Influence of co-teaching on undergraduate student learning: A mixed-methods study in nursing.
Bibliographic record
Abstract
Co-teaching has been explored in the field of education but is a relatively new phenomenon in higher education. Its benefits and challenges are well documented; however, what is lacking is substantive evidence highlighting the influence of co-teaching amongst undergraduate students. Particularly, in practice-based professions like teaching, nursing, and social work, active participation in collaborative teams is more the norm than the exception. Undergraduate students need to have opportunities to learn how to be collaborative, as well as observe modeling of collaborative teaching practice. In the article, we report on a 2-year mixed-methods research study that investigated students’ and instructors’ experiences with co-teaching in a Nurse as Educator course. The findings from three cohorts engaged in the research suggest co-teaching to be an effective teaching and learning strategy. However, for co-teaching to be a positive experience for both students and instructors, purposeful scaffolding and supports need to be in place. Also outlined are recommendations for higher education with regard to designing and modeling co-teaching practice.
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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 | 0.023 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".