Encouraging reflective practice in the teacher education practicum: A dean’s early efforts
Bibliographic record
Abstract
This article presents an analysis of a dean’s early efforts to encourage reflective practice in the teacher education practicum, in consultation with a critical friend. The focus is on the importance of listening and the identification of assumptions underlying practices. The authors met in 2010 in a week-long seminar focused on the practicum in teacher education programs at a university in Santiago, Chile. A long conversation over dinner one evening revealed a significant interest in each other’s perspectives and experiences. Since that time, more than 20 opportunities to visit each other in Chile and in Canada have established an on-going connection for sharing insights as they emerge from experiences in each other’s country. The authors now consider themselves to be life-long critical friends. In April 2021, Rodrigo was appointed as Dean of Education at Universidad Autónoma in Santiago, with an early focus on encouraging reflective practice by all who are involved in the teacher education practicum—student teachers, mentor teachers and faculty supervisors. Tom retired in 2019 after 42 years in teacher education practice and research at Queen’s University, and he continues to explore the complex issue of how people learn to teach.
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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 | 0.060 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.021 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.011 |
| 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 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".