Application of Non-Supervised Learning Tools and Visualization Techniques to Understand the Intrinsic Freshmen Enrollment Segmentation: An application to freshmen engineering students.

Identifying significant subgroups among first-year students is crucial for designing educational policies that foster their academic and personal development. This study presents a data-driven methodology to segment first-year students using sociodemographic factors, admission test scores, and initi...

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Detalhes bibliográficos

Principais autores:	Patricio Salas, Rodrigo De la Fuente, Patricio Sáez, Andrés Riquelme
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Taylor & Francis 2025-12-01
coleção:	Research in Statistics
Assuntos:	Freshmen enrollment analysis Data-driven methodology Academic information visualization Higher education institutions
Acesso em linha:	https://www.tandfonline.com/doi/10.1080/27684520.2024.2433290
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