Monitoring the Results of the Tutoring Program in its Face-to-Face and Virtual Modalities on the Academic Achievement of Students at a Mexican University
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The tutorship program is aimed at supporting students throughout their university career and its objective is to prevent future problems of adaptation in the educational ambience as well as intervening in matters of academic achievement. At the Instituto Tecnológico de Sonora (Technological Institute of Sonora) (ITSON), the individual tutorship program began in 2000. In 2002 group tutoring began in order to see to the entire first year student population and today group tutoring is offered in both the face-to-face and virtual modalities. The general objective of the present study is to determine the impact the programs of face-to-face and virtual tutoring at the ITSON has had on students’ academic achievement, during the four semesters after having participated in this program. Information on 2,995 students from the different areas of study offered at the university was collected from databases which existed at the Institute and analyzed using different statistical techniques. The tutoring program is shown to have had a favorable impact on the index of students’ failing classes, during the semester they were enrolled in tutoring, but not during the subsequent semesters, during which they did not participate in the tutorship program. The grade point averages obtained by students who had face-to-face tutoring were statistically different from those of the students who did not have tutoring. This was true for all of the semesters analyzed. The same thing happened with the students who had virtual tutoring except for during the second semester when the two were statistically equal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it