An Application of Mezirow’s Critical Reflection Theory to Electronic Portfolios
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, the authors developed a framework for the analysis of teacher reflection in standards-based e-portfolios. Using NVivo, the authors analyzed the written arguments of 127 students, as they provided rationales for why their chosen artifacts represented specific teaching standards. In total, 656 rationales yielded 1,427 statements when categorized using Mezirow’s types of reflection. The findings indicate that subjective reframing, in general, and narrative critical self-reflection on assumptions and epistemic critical self-reflection on assumptions, in particular, are well represented in the University of Northern British Columbia (UNBC) teacher education program as evidenced by approximately 50% of the overall statements represented by these two types of critical self-reflection. As well, Mezirow’s taxonomy appears to be a sound theoretical framework to represent reflection in teacher education.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it