Bibliometric Analysis of Scientific Production on Artificial Intelligence Applied to Higher Education (2015–2025)
Abstract
Artificial intelligence applied to higher education has experienced significant growth in scientific
production over the last decade, driven by digital transformation processes and the incorporation of
intelligent technologies into academic environments. The objective of this research was to analyze
the bibliometric behavior of scientific production related to artificial intelligence and higher education
between 2015 and 2025. The methodology was developed under a quantitative bibliometric approach
using information indexed in Scopus and Web of Science databases. Indicators related to scientific productivity, temporal evolution, countries with the highest
production, most cited authors, thematic areas, and research trends were analyzed. The results showed
exponential publication growth from 2020 onward, with China, the United States, and the United
Kingdom standing out as the countries with the highest scientific production. Likewise, the main
research lines identified focused on machine learning, learning analytics, personalized education, and
artificial intelligence ethics. It is concluded that artificial intelligence applied to higher education
constitutes an emerging and expanding research field with significant opportunities for developing
new pedagogical and technological models.
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