Factores socioeconómicos y académicos que explican el rendimiento escolar en la Universidad Tecnológica El Retoño (UTR)
Bibliographic record
Abstract
Abstract The globalized world is demanding better prepared professionals, so dentifying the variables that affect academic performance is of particular interest. The objective of this research was to determine the socioeconomic factors (municipality of residence, schooling and occupation of the father and mother, socioeconomic level) and academic factors (high school of origin, high school GPA, EXANL-II score), which explain the performance of students of the 2018-2020 generation of the Universidad Tecnológica el Retoño (UTR), at the end of the 3rd and 5th quarter, through a correlational, multivariate and longitudinal study with a quantitative approach, using a Beta Regression. The variables that have a positive impact in the 3rd quarter are: high school GPA, coming from a technological high school, mother’s schooling and EXANL-II result; and, in the 5th quarter: the high school average and the EXANL-II results, with a negative influence due to having graduated from the Colegio Nacional de Educación Profesional Técnica (CONALEP). In both quarters, living in a rural environment had a negative impact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".