Mentoring as a Means for Transforming Mentor-Teachers' Practical Knowledge: A Case Study from Greece
Bibliographic record
Abstract
The purpose of this research article is to reveal hidden possibilities about how mentor-teachers’ professional development through the transformation of their practical knowledge could occur into a mentoring context enhancing the role of schoolteachers as mentors. Drawing on Transformative Learning Theory literature, the study explores how five secondary teachers, involved in a mentoring program with such an orientation, come to transform or negotiate their previous conceptions of teaching, learning, and teacher’s role. The results of the qualitative data analysis reveal the transformative potential of this specific mentoring situation as well as the four types of interwoven mentoring experiences influencing the mentors’ knowledge transformation processes: innovative ideas/practices student-teachers enact in classrooms, questions on “how” and “why” of mentors’ teachings, creation of an informal mentors’ learning community, and the presence among them of a colleague having already developed a reflection-stance. The article’s contribution lies in highlighting new aspects of meaningful mentoring experiences fostering mentors’ knowledge transformation and development.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".