Bibliographic record
Abstract
The need for empirical research that assesses the outcomes of teaching development programs for graduate students is increasingly recognized.The current study investigated the effectiveness of a skills-based teaching assistant (TA) training program for novice TAs.In addition, a second objective was to assess whether the addition of reflective writing activities to the regular program led to larger gains in outcomes.Results indicated that overall TAs improved the frequency of effective teaching behaviours across the program but showed no changes in their intentions to engage in further professional development.No differences in teaching behaviours were observed between TAs who did or did not complete the reflective writing component of training.Despite no observed differences in teaching behaviours between groups, analysis of TAs' written reflections indicated that student engagement was mentioned more frequently by TAs at the end versus the beginning of training.TAs identified that they had learned specific skills related to pacing of instruction, organization and clarity of content, communication behaviours, and student engagement, as well as learned the value of confidence and practice.One implication of the results is to consider how further programming for TAs can build on these initial teaching outcomes.
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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 | 0.015 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".