelligence, higher education, teacher training, attitudes, Central America, El Salvador, digital divide, technological adoptionAbstract
Introduction: The study analyzed the knowledge, use, and attitudes of university faculty regarding the adoption of artificial intelligence (AI), identifying key benefits and limitations across six countries in Central America and the Caribbean. Methodology: A mixed-methods approach with a non-experimental, cross-sectional design was implemented. The quantitative phase included a survey administered to 280 faculty members from 42 universities, while the qualitative phase incorporated interviews with five regional specialists to deepen the understanding of perceptions and challenges. Results: Findings show a high conceptual familiarity with AI, although only 41.1% reported applied mastery of its tools. Despite this gap, attitudes are overwhelmingly positive (97.9%), and educators acknowledge benefits such as increased access to information and enhanced productivity. However, structural limitations emerge: 85.4% consider that the lack of continuous training affects proper use, and a risk of inequality is identified due to economic and geographic factors. Discussions: Progress is recognized in the acceptance of AI, but gaps persist that hinder its full pedagogical integration. Conclusions: There are no substantial or significant differences in overall attitudes toward AI when comparing faculty across different countries of origin.
Downloads
References
Álvarez-Herrero, J. F. (2024). Opinión del alumnado universitario de educación sobre el uso de la IA en sus tareas académicas. European Public & Social Innovation Review, 9, 1-18. https://doi.org/10.31637/epsir-2024-534 DOI: https://doi.org/10.31637/epsir-2024-534
Baltazar Flores, R. A. (2025). Aplicaciones de la inteligencia artificial en la evaluación del aprendizaje en la educación superior beneficios, limitaciones y desafíos éticos. Innovarium International Journal, 3(2), 1-13. https://revinde.org/index.php/innovarium/article/view/60
Caicedo-Basurto, R. L., Camacho-Medina, B. M., Quinga-Villa, C. A., Fonseca-Lombeida, A. F. y López-Freire, S. A. (2024). Análisis y beneficios de la educación en la era de la inteligencia artificial. Journal of Economic and Social Science Research, 4(4), 291-302. https://doi.org/10.55813/gaea/jessr/v4/n4/148 DOI: https://doi.org/10.55813/gaea/jessr/v4/n4/148
Creswell, J. (2013). Introducción y Enfoque del Estudio. https://bit.ly/4cly2Yx
Delgado de Frutos, N., Campo-Carrasco, L., Sainz de la Maza, M. y Extabe-Urbieta, J. M. (2024). Aplicación de la Inteligencia Artificial (IA) en Educación: Los beneficios y limitaciones de la IA percibidos por el profesorado de educación primaria, educación secundaria y educación superior. Revista Electrónica Interuniversitaria de Formación del Profesorado, 27(1), 207-224. https://doi.org/10.6018/reifop.577211 DOI: https://doi.org/10.6018/reifop.577211
Hernández-Sampieri, R. y Mendoza Torres, C. P. (2018). Metodología de la Investigación. La rutas cualitativa, cuantitativa y mixta. Mc Graw Hill Education. https://virtual.cuautitlan.unam.mx/rudics/?p=2612
Jimbo Román, F. M. (2023). Efectos de la IA en la educación superior: Beneficios y limitaciones. Sapiens Discoveries International Journal, 1(1), 1-14. https://doi.org/10.71068/3f5hx495 DOI: https://doi.org/10.71068/3f5hx495
Morantes Carvajal, I. C. (2023). Inteligencia artificial (ia) en la investigación científica: Sistematización y reflexiones sobre experiencias educativas. Revista EDUCARE - UPEL-IPB - Segunda Nueva Etapa 2.0, 27(3), 112-137. https://doi.org/10.46498/reduipb.v27i3.2050 DOI: https://doi.org/10.46498/reduipb.v27i3.2050
Otero-Agreda, O. E. (2024). Desafíos éticos, beneficios y competencias clave para implementar la inteligencia artificial en la educación superior. Código Científico Revista De Investigación, 5(2), 1287-1313. https://revistacodigocientifico.itslosandes.net/index.php/1/article/view/628 DOI: https://doi.org/10.55813/gaea/ccri/v5/n1/463
Peñafiel-Jurado, R., Márquez-Márquez, N. y Guamán-Villa, I. (2024). Inteligencia artificial en la educación: Revisión sistemática de perspectivas, beneficios y desafíos en la práctica docente. South American Research Journal, 4(2), 5-15. https://doi.org/10.5281/zenodo.14507789
Sanz Manzanedo, M. (2025). La IA en la enseñanza de idiomas: chatbots y formación del profesorado. European Public & Social Innovation Review, 10, 1-13. https://doi.org/10.31637/epsir-2025-513 DOI: https://doi.org/10.31637/epsir-2025-513
Torres, M. S. C., Quinche, E. J. F., Aguiar, A. E. N., Peralta, D. J. C., Hidalgo, L. E. C. y Moreno, J. S. E. (2025). Evaluación automatizada mediante inteligencia artificial: beneficios y limitaciones. South Florida Journal of Development, 6(8), e5725. https://doi.org/10.46932/sfjdv6n8-042 DOI: https://doi.org/10.46932/sfjdv6n8-042
VanderLinde, G. y Mera Cury, T. (2024). El uso de inteligencia artificial y sus desafíos para la evaluación académica: una revisión de la literatura. Cuaderno De Pedagogía Universitaria, 21(41), 126-137. https://doi.org/10.29197/cpu.v21i41.564 DOI: https://doi.org/10.29197/cpu.v21i41.564
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Armando Briñis Zambrano, David Alberto Quintana Pérez, Herberth Alberto Santos Guzmán

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Non Commercial, No Derivatives Attribution 4.0. International (CC BY-NC-ND 4.0.), that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
