Unpacking Reflection in Teacher Education: How Teacher Candidates Perceive, Experience, and Develop Reflective Practice
Bibliographic record
Abstract
This qualitative study examines the role of reflective practice in the development of teacher candidates within one Initial Teacher Education (ITE) program in Ontario. Grounded in a constructivist paradigm, the study explores how reflection serves as a bridge between theoretical knowledge and practical teaching experiences, enabling teacher candidates to develop adaptive expertise, critical pedagogical skills, and professional identity. The research was conducted in 2024, nearly a decade after the implementation of Ontario's Enhanced ITE, which expanded program duration and emphasized reflective practice as a cornerstone of teacher preparation. The study employs a case study methodology, using data from semi-structured interviews, reflective journals, and program documents. Guided by a conceptual framework emphasizing the interplay between theory and practice, data analysis followed an iterative, thematic approach to explore teacher candidates' perceptions and enactments of reflective practices. Findings reveal that teacher candidates' perceptions of reflection center on its role as a continuous learning and problem-solving tool, while highlighting tensions between formal, program-mandated reflections and informal, self-directed practices. Participants were able to bridge theory and practice, but their critical reflections were less frequent. This research, I conclude, highlights reflective practice as a vital mechanism for professional growth in teacher education. It underscores the need for context-sensitive approach that connects teacher candidates' lived experiences with the realities of classroom teaching. By integrating meaningful reflection into both coursework and practicum experiences, ITE programs can better prepare socially responsive, adaptive, and equity-focused educators, bridging the gap between theory and practice and fostering lifelong professional 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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".