Artificial intelligence in university teaching: Skills, perception, and technological integration in university teachers

Guillermo Romaní Pillpe; Keila Soledad  Macedo Inca; Ceslo Gaspar Tapara; Carlos Alberto Hernández Acasiete; Eddy Gladys  Esplana Paitan

doi:10.47606/ACVEN/PH0347

Authors

Guillermo Romaní Pillpe Cesar Vallejo University https://orcid.org/0000-0001-6417-9845
Keila Soledad Macedo Inca Universidad Nacional San Luis Gonzaga https://orcid.org/0000-0003-1457-370X
Ceslo Gaspar Tapara Universidad Nacional de Huancavelica https://orcid.org/0009-0008-8455-492X
Carlos Alberto Hernández Acasiete Universidad Nacional de Huancavelica https://orcid.org/0009-0001-1734-7954
Eddy Gladys Esplana Paitan Universidad del Desarrollo Andino https://orcid.org/0009-0006-7936-9063

DOI:

https://doi.org/10.47606/ACVEN/PH0347

Keywords:

Competencia, docente, enseñanza, tecnología, universidad

Abstract

El objetivo general planteado fue describir el uso de la inteligencia artificial en la enseñanza universitaria, en función de las competencias, la percepción y la integración tecnológica en docentes universitarios. Para ello, utilizó el paradigma cuantitativo, modalidad investigación de campo nivel descriptivo, diseño no experimental-transversal, La población estuvo representada por 72 docentes universitarios con una muestra finita, integrada por quienes aceptaron ser parte de la investigación de forma voluntaria. Los resultados, permitieron presentarlos a través de una tabla que analizó la frecuencia y el porcentaje evidenciando así, que la mayoría de los docentes universitarios reconoce el potencial de la inteligencia artificial en la enseñanza, usándola moderadamente y con actitud crítica. Sin embargo, aún se identifican limitaciones en formación, apoyo técnico y autonomía en su implementación pedagógica.

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References

Alzakwani, M. H. H., Zabri, S. M., & Ali, R. R. (2025). Enhancing university teaching and learning through integration of artificial intelligence in information and communication technology. Edelweiss Applied Science and Technology, 9(1), 1345-1357. Scopus. https://doi.org/10.55214/25768484.v9i1.4647 DOI: https://doi.org/10.55214/25768484.v9i1.4647

Amare, E. M., Zegeye, R. T., Wondie, A. G., & Andargie, B. A. (2024). Surveying the Digital Competencies of Health Profession Educators at Ethiopian Higher Education Institutions. Ethiopian journal of health sciences, 34(4), 281-289. Scopus. https://doi.org/10.4314/ejhs.v34i4.4

Asad, M. M., Younas, S., Ali, S., Churi, P. P., & Nayyar, A. (2023). Integration of artificial intelligence in the modern classroom: Prospects for digitization in education. En AI-Assisted Special Education for Students With Exceptional Needs (pp. 110-136). Scopus. https://doi.org/10.4018/979-8-3693-0378-8.ch005 DOI: https://doi.org/10.4018/979-8-3693-0378-8.ch005

Bernal Torres, C. A. (2000). Metodología de la investigación para administración y economía. Biblioteca Hernán Malo González de la Universidad del Azuay; Biblioteca Hernán Malo González. https://biblioteca.uazuay.edu.ec/buscar/item/55770

Bhojak, N. P., Momin, M., Jani, D., & Mathur, A. (2025). Enhancing teachers job satisfaction through the artificial intelligence utilization. Journal of Applied Research in Higher Education. Scopus. https://doi.org/10.1108/JARHE-03-2024-0126 DOI: https://doi.org/10.1108/JARHE-03-2024-0126

Cabero-Almenara, J., Barroso-Osuna, J., Palacios-Rodríguez, A., & Llorente-Cejudo, C. (2020). Digital competency frames for university teachers: Evaluation through the expert competence coefficient. Revista Electronica Interuniversitaria de Formacion del Profesorado, 23(2), 1-18. Scopus. https://doi.org/10.6018/reifop.413601 DOI: https://doi.org/10.6018/reifop.413601

Castillo, C. E. C., & Herhuay, I. L. (2025). The Lack of Educational Policies for the Benefit of Technological Implementation in Pedagogy at a Peruvian Public University. Sociologia y Tecnociencia, 15(1), 138-153. Scopus. https://doi.org/10.24197/st.1.2025.138-153 DOI: https://doi.org/10.24197/st.1.2025.138-153

