Finding the Self that Teaches: A Co-active Coaching Approach to Mindful Practice and Wellbeing in Education
Bibliographic record
Abstract
Finding the Self that Teaches:A Co-active Coaching Approach to Mindful Practice and Wellbeing in Education Doctor of PhilosophyMargaret E. Adam Department of Curriculum, Teaching and Learning Ontario Institute of Studies in Education University of Toronto 2021 Abstract This research is a qualitative study concerned with developing teachers’ ongoing professional learning through the lens of co-active coaching. It seeks to explore the mechanisms of a holistic model of co-active coaching that influence and deepen Ontario secondary school teachers’ understanding of the self in practice. It includes a self-study that investigates my professional development as a co-active member of the research. The study examines the ways in which learning occurs to cultivate mindful practice and wellbeing in teachers. The co-active coaching model is framed largely by a holistic approach to learning supported by Whitworth et al. (2007) who emphasize the quality and importance of relationship in learning. Co-active coaching is collaborative, non-directive, and co-creative where the desired outcome is a mutual growth in self-understanding and improved performance in teaching. Five secondary school teachers engaged in professional learning and collaboration over 9 months, where they reflected on their development of the self in practice. The narrative analysis of teacher learning indicates a positionality of the teacher in “Finding the Self that Teaches” and is demonstrated through the beliefs, assumptions and practices that emerge from their narratives. The results of this study demonstrate that learning occurs through multiple orientations to teaching and learning. The inward reflection of the participants indicates that a key thread of “who teachers are” is woven through the fabric of “what they do” in practice. Teacher participants reported changes in their thinking and a shift in their perspectives of their own wellbeing and their practices. They demonstrated that co-active coaching was a useful means of supporting professional collaboration and positively influencing mindful practice. This research contributes new knowledge to the field of professional learning, holistic education and coaching and has implications for co-active coaching, as a process for building capacity and delivering sustainable, professional learning to teachers—to be used formally in their classrooms and informally with their colleagues. By implementing co-active coaching as a practice for embedded, ongoing professional learning, schools can take action to ensure high quality support for both educators and students.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.029 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".