Institutional regulatory frameworks on artificial intelligence in higher education: A systematic review

Rufino Gabriel M.; Rueda Ñopo M.I.; Gabriel Rojas F.G.; Ponte Cordova S.; Salas Peña S.R.; Chavez Ortiz P.G. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.2041

Resumen

The objective of this research was to systematically analyze the regulatory frameworks governing the use of artificial intelligence in higher education. To this end, the scientific literature in the Scopus database was reviewed. Initially, 208 scientific articles were evaluated. The PICOC methodology and the Boolean operators "OR" and "AND" were used to determine the search equation and research questions. The PRISMA framework was also employed for the appropriate selection of articles based on inclusion and exclusion criteria. The first filter yielded 61 articles, and the second, 32 articles, which were included in the research. Regarding the results, three types of regulations were found: legal, institutional, and ethical. The study concluded that these three regulatory frameworks are complementary and that the regulation of AI is positive in the higher education academic sphere.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Tecnológica del Perú; Universidad Autónoma del Perú; Universidad César Vallejo; Universidad Privada del Norte