Castro, M., & Padilla, A. M. (2024). Innovation and Challenges of Artificial Intelligence in University Training in Communication. QUESTION, 3(79), e958. https://doi.org/10.24215/16696581e958 DOI: https://doi.org/10.24215/16696581e958

Chee, H., Ahn, S., & Lee, J. (2024). A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway. BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY. https://doi.org/10.1111/bjet.13556 DOI: https://doi.org/10.1111/bjet.13556

Chen, H.-L. S., Jou, H., Lin, S.-P., & Sianturi, I. A. J. (2024). Developing Teacher Performance Indicators for 21st Century Competency-Oriented Teaching and Learning: Implications From IB Philosophy and Practices. Bulletin of Educational Research, 70(4), 87-127. Scopus. https://doi.org/10.6910/BER.202412_70(4).0003

Elsakova, R. Z., & Markus, A. M. (2024). Professional Development of University Educators in Artificial Intelligence: Current State. Vysshee Obrazovanie v Rossii, 33(11), 73-94. Scopus. https://doi.org/10.31992/0869-3617-2024-33-11-73-94 DOI: https://doi.org/10.31992/0869-3617-2024-33-11-73-94

Fodor, D. (2023). What an Editor should do in the beginning of era of Artificial intelligence? MEDICAL ULTRASONOGRAPHY, 25(4), 373-374. https://doi.org/10.11152/mu-4317 DOI: https://doi.org/10.11152/mu-4317

Gazit, N., Ben -Gal, G., & Eliashar, R. (2023). Using Job Analysis for Identifying the Desired Competencies of 21st-Century Surgeons for Improving Trainees Selection. JOURNAL OF SURGICAL EDUCATION, 80(1), 81-92. https://doi.org/10.1016/j.jsurg.2022.08.015 DOI: https://doi.org/10.1016/j.jsurg.2022.08.015

Gómez-Rodríguez, V. G., Avello-Martínez, R., Gajderowicz, T., Álvarez, N. B. D., Jara, J. I. E., Hernández, N. B., Hevia, S. G., & Iturburu Salvador, D. D. (2024). Assessment of three strategies for teaching an AI literacy program, based on a neutrosophic 2-tuple linguistic model hybridized with the ARAS method. Neutrosophic Sets and Systems, 70, 378-388. Scopus. https://doi.org/10.5281/zenodo.13182404

Gupta, S., Dharamshi, R. R., & Kakde, V. (2024). An Impactful and Revolutionized Educational Ecosystem using Generative AI to Assist and Assess the Teaching and Learning benefits, Fostering the Post-Pandemic Requirements. 2nd International Conference on Emerging Trends in Information Technology and Engineering, ic-ETITE 2024. Scopus. https://doi.org/10.1109/ic-ETITE58242.2024.10493370 DOI: https://doi.org/10.1109/ic-ETITE58242.2024.10493370

Hinojosa, J. L. H. (2024). Could Private Education for the Poorest Help Close Educational Gaps and Achieve Social Mobility? The Case of Low-cost Universities in Peru. Economia y Politica, 11(1), 105-148. Scopus. https://doi.org/10.15691/07194714.2024.004 DOI: https://doi.org/10.15691/07194714.2024.004

Iraola-Real, I., Gonzales Choquehuanca, E., Villar-Mayuntupa, G., Alvarado-Rojas, F., & Del Rosario, H. (2022). Performance Evaluation of Teaching of the Professional School of Education of a Private University of Peru. Lecture Notes in Networks and Systems, 407 LNNS, 128-138. Scopus. https://doi.org/10.1007/978-3-030-96147-3_11 DOI: https://doi.org/10.1007/978-3-030-96147-3_11

Kallunki, V., Kinnunen, P., Pyörälä, E., Haarala-Muhonen, A., Katajavuori, N., & Myyry, L. (2024). Navigating the Evolving Landscape of Teaching and Learning: University Faculty and Staff Perceptions of the Artificial Intelligence-Altered Terrain. Education Sciences, 14(7). Scopus. https://doi.org/10.3390/educsci14070727 DOI: https://doi.org/10.3390/educsci14070727

Karmakar, S., & Das, T. (2024). Effect of artificial intelligence on education. En Optimization and Computing using

Intelligent Data-Driven Approaches for Decision-Making: Optimization Applications (pp. 198-211). Scopus. https://doi.org/10.1201/9781003536796-8 DOI: https://doi.org/10.1201/9781003536796-8

