Positioning undergraduate teaching and learning assistants as instructional partners
Bibliographic record
Abstract
Undergraduate teaching and learning assistants (UTLAs) can help to implement student-centered learning and collaborate with faculty as instructional partners. Researchers have documented the benefits of student-faculty instructional partnerships, but additional research is necessary to better understand how UTLA-faculty partnerships are established and sustained. In this study, I explored how UTLAs are positioned in interactions with faculty for two undergraduate courses at a large, public research institution over the Fall 2018 semester. This in-depth examination revealed UTLAs may be positioned as students, informants, consultants, co-instructors, or co-creators. Positioning of UTLAs changed moment-by-moment, and the different positions were not always mutually exclusive. Thus, UTLA-faculty partnerships are complex and dynamic; even when ranking or characterizing partnerships broadly, considering variety and fluidity in positioning may help uncover the nuances behind different partnerships. This research provides insight into the interactions of collaborative UTLA-faculty instructional partnerships and the factors that may affect those interactions.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".