Using explainable AI to align pre-university profiles with bachelor’s degree success
Juan Ramón Rico-Juan, María Luisa Pertegal-Felices, Antonio Jimeno-Morenilla · 2025
Read Using explainable AI to align pre-university profiles with bachelor’s degree success by Juan Ramón Rico-Juan, María Luisa Pertegal-Felices, Antonio Jimeno-Morenilla (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12727684.txt.
Description
Juan Ramón Rico-Juan, María Luisa Pertegal-Felices, and Antonio Jimeno-Morenilla build a degree guide for new university students in a 2025 paper. Choosing a bachelor's program blind leads many students to poor grades or dropout. The team trained machine learning models on about seventy-two thousand records from a Spanish university, spanning 2010 to 2022. The tool matches a school leaver's profile to degrees where like students thrived.
Its top five picks proved right seventy percent of the time, and its top ten ninety percent. Explanation tools showed which school subjects push toward or away from each degree. Geography, for instance, pointed away from computer engineering. Counselors get profiles they can explain, not just a bare list of picks.
Catalog record
| CREATOR | Juan Ramón Rico-Juan, María Luisa Pertegal-Felices, Antonio Jimeno-Morenilla |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 53 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |