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This study aims to measure the quality of distance university higher education in the Peruvian department of Junín, as well as to seek strategies of improvement. To meet this objective, a survey was carried out on students from the 4 universities located in this department, all with an institutional license. An intentional non-probabilistic sampling was used. The quality variable in university higher education is described in nine dimensions derived from the educational policies imposed by the National Superintendency of Higher University Education (SUNEDU in Spanish), which are: academic objectives, educational offer, infrastructure and equipment, research lines, qualified teacher, complementary services, job bank, transparency, and satisfaction. Among the results, it stands out that 59% of the students on average show satisfaction with the education received, which allows us to conclude that quality should be directed by a unit with its own name and established transversally in all administrative, academic, and academic procedures, investigative, social projection, and university extension. Transparency avoids any act of corruption, therefore it is important to associate it with the ethics of the authorities and workers of the university entity, strengthening timely communication with the student body. On the other hand, Kosko's Hidden Patterns Method was used to process a fuzzy cognitive map designed by education quality experts' opinions and in this way conclusions were reached about the strategies to follow for improving the quality of Peruvian non-face-to-face education in the department. [ABSTRACT FROM AUTHOR]

The use of Artificial Intelligence (AI) and the practice of scientific research in Higher Education centers in Peru is of vital importance for the scientific, economic, social, and educational development, among other aspects of the country. In the 21st century, the use of AI in daily life has increased in quantity and quality. In addition, the development of a country without the use of these technologies is inconceivable. But as in other contemporary aspects, AI and scientific research deepen the gap between developing countries with respect to developed ones. This article proposes a model based on descriptive logics, which allows the representation and evaluation of knowledge around the use of AI and research in state universities in Peru. The represented knowledge can be refined, socialized and enriched by specialists. It can also be represented in the form of ontologies, which can be materialized with the help of the famous Protégé software. [ABSTRACT FROM AUTHOR]