Effectiveness of past and current critical incident analysis on reflective learning and practice change
Bibliographic record
Abstract
OBJECTIVES: Critical incident analysis (CIA) is one of the strategies frequently used to facilitate reflective learning. It involves the thorough description and analysis of an authentic and experienced event within its specific context. However, CIA has also been described as having the potential to expose vulnerabilities, threaten learners' coping mechanisms and increase rather than reduce their anxiety levels. The aim of this study was to compare the analysis of current critical incidents with that of past critical incidents, and to further explore why and how the former is more conducive to reflective learning and practice change than the latter. METHODS: A collaborative research study was conducted. Eight occupational therapists were recruited to participate in a reflective learning group that convened for 12 meetings held over a 15-month period. The group facilitator planned and adapted the learning strategies to be used to promote reflective learning and guided the group process. Critical incident analysis represented the main activity carried out in the group discussions. The data collected were analysed using the grounded theory method. RESULTS: Three phenomena were found to differentiate between the learning contexts created by the analysis of, respectively, past and current critical incidents: attitudinal disposition; legitimacy of purpose, and the availability of opportunities for experimentation. Analysis of current clinical events was found to improve participants' motivation to self-evaluate, to increase their self-efficacy, and to help them transfer learning into action and to progressively self-regulate. CONCLUSIONS: The results of this collaborative research study suggest that the analysis of current clinical events in order to promote reflection offers a safer and more constructive learning environment than does the analysis of incidents that have occurred in the past. This learning strategy is directly grounded in health professional practice. The remaining challenge for continuing education providers is that of creating conditions conducive to its use.
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How this classification was reachedexpand
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".