Teachers and Artificial Intelligence: uses and training needs in Latin American higher education

Andresa Sartor-Harada; Oscar Ulloa-Guerra

doi:10.1590/1983-3652.2026.61543

Autores

Andresa Sartor-Harada Universidad Internacional de La Rioja, La Rioja, Spain https://orcid.org/0000-0003-2045-7502
Oscar Ulloa-Guerra Universidad Internacional de La Rioja, La Rioja, Spain https://orcid.org/0000-0002-9505-7768

DOI:

https://doi.org/10.1590/1983-3652.2026.61543

Palavras-chave:

Ensino superior, Inteligência Artificial, Ensino universitário, Formação de professores, América Latina

Resumo

Este estudo explora as perspectivas dos professores universitários latino-americanos sobre a integração pedagógica da inteligência artificial (IA), particularmente o ChatGPT, em contextos de ensino superior. Com base em uma abordagem de métodos mistos, os dados de 130 participantes foram coletados por meio de um instrumento de pesquisa validado e entrevistas semiestruturadas de acompanhamento. Os resultados revelam uma atitude geralmente positiva em relação à IA como ferramenta de apoio pedagógico, particularmente para automatizar tarefas rotineiras e gerar conteúdo educacional. No entanto, o estudo também identifica tensões críticas — incluindo insegurança epistêmica, preocupações éticas e treinamento pedagógico digital limitado — que impedem um uso mais profundo e reflexivo. Os participantes enfatizam a necessidade urgente de oportunidades de desenvolvimento profissional que promovam a alfabetização algorítmica crítica, e não apenas a proficiência na ferramenta. Esta pesquisa destaca a importância de situar a integração da IA em estruturas éticas, contextualizadas e socialmente responsivas na formação de professores. O estudo convoca esforços sistêmicos para repensar os programas de formação de professores para que capacitem os educadores a navegar e se envolver criticamente com a IA de maneiras que apoiem ambientes de aprendizagem equitativos e centrados no ser humano.

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Biografia do Autor

Andresa Sartor-Harada, Universidad Internacional de La Rioja, La Rioja, Spain

Doutora com qualificação máxima excelente cum laude, Pós-doutoranda em Educação, Mestra em Psicologia da Educação, Pedagoga. Trajetória docente de mais de 20 años, experiência em educação infantil, fundamental e universitária. Publicações e pesquisas relacionadas com as estratégias da aprendizagem, as competências docentes eo aprendizado reflexivo. Autora y coautora de libros e comunicações científicas no Brasil, Estados Unidos e Espanha. Participação como palestante em atividades internacionais em países como Argentina, Uruguai, Colômbia, Panamá, Brasil, Moçambique e Angola.

Referências

AKGUN, S.; GREENHOW, C. Artificial intelligence in education: addressing ethical challenges in K-12 settings. AI and Ethics, v. 2, n. 3, p. 431–440, 2022.

BARBU, C.; SBUGHEA, C. Artificial intelligence in education: global trends, clusters, and perspectives. Annals of the University Dunarea de Jos of Galati: Fascicle I, Economics & Applied Informatics, v. 30, n. 3, 2024.

BRAUN, Virginia; CLARKE, Victoria. Using thematic analysis in psychology. Qualitative Research in Psychology, v. 3, n. 2, p. 77–101, 2006.

BULATHWELA, S.; PÉREZ-ORTIZ, M.; HOLLOWAY, C.; CUKUROVA, M.; SHAWE-TAYLOR, J. Artificial intelligence alone will not democratise education: on educational inequality, techno-solutionism and inclusive tools. Sustainability, v. 16, n. 2, p. 781, 2024.

CABERO-ALMENARA, Julio; GUTIÉRREZ-CASTILLO, Juan José; BARROSO-OSUNA, Julio; RODRÍGUEZ-PALACIOS, Antonio. Digital teaching competence according to the DigCompEdu framework: comparative study in different Latin American universities. Journal of New Approaches in Educational Research, v. 12, n. 2, p. 276–291, 2023.

CHAIPIDECH, P.; SRISAWASDI, N.; KAJORNMÁNEE, T.; CHAIPAH, K. A personalized learning system-supported professional training model for teachers’ TPACK development. Computers and Education: Artificial Intelligence, v. 3, p. 100064, 2022.

