Capacitación y acompañamiento pedagógico de profesores universitarios noveles: efectos sobre el uso de estrategias de enseñanza
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
Several universities offer teaching continuous development courses and support to new professors with the purpose of leading them to concentrate more on their students’ learning than on transmitting knowledge. However, have such continuous development and follow-up had any effect on the teaching strategies employed by those professors? Is there a distinction between these strategies and those used by professors who are not in continuous development projects? This text presents data collected along three years, through observation and interviews, with 22 new professors, from which 9 are in continuous development courses, 8 have completed such courses and are in a follow-up phase and 5 who have never taken part in continuous development courses. The results have not revealed noticeable difference between these professors, which leads to the conclusion that all of the them employed strategies that go beyond knowledge transmission. Keywords: Continuous development. Education follow-up. New Professors. Teaching Strategies. University.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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