Artificial Intelligence and Educational Quality in Universities: Challenges and Opportunities
DOI:
https://doi.org/10.5377/ryr.v1i62.21746Keywords:
academic standard, higher education, artificial intelligence, learningAbstract
This research examines the impact of artificial intelligence (AI) on the quality of higher education, a topic addressed from a critical and multidimensional perspective. The theoretical framework integrates key learning theories—information processing, cognitive load, value-expectancy motivation, and self-regulation—with the analysis of technological applications in university contexts. Among the core arguments, it highlights that AI offers opportunities to personalize learning, enhance feedback, optimize institutional management, and promote inclusion and accessibility through systems such as intelligent tutoring, learning analytics, and chatbots. However, the document also warns of relevant challenges: ethical concerns related to data privacy, risks of algorithmic bias that may affect equity, the potential dehumanization of the educational process due to excessive automation, and threats to academic integrity, such as plagiarism facilitated by generative tools. The analysis underscores that AI integration must complement the teaching role and be guided by ethical and humanistic principles, to prevent technology from constraining students’ autonomy and critical thinking. It recommends the active participation of the entire educational community, training in digital competencies, transparency, and the development of clear policies. In conclusion, AI can contribute to a more inclusive and higher-quality higher education system if its implementation respects ethical values and preserves the centrality of the human being in the educational process.
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© Universidad Francisco Gavidia
Instituto de Ciencia, Tecnología e Innovación (ICTI)
Reality and Reflection
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