Becoming Authentic Teachers Through Transformative Inquiry: Final Practicum Challenges
Bibliographic record
Abstract
Within the final teaching practica, pre-service teachers encounter the crucial challenge of redefining their teacher identities. Leaving behind personas formed as students, professional settings necessitate asking themselves what kind of teacher they want to be in a new context. In collaboration with their professor, two pre-service teachers examined their final practicum experiences, highlighting how Transformative Inquiry (TI), a holistic investigative approach, supported them in becoming authentic teachers. We hear how the TI process helped them identify, honour, and strengthen their personal and unique teaching identities. Highlighted themes include: touchstone stories, the power of the circle, living the questions, and the importance of on-going reflection. These new teachers resisted traditional images of teachers by embracing imperfection and vulnerability.
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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 | 0.053 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.049 |
| Scholarly communication | 0.033 | 0.023 |
| Open science | 0.006 | 0.031 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".