University Education Versus Artificial Intelligence Methodological Challenges And Approaches For Evidence-Based Teaching

Yojaime Ibeth Polo Abello1, Jhonattan Alexis Pontón Ibarra2, Ramón Alexis Álvarez Bayona3, María Carolina Araujo Arzuaga4, Angélica Patricia Gamez Quintero5 and Luis Carlos Noriega Borja6

1,2,3,4,5,6Universidad Popular del Cesar, Colombia
1Email: yojaimepolo@unicesar.edu.co, 2Email: jalexisponton@unicesar.edu.co, 3Email: raalvarez@unicesar.edu.co, 4Email: mariaaraujo@unicesar.edu.co, 5Email: angelicagamez@unicesar.edu.co and 6Email: lcnoriega@unicesar.edu.co

Received: 16th Dec, 2025; Revised: 8th Feb 2026; Accepted: 12th Feb, 2026; Available Online: 28th Feb, 2026

SUMMARY

The objective of this article is to carry out a critical review of the methodological frameworks applied in university education in relation to artificial intelligence. It seeks to integrate empirical evidence that addresses educational effectiveness, as well as ethical and equity aspects, in order to guide teaching practices. The methodology used includes an analysis of previous studies and the evaluation of practical cases that incorporate AI in the educational field. The results obtained highlight the need to adapt pedagogical strategies to face both the challenges and opportunities presented by artificial intelligence in higher education.

Keywords: Higher education, methodologies, approaches, artificial intelligence, teaching.

How to cite this article: Polo Abello YI, Pontón Ibarra JA, Álvarez Bayona RA, Araujo Arzuaga MC, Gamez Quintero AP, Noriega Borja LC, University Education Versus Artificial Intelligence: Methodological Challenges And Approaches For Evidence-Based Teaching. Int J Drug Deliv Technol. 2026;16(5s): 65-71. DOI: 10.25258/ijddt.16.5s.9