Inquiry-based training improves teaching effectiveness of biology teaching assistants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Graduate teaching assistants (GTAs) are used extensively as undergraduate science lab instructors at universities, yet they often have having minimal instructional training and little is known about effective training methods. This blind randomized control trial study assessed the impact of two training regimens on GTA teaching effectiveness. GTAs teaching undergraduate biology labs (n = 52) completed five hours of training in either inquiry-based learning pedagogy or general instructional "best practices". GTA teaching effectiveness was evaluated using: (1) a nine-factor student evaluation of educational quality; (2) a six-factor questionnaire for student learning; and (3) course grades. Ratings from both GTAs and undergraduates indicated that indicated that the inquiry-based learning pedagogy training has a positive effect on GTA teaching effectiveness.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it