TRAINING TEACHING ASSISTANTS AS COACHES
Bibliographic record
Abstract
Abstract – The role of graduate teaching assistants (GTAs) is becoming more demanding as engineering education places an increased emphasis on teamwork and design. For undergraduate students to excel, GTAs must help them form well-functioning teams and encourage them to operate as self-directed learners. In other words, GTAs should operate more as coaches rather than teachers. Many GTAs, unfortunately, lack the basic competencies of to perform as a coach. In this work, we present a 3-hour workshop designed to address this skills gap. The role of a coach and basic theoretical concepts, as well as a simple tool to elicit self-reflection in students are presented through a series of experiential exercises and discussions. The exercises also give participants an opportunity to practice these newly acquired skills while developing confidence in identifying scenarios where the tool may be applied. This workshop has been executed once with a group of 10 graduate engineering students at the University of Victoria. Survey results have been encouraging, we believe that the participants successfully acquired basic coaching competencies and applied them to their interactions with undergraduate students.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".