Effectiveness of Artificial Intelligence in University Teaching
DOI:
https://doi.org/10.33595/2226-1478.17.1600Keywords:
artificial intelligence, pedagogical effectiveness, university teaching, adaptive learning, higher educationAbstract
The purpose of this study was to analyze the effectiveness of AI (use directed toward specific pedagogical purposes and the teacher's perception of its impact on learning) for teaching process in a private university of Peru (2025). The current research utilized a cross-sectional quantitative correlational research design. The research was conducted at a private university in Lima. The sample consisted of 31 professors from the Industrial Engineering Department. Researchers developed two Likert-type instruments measuring professor use of AI in enhancing the education of students (α = .8319) and positively impacting the delivery of instruction (α = .9449). We obtained approval for both instruments as valid and reliable from individuals with expertise in the area. Each Likert-type instrument had a maximum possible total score of 5 (maximum provided by faculty for each instrument). The analysis of data revealed a statistically significant relationship between the use of AI in education and the delivery of instruction (ρ= .643, p < .0001). The results suggested an agreement among professors regarding the potential benefits associated with utilizing AI to personalize both student instruction and the way that faculty deliver instruction to students; however, the professors did not utilize AI in their instructional activities reported in this study. We concluded that institutional guidelines and capacitation in IA will help in the integration of IA with teaching process in a university.
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Akhmadieva, R. S., Kalmazova, N. A., Belova, T., Prokopyev, A., Molodozhnikova, N. M., y Spichak, V. Y. (2024). Research trends in the use of artificial intelligence in higher education. Frontiers in Education, 9, 1438715. https://doi.org/10.3389/feduc.2024.1438715
Bermúdez García, G. B., Coronel Coronel, R. A., Alvarado Vega, M. L., Espin Urrea, J. R., y Gómez Amaiquema, S. L. (2025). Estrategias de enseñanza basadas en inteligencia artificial y su impacto en el aprendizaje personalizado de los estudiantes. Ciencia Latina Revista Científica Multidisciplinar, 9(2), 6822-6836. https://doi.org/10.37811/cl_rcm.v9i2.17409
Bernilla Rodríguez, E. B. (2024). Docentes ante la inteligencia artificial en una universidad pública del norte del Perú. Educación, 33(64), 8-28. https://doi.org/10.18800/educacion.202401.M001
Celik, I. (2023). Towards intelligent-TPACK: An empirical study on teachers' professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468
Cornelio, O. M., Rodríguez, A., Solórzano Álava, W. L., Amén Mora, P. G., Santos Mera, L. M., y Pinargote Bravo, B. J. (2024). La inteligencia artificial: Desafíos para la educación. Editorial Internacional Alema. https://editorialalema.org/libros/index.php/alema/article/view/34
Chiu, T. K. F. (2025). Developing intelligent-TPACK (I-TPACK) framework from unpacking AI literacy and competency: Implementation strategies and future research direction. Interactive Learning Environments, 33(7), 4189-4192. https://doi.org/10.1080/10494820.2025.2545053
Du Plooy, E., Casteleijn, D. & Franzsen, D. (2024). Personalized adaptive learning in higher education: A scoping review of key characteristics and impact on academic performance and engagement. Heliyon, 10(21), e39630. https://doi.org/10.1016/j.heliyon.2024.e39630
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236. https://doi.org/10.2307/249689
Guerrero López, C. A., y Guerrero Medina, C. A. (2024). Determinantes del uso de la inteligencia artificial en la enseñanza universitaria: Un enfoque cualitativo. Tierra Nuestra, 18(2). https://doi.org/10.21704/rtn.v18i2.2183
Heredia-Pérez, G., Benavides-Galvez, J. B., Rojas-Campos, E. y Sanchez-Bustamante, E. (2025). Inteligencia artificial y pedagogía: retos para la educación superior en el Perú. Revista InveCom, 6(2), 1-6. https://doi.org/10.5281/zenodo.16997148
Hernández-Sampieri, R., y Mendoza, C. P. (2018). Metodología de la investigación: Las rutas cuantitativa, cualitativa y mixta. McGraw-Hill Education.
Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioral sciences (5.a ed.). Houghton Mifflin.
Kalniņa, D., Nīmante, D., y Baranova, S. (2024). Artificial intelligence for higher education: Benefits and challenges for pre-service teachers. Frontiers in Education, 9, 1501819. https://doi.org/10.3389/feduc.2024.1501819
Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., y Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators' perspectives. Computers and Education: Artificial Intelligence, 6, 100221. https://doi.org/10.1016/j.caeai.2024.100221
Ley N.° 29733. Ley de Protección de Datos Personales. (3 de julio de 2011). Diario Oficial El Peruano. https://www.gob.pe/institucion/congreso-de-la-republica/normas-legales/243470-29733
Martínez Rizo, F. (2021). Aprendizaje, enseñanza, conocimiento, tres acepciones del constructivismo. Implicaciones para la docencia. Perfiles Educativos, 43(174), 170-185. https://doi.org/10.22201/iisue.24486167e.2021.174.60208
Menacho, M. (2024). Inteligencia artificial y aprendizaje autónomo en estudiantes de educación superior, 2024 [Tesis de doctorado, Universidad Nacional Mayor de San Marcos]. https://cybertesis.unmsm.edu.pe/item/4df3b9ba-5510-4296-aae9-91428ed87981
Naseer, F., Khan, M. N., Tahir, M., Addas, A. & Aejaz, S. M. H. (2024). Integrating deep learning techniques for personalized learning pathways in higher education. Heliyon, 10(11), e32628. https://doi.org/10.1016/j.heliyon.2024.e32628
Ojeda, A. D., Solano-Barliza, A. D., Ortega Alvarez, D. y Boom Cárcamo, E. (2023). Análisis del impacto de la inteligencia artificial ChatGPT en los procesos de enseñanza y aprendizaje en la educación universitaria. Formación Universitaria, 16(6), 61-70. https://doi.org/10.4067/S0718-50062023000600061
Rao, G. T. & Suhasini, N. (2025). Integrating artificial intelligence in higher education to enhance teaching and learning. Computer Applications in Engineering Education, 33(2), e70085. https://doi.org/10.1002/cae.70085
Reina Marín, Y., Cruz Caro, O., Maicelo Rubio, Y. C., Alva Tuesta, J. N., Sánchez Bardales, E., Carrasco Rituay, A. M. & Chávez Santos, R. (2025). Artificial intelligence as a teaching tool in university education. Frontiers in Education, 10, 1578451. https://doi.org/10.3389/feduc.2025.1578451
Roco-Videla, Á., Flores, S. V., Olguin-Barraza, M. y Aguilera-Eguía, R. (2024). Consideraciones ante el uso de la prueba de Shapiro-Wilk cuando se trabaja con muestras pequeñas. Angiología, 76(1), 61-62. https://doi.org/10.20960/angiologia.00568
Salas-Pilco, S. Z. & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: A systematic review. International Journal of Educational Technology in Higher Education, 19(1), 21. https://doi.org/10.1186/s41239-022-00326-w
Strielkowski, W., Grebennikova, V., Lisovskiy, A., Rakhimova, G. & Vasileva, T. (2024). AI-driven adaptive learning for sustainable educational transformation. Sustainable Development, 33(2), 1921-1947. https://doi.org/10.1002/sd.3221
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press.
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Copyright (c) 2026 Janet Liliana Paz Campaña, Jose Antonio Arevalo Tuesta
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