Co-teaching as a model for scholarly interactions and the acceptance of limits to knowledge
Bibliographic record
Abstract
Co-teaching has been shown to be an effective instructional tool in a range of academic settings. In this contribution, we are extending the list of benefits. Using quantitative and qualitative approaches, we assessed the impact of a co-taught, interdisciplinary course on students' perception of their own role as scholars, and on how students interact with their peers and their instructors in the classroom. Students clearly perceived and appreciated the benefits of having two professors from two different disciplines teaching an interdisciplinary course. They also paid close attention to the interaction between the instructors, noting that they rarely see scholars question or correct each other. Students recognized that there are limits to any scholar's knowledge, and that it is normal for researchers to ask questions of one another. Importantly, they came to see interactions between co-teachers as a model for their own role and behavior as scholars, and they took an acceptance of limits to knowledge with them beyond this one co-taught course.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".