CHIU, Thomas K. F.; SANUSI, Ibrahim T. Define, foster, and assess student and teacher AI literacy and competency for all: current status and future research direction. Computers and Education Open, v. 5, p. 100182, 2024. DOI: 10.1016/j.caeo.2024.100182.

COBO, Cristóbal. La innovación pendiente: reflexiones (y provocaciones) sobre educación, tecnología y conocimiento. Barcelona: Penguin Random House, 2016.

CRESWELL, John W.; PLANO CLARK, Vicki L. Designing and Conducting Mixed Methods Research. 3. ed. Thousand Oaks: Sage Publications, 2017.

DAVIS, Fred D. Technology acceptance model: TAM. In: AL-SUQRI, Mohamed N.; AL-AUFI, Ali S. (eds.). Information seeking behavior and technology adoption. Hershey: IGI Global, 1989. p. 205–219.

DILEK, M.; BARAN, E.; ALEMAN, E. AI literacy in teacher education: empowering educators through critical co-discovery. Journal of Teacher Education, v. 76, n. 3, p. 294–311, 2025.

EVANGELIDIS, V.; THEODOROPOULOU, H. G.; KATSOUROS, V.; KIOURT, C. AI-enabled art education: unleashing creative potential and exploring co-creation frontiers. In: PROCEEDINGS of the 16th International Conference on Computer Supported Education (CSEDU). Setúbal: SCITEPRESS, 2024. p. 294–301.

GALÁN-RODRÍGUEZ, N. M.; BOBADILLA-PÉREZ, M.; BARROS-GRELA, E. Actitudes y percepciones: el papel de la inteligencia artificial en la formación de los futuros profesores de lenguas extranjeras de secundaria. Texto Livre, v. 18, e51692, 2025.

HARADA, A. S. Innovación educativa: la revolución de la IA en la experiencia universitaria. In: INTELIGENCIA artificial y educación: innovación pedagógica para un aprendizaje transformador. Madrid: Dykinson, 2025. p. 285–300.

HOLMES, Wayne; BIALIK, Maya; FADEL, Charles. Artificial intelligence in education: promises and implications for teaching and learning. Boston: Center for Curriculum Redesign, 2019.

KANDLHOFER, Michaela; STEINBAUER, Gerald; HIRSCHMUGL-GAISCH, Sabine; HUBER, Petra. Artificial intelligence and computer science in education: from kindergarten to university. In: PROCEEDINGS of the IEEE Frontiers in Education Conference (FIE). Piscataway: IEEE, 2016. p. 1–9.

KARATAŞ, F.; ERIÇOK, B.; TANRIKULU, L. Reshaping curriculum adaptation in the age of artificial intelligence: mapping teachers’ AI-driven curriculum adaptation patterns. British Educational Research Journal, v. 51, n. 1, p. 154–180, 2025.

KNOX, Jeremy. Artificial intelligence and education in China. Learning, Media and Technology, v. 45, n. 3, p. 298–311, 2020.

KOEHLER, Matthew J.; MISHRA, Punya. What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education, v. 9, n. 1, p. 60–70, 2009.

LONG, D.; MAGERKO, Brian. What is AI literacy? Competencies and design considerations. In: PROCEEDINGS of the CHI Conference on Human Factors in Computing Systems. New York: ACM, 2020. p. 1–16.

LUCKIN, Rose; HOLMES, Wayne. Intelligence unleashed: an argument for AI in education. London: Pearson Education, 2016.

MAI, Gengchen; CUNDY, Chris; CHOI, Kyung; HU, Yao-Yi; LAO, Ni; ERMON, Stefano. Towards a foundation model for geospatial artificial intelligence (vision paper). In: PROCEEDINGS of the 30th International Conference on Advances in Geographic Information Systems. New York: ACM, 2022. p. 1–4.

MIAO, Fengchun; HOLMES, Wayne. Beyond disruption: technology enabled learning futures: 2020 edition of Mobile Learning Week, 12–14 October 2020. Paris, 2021.

NING, Y.; ZHANG, C.; XU, B.; ZHOU, Y.; WIJAYA, T. T. Teachers’ AI-TPACK: Exploring the relationship between knowledge elements. Sustainability, v. 16, n. 3, p. 978, 2024.

OECD. Harnessing the power of AI and emerging technologies. Paris, 2022. (OECD Digital Economy Papers, 3402).

