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

Autores/as

Guillermo Romaní Pillpe Universidad César Vallejo https://orcid.org/0000-0001-6417-9845
Keila Soledad Macedo Inca Universidad Nacional San Luis Gonzaga https://orcid.org/0000-0003-1457-370X
Celso 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

Palabras clave:

Competence, teaching, education, technology, university

Resumen

The overall objective was to describe the use of artificial intelligence in university teaching, based on the skills, perception, and technological integration of university teachers. To this end, a quantitative paradigm was used, with descriptive field research, a non-experimental cross-sectional design, and a population represented by 72 university teachers with a finite sample, consisting of those who voluntarily agreed to participate in the research. The results were presented in a table that analyzed frequency and percentage, showing that most university teachers recognize the potential of artificial intelligence in teaching, using it moderately and with a critical attitude. However, limitations in training, technical support, and autonomy in its pedagogical implementation were still identified.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

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