Preparing and Supporting Graduate Students in Their Role as Teaching Assistants: An Exploration of TA Training in a School of Criminology
Bibliographic record
Abstract
Teaching Assistants (TAs) play an important role in many undergraduate courses throughout North America. TAs have a range of responsibilities to fulfil, such as facilitating tutorials, delivering lessons, applying rubrics, invigilating exams, and/or providing students with feedback and academic support during the term. This article presents key findings from a project designed to identify how TAs in a School of Criminology in Western Canada are currently being prepared for and supported in their roles as TAs, their perceived utility of the preparation they receive, and their recommendations to improve their training and support preparation. Given the centrality of TAs in the delivery of undergraduate education, it is vitally important that institutions adequately train and support graduate students for their roles. This article provides recommendations for individual instructors, academic units, and universities to consider to better prepare and support graduate students for their increasingly complex roles as TAs.
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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 | 0.008 | 0.018 |
| 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 | 0.003 |
| 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".