Effective Use of Graduate Students as Teaching Assistants in Undergraduate Engineering Education
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
Undergraduate Engineering Education can be significantly enhanced through the effective use of Teaching Assistants. Traditionally, Teaching Assistants have been viewed as support for the instructor, but as student-centred learning models take more precedence, the role of the Teaching Assistant is changing to adapt. Recognizing the challenges presented by large class sizes and Teaching Assistants’ limited teaching experience, how can we effectively employ graduate students as Teaching Assistants to enhance undergraduate learning in engineering? This paper provides details on the approach taken by Memorial University to support Teaching Assistants as educators and to draw on their experience and enthusiasm for engineering education. It also examines the approach taken in one undergraduate engineering course to engage Teaching Assistants with the content, the students, and the professor.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it