Artificial intelligence in the emotional learning of higher education students: a systematic review

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DOI:

https://doi.org/10.5281/zenodo.23383679

Keywords:

Artificial intelligence, emotional learning, university students

Abstract

Artificial intelligence (AI) in higher education is essential, as it contributes to well-being and the personalization of emotional learning, in addition to adapting the educational process. It enables the detection of emotions through facial recognition, voice analysis, and natural language processing; however, it presents limitations related to accuracy, bias, privacy, consent, and cultural differences in the assessment of college students’ moods. Its effects on the emotional dimension of learning continue to yield mixed results and require a systematic synthesis of the existing evidence. The present study aims to analyze the scientific evidence on the use of artificial intelligence in the emotional learning of higher education students through a systematic review based on the PRISMA 2020 guidelines. A systematic review method was applied to scientific studies published between 2020 and 2026. Searches and selection based on eligibility criteria were conducted through August 28, 2026, analyzing 29 studies from the Scopus, Web of Science, and SciELO databases that addressed artificial intelligence and emotional learning among higher education students. The results were synthesized and grouped into six categories, which were constructed using a mixed-methods approach: the process began with defined conceptual dimensions, and emerging categories were included during the data extraction process. Four researchers conducted the coding independently and resolved discrepancies through consensus. It is concluded that the scientific evidence suggests that AI can promote emotional learning among higher education students when used as a support tool and with appropriate pedagogical mediation that generates positive emotions in students. However, its potential advantages coexist with risks that may affect autonomy, well-being, and human relationships.

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Published

2026-10-12

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Section

Communication of Science: Bibliometrics and systematic reviews.

How to Cite

Príncipe Bayona, A. O., Pastor Aguero, F. M., Saldaña Chinchayan, M. B., & García-García, E. E. (2026). Artificial intelligence in the emotional learning of higher education students: a systematic review. InveCom Journal, 6(Especial 2), 1-17. https://doi.org/10.5281/zenodo.23383679

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