Supporting teacher candidates’ multidimensional reflection: a model and a protocol
Bibliographic record
Abstract
In this conceptual paper, we present a professional practice-oriented Multidimensional Model of Reflective Practice (MMRP) and a Critical Incident Reflection (CIR) protocol as worthwhile tools for supporting teacher candidates (TCs) to become more self-directed, multi-faceted, and holistic in their reflective practice. The model presents reflection as a complex endeavor situated in a dynamic milieu. It emphasizes the complementary nature of professional competencies of knowledge, skills, and disposition, and the interrogation of an incident through technical, contextual, and critical reflection as well as reflection-in, -on, and -for-action. The CIR protocol provides scaffolding support for TCs as they move toward becoming independent reflective practitioners. Together, the MMRP and CIR protocol facilitate multidimensional reflection. We present a case for providing a more deliberate support for reflection. In doing this, we define reflection, highlight its common frameworks, and discuss the significance of intentional and systematic reflection on professional competencies. In the conclusion, we bring these ideas together to discuss the implications for a self-directed and agentic approach to reflection and professional growth.
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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 | 0.198 | 0.180 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".