Science students' perspectives on how to decrease the stigma of failure
Bibliographic record
Abstract
Failure is hard-wired into the scientific method and yet teaching students to productively engage with failure is not foundational in most biology curricula. To train successful scientists, it is imperative that we teach undergraduate science students to be less fearful of failure and to instead positively accept it as a productive part of the scientific process. In this article, we focus on student perceptions of the stigma of failure and their associated concerns to explore how failure could be better supported within and beyond a university context. Through a survey of first-year biology students, we found that societal and familial pressures to succeed were the greatest contributing factors to students' fear of failure. In student suggestions on how to reduce the stigma of failure within and beyond the university context, the most common theme identified across both contexts was for increased discussion and open communication about experiences of failure. Importantly, student comments in this study bring attention to the role of factors beyond the classroom in shaping student experiences of failure within their biology 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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".