Emotion as the hidden curriculum: The case of student anxiety
Bibliographic record
Abstract
The primary research focus of Dr. Schussler’s lab is the shaping of undergraduate learning environments to foster meaningful student learning. Although learning environments are organized around specific curricula, the effectiveness of the curriculum is often impacted by the instructor and/or student perception of the instructor. Much of my lab’s research has focused on this interplay between curricula and the instructor and how it affects student learning. Some lab research specifically informs teaching professional development (TPD) for biology graduate teaching assistants. We have found, for example, that student perceptions of GTAs change over the semester, are impacted by the title the GTA uses with their students, and are linked to particular teaching behaviors that can predict perception of teaching effectiveness. These lines of research led to the creation of an NSF-funded research coordination network (BioTAP) focused on improving GTA TPD. BioTAP members have co-published a national survey on the state of GTA TPD at institutions across the US and Canada and proposed a conceptual model for conducting research on GTA TPD programs, which is used as part of the BioTAP Scholars program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".