Participation value of undergraduate students leading STEM outreach: evaluation of academic, personal, and professional effects
Bibliographic record
Abstract
This study explores the academic, professional, and personal career benefits of leading science, technology, engineering, and mathematics (STEM) outreach, from the perspective of undergraduate student leaders. We consider traditional and nontraditional STEM university students, gender, and type of position (paid or volunteer) in this evaluation. Data were collected through an online survey completed by 30 former student STEM outreach leaders from the University of British Columbia. Self-reported survey data indicated that STEM outreach had a moderately strong average impact of 6.89 ± 1.55 out of 10 on participants' personal, academic, and professional development, with no significant differences between these areas. Outcomes did not differ between genders, and paid work was found to contribute to greater personal and professional impact. The positive influence of outreach on academic and professional decision making was higher in traditional STEM fields than STEM-based health-science studies. The outcomes of this research adds insight into positive impacts of STEM outreach on university student instructors.
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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 | 0.000 |
| 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) | 0.000 | 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".