A Scientific Review of Generative Artificial Intelligence Models in Higher Education

Authors

DOI:

https://doi.org/10.63948/intraj.v2i1.600

Keywords:

Artificial intelligence, educational model, academic performance, scientific review

Abstract

The development of generative artificial intelligence models in students' autonomous learning has generated special interest in scientific research. This study proposes a literature review from a multivariate analysis to establish the conditions, capabilities, and prospects for introducing these models that introduce artificial intelligence as an assisted study tool in spatial learning environments. The implications of proper use of artificial intelligence and access modalities for virtual education are analyzed; therefore, variables that define impact and scientific relevance are generated. It discusses how artificial intelligence can improve or impair the capacity for design generation based on a sequentiality of processes within the algorithm. It is concluded that controlled models should be generated, specifying each algorithm indicator, thus improving students' spatial learning experience.

Author Biography

Bryan Colorado Pastor, Universidad César Vallejo

Born in Guayaquil, Ecuador. As an urban architect with a master's degree in Land Use Planning and Urbanism, I have worked on various research projects in the field of public space and urban accessibility for people with disabilities. I currently work for the University of Guayaquil on progressive community housing studies using flexible space architecture. Among my main research interests, my efforts focus on the sustainable development of the territory, human beings, and their habitat within the field of architecture.

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Published

2025-08-15

How to Cite

Colorado Pastor, B. (2025). A Scientific Review of Generative Artificial Intelligence Models in Higher Education. INTRA: Interdisciplinary Research and Analysis Journal, 2(1), 24–38. https://doi.org/10.63948/intraj.v2i1.600

Issue

Vol. 2 No. 1 (2025): Summer

Section

Articles

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