Bibliographic record
Abstract
This paper focuses on instructor led, student-focused coaching sessions undertaken in the senior (capstone) design classes at the University of Manitoba. The team-based design approach used in capstone courses allows students to work in a manner more closely reflecting industry practice; however, team writing does not allow for individualized scaffolding which could ensure each graduate meets the standard for communicative competence. Rather than allow students to rely on the team’s collective communication skills, we developed an approach that incorporates individual coaching sessions at multiple stages in the writing process. These sessions require students to reflect upon their work, and allow them to discuss it in a meaningful way with the instructor. Doing so at various stages affords students the opportunity to engage in an iterative approach to developing communicative competence: applying what they learn, reflecting on their work, and discussing communicative gains and new methodologies.While integrating individual coaching and directed instruction into the curriculum can be challenging, this paper demonstrates how student-focused coaching sessions provide a platform from which senior design students can increase both communicative competence and their value to industry as future engineers
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".