Madrid, C., Chimborazo, L., Morales-García, W. C., Quispe-Sanca, D., Huancahuire-Vega, S., Sánchez-Garcés, J., & Saintila, J. (2024). DIGITAL COMPETENCIES AND TRANSFORMATIONAL LEADERSHIP AS PREDICTORS OF JOB PERFORMANCE IN UNIVERSITY TEACHERS. Journal of Educators Online, 21(3). Scopus. https://doi.org/10.9743/JEO.2024.21.3.18 DOI: https://doi.org/10.9743/JEO.2024.21.3.18

Nirchi, S., Mangione, G. R. J., De Vincenzo, C., & Pettenati, M. C. (2024). EXPLORATORY SURVEY ON NEWLY RECRUITED TEACHERS’ PERCEPTIONS OF THE USE OF ARTIFICIAL INTELLIGENCE IN TEACHING: STRONG POINTS, OBSTACLES AND PERSPECTIVES. Journal of Educational, Cultural and Psychological Studies, 2024(30), 151-180. Scopus. https://doi.org/10.7358/ecps-2024-030-nirc DOI: https://doi.org/10.7358/ecps-2024-030-nirc

Ñañez-Silva, M., Quispe-Calderón, J., & Santos-Jiménez, O. (2023). Teacher management and its impact on job satisfaction in higher education: A case study in Peru. International Journal of Advanced and Applied Sciences, 10(8), 148-157. Scopus. https://doi.org/10.21833/ijaas.2023.08.017 DOI: https://doi.org/10.21833/ijaas.2023.08.017

Paitán, H. Ñ., Mejía, E. M., Ramírez, E. N., & Paucar, A. V. (2014). Metodología de la investigación cuantitativa—Cualitativa y redacción de la tesis. Ediciones de la U.

Ren, Y., Wenxin, J., & Lu, H. (2024). Analysis on the Application of Artificial Intelligence Technology in College Teaching. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 582 LNICST, 434-444. Scopus. https://doi.org/10.1007/978-3-031-63136-8_45 DOI: https://doi.org/10.1007/978-3-031-63136-8_45

Sharma, S. K., Dixit, R. J., Rai, D., & Mall, S. (2024). Artificial intelligence and machine learning in smart education. En Infrastructure Possibilities and Human-Centered Approaches With Industry 5.0 (pp. 86-106). Scopus. https://doi.org/10.4018/979-8-3693-0782-3.ch006 DOI: https://doi.org/10.4018/979-8-3693-0782-3.ch006

Tavares, W., Kinnear, B., Schumacher, D. J., & Forte, M. (2023). «Rater training» re-imagined for work-based assessment in medical education. ADVANCES IN HEALTH SCIENCES EDUCATION, 28(5), 1697-1709. https://doi.org/10.1007/s10459-023-10237-8 DOI: https://doi.org/10.1007/s10459-023-10237-8

Üzüm, B., Elçiçek, M., & Pesen, A. (2025). Development of Teachers’ Perception Scale Regarding Artificial Intelligence Use in Education: Validity and Reliability Study. International Journal of Human-Computer Interaction, 41(5), 2776-2787. Scopus. https://doi.org/10.1080/10447318.2024.2385518 DOI: https://doi.org/10.1080/10447318.2024.2385518

Vitanova, N. (2024). Artificial Intellect in the Education of the Future. PEDAGOGIKA-PEDAGOGY, 96(9), 1199-1212. https://doi.org/10.53656/ped2024-9.02 DOI: https://doi.org/10.53656/ped2024-9.02

Wang, Y. (2022). A conceptual framework of contemporary luxury consumption. INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING, 39(3), 788-803. https://doi.org/10.1016/j.ijresmar.2021.10.010 DOI: https://doi.org/10.1016/j.ijresmar.2021.10.010

Yatsenko, T., Slyzhuk, O., Hohol, N., Novykov, A., & Hrychanyk, N. (2024). Competence-Based Approach to Studying Contemporary Ukrainian Literature by Early Adolescents: Theory and Practice. CADERNOS EDUCACAO TECNOLOGIA E SOCIEDADE, 17, 1-16. https://doi.org/10.14571/brajets.v17.nse1.2024 DOI: https://doi.org/10.14571/brajets.v17.nse1.1-16

Zambrano, A. B., & Pérez, D. A. Q. (2024). Benefits and Limitations for Salvadoran University Teachers and Students on the Use of AI in Teaching-Learning Processes. European Public and Social Innovation Review, 9. Scopus. https://doi.org/10.31637/epsir-2024-368 DOI: https://doi.org/10.31637/epsir-2024-368