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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis
2025-01-01
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| Series: | Research in Statistics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27684520.2024.2433290 |
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