Inteligencia artificial generativa en la educación superior: Análisis empírico y modelado predictivo con Python
This study addresses the critical gap between the rapid and widespread adoption of generative artificial intelligence by students and the slow response capacity of higher education institutions. To inform the development of effective educational policies and strategies, quantitative research was...
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| Những tác giả chính: | , |
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| Định dạng: | Online |
| Ngôn ngữ: | Tiếng Tây Ban Nha |
| Được phát hành: |
Editorial Grupo AEA
2026
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://directory.doabooks.org/handle/20.500.12854/173365 |
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| Tóm tắt: | This study addresses the critical gap between the rapid and widespread adoption of generative
artificial intelligence by students and the slow response capacity of higher education institutions.
To inform the development of effective educational policies and strategies, quantitative research
was done using a validated survey given to a sample of 474 university students in Ecuador. Data
analysis combined descriptive and inferential statistics with machine learning techniques in
Python, including the K-Means clustering algorithm for profile segmentation and classification
models such as Random Forest for prediction. The results identify the dominant profile of the
“critical pragmatist,” a user who values the benefits of AI while being keenly aware of its risks,
and segment the population into three archetypes (Skeptic, Critical Pragmatist, and Techno-
Optimist). In addition, a model was developed that predicts long-term usage intent with 88.1%
accuracy. It is concluded that students express a clear and widespread demand for greater
institutional guidance, and it is recommended that universities move from a reactive stance to a
proactive strategy that encourages critical and ethical use. |
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