ORELLANA, J. S.; CORDERO, C. A.; ESPINOZA, J. C. Validación del cuestionario para docentes: percepción sobre el uso de ChatGPT en la educación superior. Revista Andina de Educación, v. 8, n. 1, p. 000816, 2025.

PATTON, Michael Quinn; MCKEGG, Kate; WEHIPEIHANA, Nan (eds.). Developmental evaluation exemplars: principles in practice. New York: Guilford Publications, 2015.

PERROTTA, Carlo. Plug-and-play education: knowledge and learning in the age of platforms and artificial intelligence. London: Taylor & Francis, 2024.

REYES, C. E. G.; AVELLO-MARTÍNEZ, R. Alfabetización digital en la educación: revisión sistemática de la producción científica en Scopus. Revista de Educación a Distancia (RED), v. 21, n. 66, 2021.

RUSSELL, Stuart; NORVIG, Peter. Artificial intelligence: a modern approach. 3. ed. Upper Saddle River: Prentice Hall, 2010.

SCHIAVO, G.; BUSINARO, S.; ZANCANARO, M. Comprehension, apprehension, and acceptance: understanding the influence of literacy and anxiety on acceptance of artificial intelligence. Technology in Society, v. 77, p. 102537, 2024.

SELWYN, Neil. Should robots replace teachers? AI and the future of education. London: John Wiley & Sons, 2019.

SHAH, P. AI and the future of education: teaching in the age of artificial intelligence. London: John Wiley & Sons, 2023.

SHARMA, S.; SINGH, G. Adoption of artificial intelligence in higher education: an empirical study of the UTAUT model in Indian universities. International Journal of System Assurance Engineering and Management, p. 1–27, 2024.

SHULMAN, Lee S. Those Who Understand: Knowledge Growth in Teaching. Educational Researcher, Washington, DC, v. 15, n. 2, p. 4–14, 1986.

TEO, T.; NOYES, J. Explaining the intention to use technology among pre-service teachers: A multi-groupanalysis of the UTAUT model. Computers & Education, v. 72, p. 150–164, 2014.

UNESCO. Guidance for generative AI in education and research. Paris: UNESCO Publishing, 2023.

VENKATESH, Venkatesh; MORRIS, Michael G.; DAVIS, Gordon B.; DAVIS, Fred D. User acceptance of information technology: toward a unified view. MIS Quarterly, v. 27, n. 3, p. 425–478, 2003.

VENKATESH, Venkatesh; THONG, James Y.; CHAN, Frank K.; HU, Paul J. H.; BROWN, Susan A. Extending the two-stage information systems continuance model: incorporating UTAUT predictors and the role of context. Information Systems Journal, v. 21, n. 6, p. 527–555, 2011.

VENKATESH, Venkatesh; THONG, James Y. L.; XU, Xin. Consumer acceptance and use of information technology: extending the UTAUT model. MIS Quarterly, v. 36, n. 1, p. 157–178, 2012.

WILLIAMSON, Ben. The hidden architecture of higher education: building a big data infrastructure for the “smarter university”. International Journal of Educational Technology in Higher Education, v. 17, p. 44, 2020.

WILLIAMSON, Ben; BAYNE, Sian; SHAY, Suellen. The datafication of teaching in higher education: critical issues and perspectives. Teaching in Higher Education, v. 25, n. 4, p. 351–365, 2020.

WILLIAMSON, Ben; EYNON, Rebecca. Historical threads, missing links, and future directions in the study of education and technology. Learning, Media and Technology, v. 45, n. 3, p. 207–221, 2020.

XU, Wei; OUYANG, Fan. The application of AI technologies in STEM education: a systematic review from 2011 to 2021. International Journal of STEM Education, v. 9, n. 1, p. 59, 2022.

YIM, Irene H. Y.; WEGERIF, Rupert. Teachers’ perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: an exploratory study on AI literacy for young students. Future in Educational Research, v. 2, n. 4, p. 318–345, 2024.

YUE, Mengdi; JONG, Morris S. Y.; NG, Daniel T. K. Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, p. 1–32, 2024.

ZAWACKI-RICHTER, Olaf; MARÍN, Victoria I.; BOND, Melissa; GOUVERNEUR, Franziska. Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, v. 16, n. 1, p. 1–27, 2019.