Generic and specific competences of the mentor teacher: higher education students perception in the health area
Bibliographic record
Abstract
Introduction: The mentoring process is dynamic, reciprocal and reflexive, hence skills as a disposition to act in a relevant way in relation to a specific situation (Le Boterf, 2003), need to be evaluated in the mentoring processes. The mentor refers to a more experienced professional who guides, teaches, directs, supports and advises a student with less practice, playing an important role on a personal and professional level (Botti & Rego, 2007). Objetive: To evaluate the perception of the college students about the supervisory skills that need to be obtained by the mentor teacher. Methods: The cross-sectional descriptive study was carried out on a sample of 306 college students of the health area, of a polytechnic, with an average age of 21.15 years and a higher percentage of women (81.7%). The gathering of Information was supported by the application of Generic, specific and meta-competences of the supervisor scale (Cunha, Cruz, Menezes & Albuquerque, 2017) and Supervisor Core competencies scale (Cunha & Albuquerque, 2017), available online in the academic institution site. Results: The study allows us to conclude that the most important characteristics necessary for the mentor teacher, for college students, are the supervisor's generic skills (average = 4.36 and SD = 0.47), and personal factors (averagde = 4.83 and SD = 0.46). The supervisor's core competencies predicts the supervisor's generic, specific and meta-competencies skills, explaining their 70% variation. The results support the importance of the assignment of a mentor teacher in college (87.5%), and the monitoring should be effective from the 1st to the 3rd / 4th year (60.4%). They also suggest the preference of daily sessions (51.6%) in the training place (52.4%), lasting less than one hour (49.7%). Conclusions: The importance of monitoring the pedagogical competences of supervision and mentoring emerges from the study and the results suggest that the students of higher education value the existence of a mentor teacher, so their attribution is pertinent to consolidate the mission all dimensions of pedagogical action.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".