Students’ Perceptions and Teaching Challenges regarding Generative Artificial Intelligence in Higher Education

Authors

  • Carlos Villanueva Valadez Universidad Autónoma de Nuevo León
  • Sergio Guadalupe Torres Flores Universidad Autónoma de Nuevo León, México

DOI:

https://doi.org/10.29105/innoacad.v1i3.51

Keywords:

Artificial Intelligence, university education, digital skills

Abstract

Higher education is undergoing a substantial transformation due to the incorporation of generative artificial intelligence (GAI) tools, such as ChatGPT, which have automated academic and research tasks, enabling faster access to information. This evolution raises significant challenges regarding the redefinition of the teaching role, educational quality, and the ethical management of knowledge. The aim of this study is to analyze students’ perceptions of GAI use in higher education and to identify the main teaching challenges emerging from these perceptions. A quantitative, exploratory, and descriptive study was conducted through online questionnaires applied to 232 students from a public university in northeastern Mexico, within the context of a flipped classroom. The results indicate a positive evaluation of GAI for learning, while also highlighting concerns related to plagiarism, technological dependence, and the reliability of generated information. It is concluded that effective integration of GAI requires innovative pedagogical strategies, institutional regulation, and continuous faculty training.

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Author Biographies

Carlos Villanueva Valadez, Universidad Autónoma de Nuevo León

Doctorado en Comunicación por la Universidad Complutense de Madrid.

Sergio Guadalupe Torres Flores, Universidad Autónoma de Nuevo León, México

Doctorado en Tecnología Educativa por la Escuela de Ciencias de la Educación.

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Published

2025-09-30

How to Cite

Villanueva Valadez, C., & Torres Flores, S. G. (2025). Students’ Perceptions and Teaching Challenges regarding Generative Artificial Intelligence in Higher Education. INNOVACADEMIA, 1(3), 34–44. https://doi.org/10.29105/innoacad.v1i3.51