Researchers' Seedbeds for the Development of Research Skills in Universities
Bibliographic record
Abstract
The objective of this study is to demonstrate the effects of the application of the pedagogical strategy "researcher's seedbed" in the development of research skills in universities. This research is of quasi-experimental, longitudinal and prospective design, where 2 groups were formed: control and experimental, of 18 students each. A validated instrument was used to measure the research competences, as well as a rubric for the evaluation of the research projects. It began with a pre-test, and after 14 weeks of the development of the strategy, through different educational sessions, the post-test was administered. Likewise, the research projects carried out were evaluated. The results obtained showed that the pedagogical strategy had a positive effect on the development of research skills, with the highest evaluation being found in 40% of the students, with statistically significant differences between the control and experimental groups (Mann Whitney U, p=0.007), and between the pre-test and post-test (Wilcoxon, p=0.00). In the development of cognitive and procedural competence, an effect was also found in the strategy, but not in the attitudinal competence (Mann Whitney U, p=0.496). The application of this study is based on the fact that the formation of research groups in universities strengthens formative research in higher level students. This study shows the benefits of the implementation of strategies for the development of research competencies, since the product will be to train professionals with a scientific culture in favor of society.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".