The development of Critical Thinking Skills during Practical Training: The Perspectives of Pedagogical Supervisors and Sports and Physical Education Trainees
Bibliographic record
Abstract
In the Republic of Congo, initial teacher training has both a theoretical and a practical dimension. Theoretical training takes the form of theoretical courses within the training institution itself. Practical training, on the other hand, takes place in professional settings (secondary schools). This comparative study consisted of identifying the conceptions relating to the development of critical thinking by educational supervisors and by student-trainees. Inscribed in a qualitative methodological approach, this research was based on Eric Lavertu's (2013) conceptual approach to the development of critical thinking in internships. Eight (08) educational supervisors and nineteen (19) student-trainees voluntarily participated in the study via three focus groups. The results obtained, following a content analysis of the corpus collected, reveal several didactic-pedagogical devices for the development of student-trainees' critical thinking, both according to the perception of pedagogical supervisors, and also, according to that of student-trainees. As didactic-pedagogical devices, educational supervisors identify three: the communication strategies highlighted by the supervisor, the climate of exchange established by the supervisor and the attitude of the supervisor. The student-trainees, for their part, emphasize the educational supervision environment, the attitude of the supervisor and the attitude of the student-trainee. Thus, to promote the development of critical thinking among student trainees, the measures mentioned specify that the supervisor must implement a pedagogical approach to supervision anchored in a social-constructivist paradigm to support the development of the student, using a reflective approach in support. In addition, these mentioned systems emphasize the importance of placing the student at the center of their learning by making them a real actor in their development.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".