“I Think Many of Them Want to Appear to Have a Growth Mindset”: Exploring Supervisors’ Perceptions of Feedback-Seeking Behavior
Bibliographic record
Abstract
PURPOSE: Feedback seeking is an expected learner competency. Motivations to seek feedback are well explored, but we know little about how supervisors perceive such requests for feedback. These perceptions matter because how supervisors judge requests can affect the feedback they give. This study explores how supervisors perceive and attribute motivations behind feedback requests to better understand the benefits and hazards of feedback seeking. METHOD: Constructivist grounded theory was used to interview supervisors at the Temerty Faculty of Medicine, University of Toronto, from February 2020 to September 2022. Supervisors were asked to describe instances when they perceived feedback requests as being sincere or insincere, what led to their opinions, and how they responded. Transcripts were analyzed and coded in parallel with data collection; data analysis was guided by constant comparison. RESULTS: Seventeen faculty were interviewed. Participants perceived 4 motivations when learners sought feedback: affirmation or praise; a desire to improve; an administrative requirement, such as getting forms filled out; and hidden purposes, such as making a good impression. These perceptions were based on assumptions regarding the framing of the initial request; timing; preexisting relationship with the learner; learner characteristics, such as insecurity; and learner reactions to feedback, particularly defensiveness. Although being asked for feedback was generally well received, some participants reported irritation at requests that were repetitive, were poorly timed, or did not appear sincere. CONCLUSIONS: Feedback seeking may prompt supervisors to consider learners' motivations, potentially resulting in a set of entangled attributions, assumptions, and reactions that shape the feedback conversation in invisible and potentially problematic ways. Learners should consider these implications as they frame their feedback requests and be explicit about what they want and why they want it. Supervisors should monitor their responses, ask questions to clarify requests, and err on the side of assuming feedback-seeking requests are sincere.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".