A MODEL TO DEVELOP PEER FEEDBACK SKILLS IN FIRST-YEAR ENGINEERING STUDENTS
Bibliographic record
Abstract
Abstract – Giving and receiving feedback is a necessary, but often difficult skill for young engineers to acquire. We developed and piloted the delivery of a feedback model as part of the first-year engineering experience at the University of British Columbia. The approach is based on recognizing feedback as a form of professional communication, and that it requires practice to improve. We wove different aspects of communication skill development through two large newly-designed first-year introduction to engineering courses, building towards face-to-face feedback through a staged series of communication experiences. 
 The full feedback model highlighted the nuances of face-to-face communication, and was called the "3×3", since it includes the three components involved in face-to-face feedback (sender, message, and receiver), each with three associated aspects. The sender uses appropriate words and body language, ensures proper interpretation, and is empathetic; the message is objective and non-judgmental, sufficiently detailed, and contains suggestions for improvement; and the receiver remains open and listening, acknowledges to the sender that they are listening, and clarifies to ensure understanding. 
 Students applied what they had learned through an activity reviewing poster presentations from a major course design project. In the activity, they each had an opportunity to craft a feedback message before delivering the message face-to-face to a peer. Students then reflected on the feedback they received by summarizing the message, recognizing how the sender delivered the feedback, and identifying why the feedback was helpful. Student reflections were analyzed for themes from the 3×3 model. 
 Students found feedback from peers particularly helpful when it was delivered in an appropriate and courteous manner, checked for proper interpretation, provided clear suggestions for improvement, and was coupled with praise of something that was done well.
 Providing students with a structured model allows them to follow a process in both providing effective face-to-face feedback, but also better appreciate why receiving feedback is beneficial in helping them improve.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".