Making Collaboration Work: Fostering Positive Experiences and Attitudes around Psychological Safety, Diversity, and the Value of Teamwork
Bibliographic record
Abstract
The ability to work well in a team is becoming increasingly important across disciplines and throughout the workplace, making it a valuable skill for students to develop. Evidence suggests that diverse perspectives can generate more innovative ideas and enhance critical thinking, but only if team members value diversity and share knowledge with one another. To foster students’ abilities to work well in diverse teams, we must teach them why collaboration is important and how to bring about its benefits. We describe a new interdisciplinary course designed with these goals, along with an evaluation of the degree to which students who take this course show changes in attitudes and beliefs around teamwork. The course emphasizes psychological safety—a measure of how safe a team is for interpersonal risk-taking. Research shows that psychological safety is an important predictor of team success and a key mechanism for incorporating diverse perspectives. We surveyed students at the start of the course, the end of the course, and just after the following term. At the end of the course, students reported increased psychological safety in their teams, more positive attitudes towards teamwork, and stronger beliefs that diversity is beneficial. At the end of the following term, students reported higher levels of psychological safety in their teams than before the course, and their attitudes about psychological safety and teamwork still remained more positive. We discuss implications of these findings for researchers studying student teamwork and for instructors who wish to introduce or improve collaborative experiences in their courses.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".