Could the R2C2 Feedback and Coaching Model Enhance Feedback Literacy Behaviors: A Qualitative Study Exploring Learner-Preceptor Feedback Conversations
Bibliographic record
Abstract
Introduction: Feedback literacy (FBL) is a critical skill for learners encompassing four behaviors: appreciating feedback, making judgements, managing affect, and taking action. Little guidance has been available for clinical preceptors to promote FBL. The R2C2 feedback and coaching model that guides teachers through building Relationships, exploring Reactions and Reflections, discussing Content and Coaching to co-develop an action plan for follow-up may support FBL. This study sought to identify whether R2C2 conversations operationalized FBL behaviors and the factors that appeared to influence FBL. Methods: Based on data from a multi-institutional, qualitative study involving 15 dyads of learners (residents and medical students) and their physician preceptors, a secondary analysis of R2C2-guided feedback conversations and debriefing interviews was undertaken. A framework analysis mapped the data to FBL behaviors and explored factors that impacted behaviors in the context of the research and theories underpinning R2C2 and FBL. Results: Most elements of FBL behaviors were demonstrated in R2C2 conversations. Appreciating feedback and making judgements were most consistently noted. There was less evidence of managing affect as learners indicated acceptance of feedback. There was variability in the co-creation of action plans. Some created action plans, others had incomplete or no plan for immediate action or follow-up. FBL appeared to be impacted by learner-preceptor relationships, active learner engagement in feedback discussions, and personal characteristics. Discussion: Our analysis demonstrated that effective use of the R2C2 model could enhance FBL behaviors provided attention was paid to optimizing all phases of R2C2, particularly co-creation of action plans for follow-up.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".