Resumen

CALERO VELASCO, DIEGO F. et al. Obtaining Insights from a Natural Language Processing model for naming academic programs in higher education. Ing. Desarro. [online]. 2024, vol.42, n.2, pp.145-163.  Epub 01-Jul-2024. ISSN 0122-3461.  https://doi.org/10.14482/inde.42.02.528.748.

Natural Language Processing (NLP) is recognized as essential in Artificial Intelligence for the interaction between computers and humans. In this article, the use of NLP and visualization techniques in the creation of a model for insights acquisition in the design of new academic programs was explored. The quantitative methodology use techniques such as tokenization and TextRank, and with the support of the Scattertext Plot, discriminate categories on doctoral programs in information technologies. This methodology, validated by experts and widely used, highlighted particularities, general knowledge, and emerging trends in the compared programs. The results identify four essential quadrants for decision-making in program design, and shows current and future needs in program naming. In conclusion, the study underscores the importance of NLP in contemporary academic design and provides a robust tool for program designers.

Palabras clave : academic programs design; insights generation, natural language processing; visualization approach.

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