LA FORMACIÓN EN COMPETENCIAS A TRAVÉS DEL PRACTICUM: UN ESTUDIO PILOTO
Bibliographic record
Abstract
The aim of this paper is to diagnose generic skills acquired through the Practicum. A sample of 52 subjects belonging to the degree of Psychopedagogy and Speech Thereapy, Faculty of Science Education at the University of A Coruna (Spain). The instrument used a Likert scale of five categories. The levels of internal reliability (α = 0.960) and construct validity (KMO = 0.787), are optimal. The results obtained through discriminant analysis (Box M = 24.785 and p =. 000 <.05), to establish the profiles and the comparison between the two degrees, suggest that the probationary period is a good time to general work skills, present in all studies, and increasingly demanded by the labor market. Competence profiles that are drawn once analyzed the data tell us, in the case of the degree of Psychopedagogy, a student who stands out for its resolution of problems, be creative, be able to analyze and synthesize, and be self-employment collaborative. The competency profile of Speech Thereapy student is someone organized and planned well, with great resilience and skills to locate and analyze information. Weaknesses point aspects to consider in the planning of courses leading to the professional profile. In the case of psychopedagogy should place greater emphasis on organization and planning capacity, improved resilience and localization and analysis of information. Speech therapists, for their part, need to strengthen the capacity of problem solving, creativity, capacity for analysis and synthesis as well as the ability of independent work and iniciative and the ability to work collaboratively.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".